U.S. patent application number 14/947685 was filed with the patent office on 2016-03-17 for sensor strip for gathering human biological signals and controlling a bed device.
The applicant listed for this patent is Eight Sleep, Inc.. Invention is credited to Massimo Andreasi Bassi, Matteo Franceschetti.
Application Number | 20160073788 14/947685 |
Document ID | / |
Family ID | 54434442 |
Filed Date | 2016-03-17 |
United States Patent
Application |
20160073788 |
Kind Code |
A1 |
Franceschetti; Matteo ; et
al. |
March 17, 2016 |
SENSOR STRIP FOR GATHERING HUMAN BIOLOGICAL SIGNALS AND CONTROLLING
A BED DEVICE
Abstract
Introduced are methods and systems for an adjustable bed device
configured to: gather biological signals associated with multiple
users, such as heart rate, breathing rate, or temperature; analyze
the gathered human biological signals; and heat or cool a bed based
on the analysis.
Inventors: |
Franceschetti; Matteo; (San
Francisco, CA) ; Bassi; Massimo Andreasi; (San
Francisco, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Eight Sleep, Inc. |
San Francisco |
CA |
US |
|
|
Family ID: |
54434442 |
Appl. No.: |
14/947685 |
Filed: |
November 20, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14732646 |
Jun 5, 2015 |
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14947685 |
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62008480 |
Jun 5, 2014 |
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62024945 |
Jul 15, 2014 |
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62159177 |
May 8, 2015 |
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62161142 |
May 13, 2015 |
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Current U.S.
Class: |
219/486 ; 156/60;
219/490; 219/494; 600/508; 600/529; 600/549; 600/595 |
Current CPC
Class: |
A61M 21/02 20130101;
A47C 21/00 20130101; A61M 2205/3673 20130101; A61M 2021/0066
20130101; A61M 2205/3584 20130101; A61B 5/024 20130101; A61B
5/02055 20130101; G05B 2219/2614 20130101; A61M 2230/63 20130101;
A61B 2505/07 20130101; A61M 2205/3306 20130101; A61B 5/01 20130101;
A61B 5/4812 20130101; A61M 2205/0294 20130101; A61B 5/0022
20130101; A61B 5/7455 20130101; A61M 2230/06 20130101; G08B 6/00
20130101; G16H 40/67 20180101; H05B 1/0272 20130101; A61M 16/161
20140204; A61M 2205/505 20130101; A61B 2560/0242 20130101; A61M
2205/3368 20130101; A47G 9/0238 20130101; A61M 2205/50 20130101;
A61M 2230/50 20130101; A61B 2562/063 20130101; G05D 23/1393
20130101; A61M 2205/3375 20130101; A61B 5/0816 20130101; A61B
2560/0475 20130101; G05B 19/0428 20130101; A47C 21/044 20130101;
A47C 31/123 20130101; A61B 5/6892 20130101; A61B 5/117 20130101;
A61M 2021/0083 20130101; A61M 2205/3592 20130101; A61M 2205/3303
20130101; A61M 2230/42 20130101; A61B 2562/0271 20130101; A61B 5/11
20130101; A61M 2205/18 20130101; A61B 5/4266 20130101; A61M 21/00
20130101; A47C 21/048 20130101; A61M 2021/0022 20130101; A61M
2230/42 20130101; A61M 2230/005 20130101; A61M 2230/06 20130101;
A61M 2230/005 20130101; A61M 2230/50 20130101; A61M 2230/005
20130101 |
International
Class: |
A47C 21/04 20060101
A47C021/04; A61B 5/11 20060101 A61B005/11; A61M 21/02 20060101
A61M021/02; H05B 1/02 20060101 H05B001/02; A61B 5/0205 20060101
A61B005/0205; A61B 5/00 20060101 A61B005/00 |
Claims
1. A system for automatically heating a mattress comprising: a
sensor strip, comprising: a user sensor configured to measure a
biological signal associated with a user, wherein said user sensor
comprises a piezo sensor and a temperature sensor, and further
wherein said biological signal comprises a heart rate associated
with said user and a breathing rate associated with said user; and
a computer bus, wherein said computer bus comprises three straight
strips, wherein said three straight strips include a first strip
coupled at a first right angle to a second strip, and said second
strip is coupled at a second right angle to a third strip, and
further wherein said first strip is configured to bend backwards at
specified locations, thereby extending a total length of said
sensor strip; and an environment sensor associated with a bed, said
environment sensor configured to measure an environment property,
wherein said environment property comprises a temperature, a
humidity, a light intensity, or a sound; and a coil, divided into a
plurality of zones corresponding to a plurality of users, wherein
each zone of said plurality of zones is controlled independently of
remaining zones of said plurality of zones, and wherein each said
zone is further divided into a plurality of subzones, wherein said
coil is configured to uniformly heat each subzone in said plurality
of subzones; and a computer processor communicatively coupled to
said sensor strip and said coil, said computer processor configured
to determine a control signal, and a time to send said control
signal to said coil.
2. The system of claim 1, wherein said control signal comprises an
instruction to heat said coil to a high temperature, wherein said
high temperature comprises an average high temperature associated
with said user.
3. The system of claim 1, wherein said time comprises average
bedtime associated with said user.
4. A system comprising: a sensor strip, comprising: a user sensor
configured to measure a biological signal associated with a user;
and a computer bus configured to bend at specified locations,
thereby changing a length of said sensor strip; and a coil,
configured to modify temperature of a mattress; and a computer
processor communicatively coupled to said sensor strip and said
coil, said computer processor configured to determine a control
signal, and a time to send said control signal to said coil.
5. The system of claim 4, wherein said coil is divided into a
plurality of zones corresponding to a plurality of users, wherein
each zone of said plurality of zones is controlled independently of
remaining zones of said plurality of zones.
6. The system of claim 5, wherein each said zone is further divided
into a plurality of subzones, wherein said coil is configured to
uniformly heat each subzone in said plurality of subzones.
7. The system of claim 6, wherein said coil has a density that is
higher in said subzone corresponding to lower back, or feet, than
in said plurality of subzones corresponding to other parts of said
user's body.
8. The system of claim 5, wherein each said zone is further divided
into a plurality of subzones, wherein said coil is configured to
uniformly cool each subzone in said plurality of subzones.
9. The system of claim 8, wherein said coil has a density that is
higher in said subzone corresponding to lower back, or feet than in
said plurality of subzones corresponding to other parts of said
user's body.
10. The system of claim 5, further comprising a power supply,
wherein said power supply is configured to independently supply
power to each of said plurality of zones corresponding to said
plurality of users.
11. The system of claim 4, wherein said user sensor comprises at
least one of a piezo sensor or a temperature sensor.
12. The system of claim 4, wherein said sensor strip comprises a
body, wherein said body comprises a fabric layer, foam layer, a
piezo sensor, and temperature sensor.
13. The system of claim 4, wherein said sensor strip comprises a
tail region, wherein said tail region comprises a polycarbonate
stiffener layer, a stiffener foam layer, piezo sensor wire leads,
and temperature sensor wire leads.
14. The system of claim 4, wherein said biological signal
associated with said user corresponds to a presence associated with
said user, a motion associated with said user, a breathing rate
associated with said user, a temperature associated with said user,
or a heart rate associated with said user.
15. The system of claim 4, wherein said control signal comprises
one of: an instruction to heat said coil, or an instruction to cool
said coil.
16. The system of claim 4, wherein said time comprises average
bedtime associated with said user.
17. The system of claim 4, wherein said computer bus comprises
three straight strips, wherein said three straight strips include a
first strip that is coupled at a first right angle to a second
strip, and said second strip is coupled at a second right angle to
a third strip, and further wherein said first strip is configured
to bend backwards at specified locations, thereby extending a total
length of said sensor strip.
18. The system of claim 4, wherein said coil comprises a left coil
and a right coil, wherein said left coil and said right coil are
mirror images of each other, and further wherein said left coil
comprises a plurality of consecutive elongated rectangles, each
rectangle sharing and elongated edge with a neighboring rectangle,
and further wherein each said rectangle is missing a short edge,
wherein said short edge is different from a first short edge
missing in said neighboring rectangle.
19. A system comprising: a sensor strip, comprising: a user sensor
configured to measure a biological signal associated with a user,
said biological signal comprising a heart rate associated with said
user, a breathing rate associated with said user, a temperature
associated with said user, or a motion associated with said user; a
computer bus configured to bend at specified locations, thereby
changing a length of said sensor strip; and a computer processor
communicatively coupled to said sensor strip, said computer
processor configured to identify said user based on at least one
of: said heart rate associated with said user, said breathing rate
associated with said user, said temperature associated with said
user, or said motion associated with said user.
20. The system of claim 19, wherein said computer processor is
configured to display said biological signal over time, in a
graphical user interface.
21. The system of claim 19, wherein said computer processor is
configured to determine a sleep phase associated with said user,
based on said biological signal.
22. The system of claim 19, wherein said computer processor is
configured to calculate an average bedtime associated with said
user.
23. The system of claim 19, wherein said user sensor comprises at
least one of a piezo sensor or a temperature sensor.
24. The system of claim 19, wherein said sensor strip comprises a
body, wherein said body comprises a fabric layer, foam layer, a
piezo sensor, and temperature sensor.
25. The system of claim 19, wherein said sensor strip comprises a
tail region, wherein said tail region comprises a polycarbonate
stiffener layer, a stiffener foam layer, piezo sensor wire leads,
and temperature sensor wire leads.
26. The system of claim 19, wherein said computer bus comprises
three straight strips, wherein a first strip is coupled at a first
right angle to a second strip, and said second strip is coupled at
a second right angle to a third strip, and further where said first
strip is configured to bend backwards at predetermined locations,
thereby extending a total length of said sensor strip.
27. The system of claim 19, further comprising a material layer
coupled to said computer processor, said material configured to
receive a control signal from said computer processor, and to heat
or cool based on said control signal.
28. A system comprising: a sensor strip configured to obtain a
biological signal associated with a user from a sensor, wherein
said biological signal corresponds to a heart rate associated with
said user, a temperature associated with said user, a motion
associated with said user, and breathing rate associated with said
user; a processor configured to: identify said user based on at
least one of: said heart rate associated with said user, said
breathing rate associated with said user, said temperature
associated with said user, or said motion associated with said
user; determine a control signal, and a time to send said control
signal to a coil, using said processor, wherein said control signal
comprises one of an instruction to heat said coil to a high
temperature, or an instruction to cool said coil to a low
temperature, and further wherein said time comprises an average
bedtime associated with said user; and sending said control signal
at said average bedtime associated with said user to said coil,
such that said coil is heated or cooled according to said control
signal.
29. The system of claim 28, wherein said high temperature comprises
an average high temperature associated with said user.
30. The system of claim 28, wherein said low temperature comprises
an average low temperature associated with said user.
31. The system of claim 28, wherein said sensor strip comprises a
body, wherein said body comprises a fabric layer, foam layer, a
piezo sensor, and temperature sensor.
32. The system of claim 28, wherein said sensor strip comprises a
tail region, wherein said tail region comprises a polycarbonate
stiffener layer, a stiffener foam layer, piezo sensor wire leads,
and temperature sensor wire leads.
33. A method to manufacture a sensor strip, said method comprising:
placing a first fabric layer with a coated surface associated with
said first fabric layer facing up, wherein said first fabric layer
comprises a first and a second long edge, and a first and a second
short edge; placing a first foam layer on top of said first fabric
layer, wherein said first foam layer is centered between said first
and said second long edge, and wherein said first foam layer is
closer to said first short edge then to said second short edge, and
wherein a 1st region between said first foam layer and said second
short edge is a tail region; placing a temperature sensor on top of
said first foam layer; placing a piezo sensor on top of said first
foam layer; placing a second foam layer on top of said piezo
sensor, wherein said second foam layer is centered between said
first and said second long edge, and wherein said second foam layer
is closer to said first short edge then to said second short edge,
and wherein a region between said second foam layer and said second
short edge is said tail region; placing a second fabric layer on
top of said second foam layer; and laminating said first and said
second fabric layer, said first and said second foam layer, said
piezo sensor, and said temperature sensor.
34. The method of claim 33, said method further comprising: placing
a first polycarbonate stiffener layer on top of said tail region
associated with said first fabric layer; placing a first stiffener
foam layer on top of said first polycarbonate stiffener layer;
placing a plurality of wireless leads associated with said piezo
sensor and a plurality of wireless leads associated with said
temperature sensor on top of said first stiffener foam layer;
placing a second stiffener foam layer on top of said plurality of
wireless leads associated with said piezo sensor, and said
plurality of wireless leads associated with said temperature
sensor; placing a second polycarbonate stiffener layer on top of
said second stiffener foam layer; and laminating said first and
said second polycarbonate stiffener layer, said first and said
second stiffener foam layer in said plurality of wireless leads
associated with said piezo sensor, and said plurality of wireless
leads associated with said temperature sensor.
35. The method of claim 33, wherein said first foam layer and said
second foam layer have a same shape, said shape comprising a first
and a second long edge, and a first and a second short edge,
wherein said first long edge comprises a plurality of protrusions,
and a plurality of gaps.
36. The method of claim 35, wherein said placing said second foam
layer further comprises: orienting said second foam layer so that
said plurality of gaps associated with said second foam layer are
on top of said plurality of protrusions associated with said first
foam layer.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation in part of U.S. patent
application Ser. No. 14/732,646, filed Jun. 5, 2015, which claims
priority to the following U.S. provisional patent applications:
U.S. provisional patent application Ser. No. 62/008,480, filed Jun.
5, 2014; U.S. provisional patent application Ser. No. 62/024,945,
filed Jul. 15, 2014; U.S. provisional patent application Ser. No.
62/159,177, filed May 8, 2015; and U.S. provisional patent
application Ser. No. 62/161,142, filed May 13, 2015; which
applications are incorporated herein in their entirety and by this
reference thereto.
TECHNICAL FIELD
[0002] Various embodiments relate generally to home automation
devices, and human biological signal gathering and analysis.
BACKGROUND
[0003] According to current scientific research into sleep, there
are two major stages of sleep: rapid eye movement ("REM") sleep,
and non-REM sleep. First comes non-REM sleep, followed by a shorter
period of REM sleep, and then the cycle starts over again.
[0004] There are three stages of non-REM sleep. Each stage can last
from 5 to 15 minutes. A person goes through all three stages before
reaching REM sleep.
[0005] In stage one, a person's eyes are closed, but the person is
easily woken up. This stage may last for 5 to 10 minutes.
[0006] In stage two, a person is in light sleep. A person's heart
rate slows and the person's body temperature drops. The person's
body is getting ready for deep sleep.
[0007] Stage three is the deep sleep stage. A person is harder to
rouse during this stage, and if the person was woken up, the person
would feel disoriented for a few minutes. During the deep stages of
non-REM sleep, the body repairs and regrows tissues, builds bone
and muscle, and strengthens the immune system.
[0008] REM sleep happens 90 minutes after a person falls asleep.
Dreams typically happen during REM sleep. The first period of REM
typically lasts 10 minutes. Each of later REM stages gets longer,
and the final one may last up to an hour. A person's heart rate and
breathing quickens. A person can have intense dreams during REM
sleep, since the brain is more active. REM sleep affects learning
of certain mental skills.
[0009] Even in today's technological age, supporting healthy sleep
is relegated to the technology of the past such as an electric
blanket, a heated pad, or a bed warmer. The most advanced of these
technologies, an electric blanket, is a blanket with an integrated
electrical heating device which can be placed above the top bed
sheet or below the bottom bed sheet. The electric blanket may be
used to pre-heat the bed before use or to keep the occupant warm
while in bed. However, turning on the electric blanket requires the
user to remember to manually turn on the blanket, and then manually
turn it on. Further, the electric blanket provides no additional
functionality besides warming the bed.
SUMMARY
[0010] Introduced are methods and systems for an adjustable bed
device configured to: gather biological signals associated with
multiple users, such as heart rate, breathing rate, or temperature;
analyze the gathered human biological signals; and heat or cool a
bed based on the analysis.
[0011] In one embodiment, one or more user sensors, associated with
a piece of furniture, such as a bed, measure the bio signals
associated with a user, such as the heart rate associated with said
user or breathing rate associated with said user. One or more
environment sensors measure the environment property such as
temperature, humidity, light, or sound. Based on the bio signals
associated with said user and environment properties received, the
system determines the time at which to send an instruction to an
appliance to turn on or to turn off. In one embodiment, the
appliance is a bed device, capable of heating or cooling the user's
bed. In another embodiment, the appliance is a thermostat, a light,
a coffee machine, or a humidifier.
[0012] In another embodiment, based on the heart rate, temperature,
and breathing rate, associated with a user, the system determines
the sleep phase associated with said user. Based on the sleep phase
and the user-specified wake-up time, the system determines a time
to wake up the user, so that the user does not feel tired or
disoriented when woken up.
BRIEF DESCRIPTION OF THE DRAWINGS
[0013] These and other objects, features and characteristics of the
present embodiments will become more apparent to those skilled in
the art from a study of the following detailed description in
conjunction with the appended claims and drawings, all of which
form a part of this specification. While the accompanying drawings
include illustrations of various embodiments, the drawings are not
intended to limit the claimed subject matter.
[0014] FIG. 1 is a diagram of a bed device, according to one
embodiment.
[0015] FIG. 2 illustrates an example of a bed device, according to
one embodiment.
[0016] FIG. 3 illustrates an example of layers comprising a bed pad
device, according to one embodiment.
[0017] FIG. 4A illustrates a user sensor placed on a sensor strip,
according to one embodiment.
[0018] FIG. 4B is the sensor strip, according to one
embodiment.
[0019] FIG. 4C is a flowchart of a process to manufacture the body
of the sensor strip, according to one embodiment.
[0020] FIG. 4D is a flowchart of a process to manufacture the tail
part of the sensor strip, according to one embodiment.
[0021] FIGS. 5A, 5B, 5C, and 5D show different configurations of a
sensor strip, to fit different size mattresses, according to one
embodiment.
[0022] FIG. 6A illustrates the division of the heating coil into
zones and subzones, according to one embodiment.
[0023] FIGS. 6B and 6C illustrate the independent control of the
different subzones, according to one embodiment.
[0024] FIG. 7 is a flowchart of the process for deciding when to
heat or cool the bed device, according to one embodiment.
[0025] FIG. 8 is a flowchart of the process for recommending a bed
time to a user, according to one embodiment.
[0026] FIG. 9 is a flowchart of the process for activating the
user's alarm, according to one embodiment.
[0027] FIG. 10 is a flowchart of the process for turning off an
appliance, according to one embodiment.
[0028] FIG. 11 is a diagram of a system capable of automating the
control of the home appliances, according to one embodiment.
[0029] FIG. 12 is an illustration of the system capable of
controlling an appliance and a home, according to one
embodiment.
[0030] FIG. 13 is a flowchart of the process for controlling an
appliance, according to one embodiment.
[0031] FIG. 14 is a flowchart of the process for controlling an
appliance, according to another embodiment.
[0032] FIG. 15 is a diagram of a system for monitoring biological
signals associated with a user, and providing notifications or
alarms, according to one embodiment.
[0033] FIG. 16 is a flowchart of a process for generating a
notification based on a history of biological signals associated
with a user, according to one embodiment.
[0034] FIG. 17 is a flowchart of a process for generating a
comparison between a biological signal associated with a user and a
target biological signal, according to one embodiment.
[0035] FIG. 18 is a flowchart of a process for detecting the onset
of a disease, according to one embodiment.
[0036] FIG. 19 is a diagrammatic representation of a machine in the
example form of a computer system within which a set of
instructions, for causing the machine to perform any one or more of
the methodologies or modules discussed herein, may be executed.
DETAILED DESCRIPTION
[0037] Examples of a method, apparatus, and computer program for
automating the control of home appliances and improving the sleep
environment are disclosed below. In the following description, for
the purposes of explanation, numerous specific details are set
forth in order to provide a thorough understanding of the
embodiments of the invention. One skilled in the art will recognize
that the embodiments of the invention may be practiced without
these specific details or with an equivalent arrangement. In other
instances, well-known structures and devices are shown in block
diagram form in order to avoid unnecessarily obscuring the
embodiments of the invention.
TERMINOLOGY
[0038] Brief definitions of terms, abbreviations, and phrases used
throughout this application are given below.
[0039] In this specification, the term "biological signal" and "bio
signal" are synonyms, and are used interchangeably.
[0040] Reference in this specification to "sleep phase" means light
sleep, deep sleep, or REM sleep. Light sleep comprises stage one
and stage two, non-REM sleep.
[0041] Reference in this specification to "one embodiment" or "an
embodiment" means that a particular feature, structure, or
characteristic described in connection with the embodiment is
included in at least one embodiment of the disclosure. The
appearances of the phrase "in one embodiment" in various places in
the specification are not necessarily all referring to the same
embodiment, nor are separate or alternative embodiments mutually
exclusive of other embodiments. Moreover, various features are
described that may be exhibited by some embodiments and not by
others. Similarly, various requirements are described that may be
requirements for some embodiments but not others.
[0042] Unless the context clearly requires otherwise, throughout
the description and the claims, the words "comprise," "comprising,"
and the like are to be construed in an inclusive sense, as opposed
to an exclusive or exhaustive sense; that is to say, in the sense
of "including, but not limited to." As used herein, the terms
"connected," "coupled," or any variant thereof, means any
connection or coupling, either direct or indirect, between two or
more elements. The coupling or connection between the elements can
be physical, logical, or a combination thereof. For example, two
devices may be coupled directly, or via one or more intermediary
channels or devices. As another example, devices may be coupled in
such a way that information can be passed there between, while not
sharing any physical connection with one another. Additionally, the
words "herein," "above," "below," and words of similar import, when
used in this application, shall refer to this application as a
whole and not to any particular portions of this application. Where
the context permits, words in the Detailed Description using the
singular or plural number may also include the plural or singular
number respectively. The word "or," in reference to a list of two
or more items, covers all of the following interpretations of the
word: any of the items in the list, all of the items in the list,
and any combination of the items in the list.
[0043] If the specification states a component or feature "may,"
"can," "could," or "might" be included or have a characteristic,
that particular component or feature is not required to be included
or have the characteristic.
[0044] The term "module" refers broadly to software, hardware, or
firmware components (or any combination thereof). Modules are
typically functional components that can generate useful data or
another output using specified input(s). A module may or may not be
self-contained. An application program (also called an
"application") may include one or more modules, or a module may
include one or more application programs.
[0045] The term "on top of" means that the two objects, where the
first object is "on top of" the second object, can be rotated so
that the first object is above the second object relative to the
ground. The 2 objects can be in direct or indirect contact, or may
not be in contact at all.
[0046] The terminology used in the Detailed Description is intended
to be interpreted in its broadest reasonable manner, even though it
is being used in conjunction with certain examples. The terms used
in this specification generally have their ordinary meanings in the
art, within the context of the disclosure, and in the specific
context where each term is used. For convenience, certain terms may
be highlighted, for example using capitalization, italics, and/or
quotation marks. The use of highlighting has no influence on the
scope and meaning of a term; the scope and meaning of a term is the
same, in the same context, whether or not it is highlighted. It
will be appreciated that the same element can be described in more
than one way.
[0047] Consequently, alternative language and synonyms may be used
for any one or more of the terms discussed herein, but special
significance is not to be placed upon whether or not a term is
elaborated or discussed herein. A recital of one or more synonyms
does not exclude the use of other synonyms. The use of examples
anywhere in this specification, including examples of any terms
discussed herein, is illustrative only and is not intended to
further limit the scope and meaning of the disclosure or of any
exemplified term. Likewise, the disclosure is not limited to
various embodiments given in this specification.
Bed Device
[0048] FIG. 1 is a diagram of a bed device, according to one
embodiment. Any number of user sensors 140, 150 monitor the bio
signals associated with a user, such as the heart rate, the
breathing rate, the temperature, motion, or presence, associated
with said user. Any number of environment sensors 160, 170 monitor
environment properties, such as temperature, sound, light, or
humidity. The user sensors 140, 150 and the environment sensors
160, 170 communicate their measurements to the processor 100. The
environment sensors 160, 170, measure the properties of the
environment that the environment sensors 160, 170 are associated
with. In one embodiment, the environment sensors 160, 170 are
placed next to the bed. The processor 100 determines, based on the
bio signals associated with said user, historical bio signals
associated with said user, user-specified preferences, exercise
data associated with said user, or the environment properties
received, a control signal, and a time to send said control signal
to a bed device 120.
[0049] According to one embodiment, the processor 100 is connected
to a database 180, which stores the biological signals associated
with a user. Additionally, the database 180 can store average
biological signals associated with the user, history of biological
signals associated with a user, etc. The database 180 can be
associated with a user, or the database 180 can be associated with
the bed device.
[0050] FIG. 2 illustrates an example of the bed device of FIG. 1,
according to one embodiment. A sensor strip 210, associated with a
mattress 200 of the bed device 120, monitors bio signals associated
with a user sleeping on the mattress 200. The sensor strip 210 can
be built into the mattress 200, or can be part of a bed pad device.
Alternatively, the sensor strip 210 can be a part of any other
piece of furniture, such as a rocking chair, a couch, an armchair
etc. The sensor strip 210 comprises a temperature sensor, or a
piezo sensor. The environment sensor 220 measures environment
properties such as temperature, sound, light or humidity. According
to one embodiment, the environment sensor 220 is associated with
the environment surrounding the mattress 200. The sensor strip 210
and the environment sensor 220 communicate the measured environment
properties to the processor 230. In some embodiments, the processor
230 can be similar to the processor 100 of FIG. 1 A processor 230
can be connected to the sensor strip 210, or the environment sensor
220 by a computer bus, such as an I2C bus. Also, the processor 230
can be connected to the sensor strip 210, or the environment sensor
220 by a communication network. By way of example, the
communication network connecting the processor 230 to the sensor
strip 210, or the environment sensor 220 includes one or more
networks such as a data network, a wireless network, a telephony
network, or any combination thereof. The data network may be any
local area network (LAN), metropolitan area network (MAN), wide
area network (WAN), a public data network (e.g., the Internet),
short range wireless network, or any other suitable packet-switched
network, such as a commercially owned, proprietary packet-switched
network, e.g., a proprietary cable or fiber-optic network, and the
like, or any combination thereof. In addition, the wireless network
may be, for example, a cellular network and may employ various
technologies including enhanced data rates for global evolution
(EDGE), general packet radio service (GPRS), global system for
mobile communications (GSM), Internet protocol multimedia subsystem
(IMS), universal mobile telecommunications system (UMTS), etc., as
well as any other suitable wireless medium, e.g., worldwide
interoperability for microwave access (WiMAX), Long Term Evolution
(LTE) networks, code division multiple access (CDMA), wideband code
division multiple access (WCDMA), wireless fidelity (WiFi),
wireless LAN (WLAN), Bluetooth.RTM., Internet Protocol (IP) data
casting, satellite, mobile ad-hoc network (MANET), and the like, or
any combination thereof.
[0051] The processor 230 is any type of microcontroller, or any
processor in a mobile terminal, fixed terminal, or portable
terminal including a mobile handset, station, unit, device,
multimedia computer, multimedia tablet, Internet node, cloud
computer, communicator, desktop computer, laptop computer, notebook
computer, netbook computer, tablet computer, personal communication
system (PCS) device, personal navigation device, personal digital
assistants (PDAs), audio/video player, digital camera/camcorder,
positioning device, television receiver, radio broadcast receiver,
electronic book device, game device, the accessories and
peripherals of these devices, or any combination thereof.
[0052] FIG. 3 illustrates an example of layers comprising the bed
pad device of FIG. 1, according to one embodiment. In some
embodiments, the bed pad device 120 is a pad that can be placed on
top of the mattress. Bed pad device 120 comprises a number of
layers. A top layer 350 comprises fabric. A layer 340 comprises
batting, and a sensor strip 330. A layer 320 comprises coils for
cooling or heating the bed device. A layer 310 comprises waterproof
material.
[0053] According to another embodiment, the layer 320 comprises a
material that can be heated or cooled in the 10.degree. C. to
50.degree. C. range without changing the materials properties such
as the state of matter. An example of such materials can be air,
water, argon, a synthetic material such as carbon nanotubes, etc.
According to one embodiment, the layer 320 is connected to an
external thermal regulator which heats or cools the material, based
on the signal received from the processor 230.
[0054] According to another embodiment, the layer 320 comprising
the material is integrated into the mattress, the bed sheets, the
bed cover, the bed frame, etc. The layer 320 comprising the
material can also be integrated with any piece of furniture.
[0055] FIG. 4A illustrates a user sensor 420, 440, 450, 470 placed
on a sensor strip 400, according to one embodiment. In some
embodiments, the user sensors 420, 440, 450, 470 can be similar to
or part of the sensor strip 210 of FIG. 2. Sensors 470 and 440
comprise a piezo sensor, which can measure a bio signal associated
with a user, such as the heart rate and the breathing rate. Sensors
450 and 420 comprise a temperature sensor. According to one
embodiment, sensors 450, and 470 measure the bio signals associated
with one user, while sensors 420, 440 measure the bio signals
associated with another user. Analog-to-digital converter 410
converts the analog sensor signals into digital signals to be
communicated to a processor. Computer bus 430 and 460, such as the
I2C bus, communicates the digitized bio signals to a processor.
[0056] FIG. 4B is the sensor strip 400, according to one
embodiment. The sensor strip 400 comprises several layers, such as
a fabric layer 471, a foam layer 473, 475, a piezo sensor 470, 440,
a polycarbonate stiffener 485, a stiffener foam 487, and a
temperature sensor 450, 420. Region 477 of the fabric layer 471 is
the tail region of the sensor strip 400. Wire leads 489 associated
with piezo sensor 470, 440, and temperature sensor 450, 420 are
placed on top of the tail region 477. The fabric layer 471 includes
two short edges and two long edges. The length of the short edge
varies from 40-70 mm. The fabric layer 471 has at least one coated
surface. The foam layer 473, 475 also has two short edges and two
long edges. One of the long edges includes multiple protrusions
491, and multiple gaps 493, between the multiple protrusions
491.
[0057] FIG. 4C is a flowchart of a process to manufacture the body
of the sensor strip 400, according to one embodiment. In step 472,
the fabric layer 471 is laid out with the coated surface pointing
up. In step 474, a first foam layer is applied to the fabric layer
471. In one embodiment, the first foam layer 473 is centered on the
fabric layer 471, with a margin of 10 mm from the first short edge
and a margin of 5 mm from the long edges. The margin to the second
short edge of the fabric layer 471 is greater than the margin to
the first short edge. In one embodiment, the margin to the second
short edge is at least twice as big than the margin to the first
short edge. The margin to the second short edge of the fabric layer
471 is considered a tail part of the sensor strip 400, comprising
the tail region 477 of the fabric layer 471. In step 476, two
temperature sensors 450, 420 are placed on the first foam layer
473. In one embodiment, the temperature sensors are placed 17 mm
from a long edge of the fabric layer 471. In step 478, two piezo
sensors 470, 440 are placed on the first foam layer 473. In one
embodiment, the piezo sensors are centered on the fabric layer 471.
In step 480, a second foam layer 475 is applied on top of the piezo
sensors. In one embodiment, the second foam layer 475 is centered
on the fabric layer 471, with a margin of 10 mm from the short
edges, and 5 mm from the long edges. Further, the second foam layer
475 is placed as a mirror image of the first foam layer 473, and is
interlaced with the first foam layer 473. In step 482, a second
fabric layer is applied on top of the second foam layer 475. In
step 484, the whole assembly, comprising all the layers, is
laminated.
[0058] FIG. 4D is a flowchart of a process to manufacture the tail
part of the sensor strip 400, according to one embodiment. In step
486, first polycarbonate stiffener layer 485 is placed on top of
the tail region 477 of the fabric layer 471. In one embodiment, the
dimensions of the polycarbonate stiffener layer 485 are 40-70 mm by
5-25 mm. The 40-70 mm edge matches the length of the 40-70 mm edge
of the sensor strip 400. In step 488, the first stiffener foam
layer 487 is applied on top of the polycarbonate stiffener layer
485. In step 490, the wire leads 489 of the piezo sensors 470, 440,
and the wire leads 489 of the temperature sensors 450, 420 are
placed on top of the first stiffener foam layer 487, and past the
tail region 477 of the fabric layer 471. In step 492, the second
stiffener foam layer is applied on top of the wire leads 489. The
dimensions of the second stiffener foam layer are identical to the
first stiffener foam layer 487. In step 494, the second
polycarbonate stiffener layer is applied on top of the second
stiffener foam layer. The dimensions of the second polycarbonate
stiffener layer are identical to the dimensions of the first
polycarbonate stiffener layer 485. In step 496, the whole tail part
assembly is laminated.
[0059] FIGS. 5A and 5B show different configurations of the sensor
strip, to fit different size mattresses, according to one
embodiment. FIGS. 5C and 5D show how such different configurations
of the sensor strip can be achieved. Specifically, sensor strip 400
comprises a computer bus 510, 530, and a sensor striplet 505. The
computer bus 510, 530 can be bent at predetermined locations 540,
550, 560, 570. Bending the computer bus 515 at location 540
produces the maximum total length of the computer bus 530. Computer
bus 530 combined with a sensor striplet 505, fits a king size
mattress 520. Bending the computer bus 515 at location 570 produces
the smallest total length of the computer bus, 510. Computer bus
510 combined with a sensor striplet 505, fits a twin size mattress
500. Bending the computer bus 515 at location 560, enables the
sensor strip 400 to fit a full-size bed. Bending the computer bus
515 at location 550 enables the sensor strip 400 to fit a
queen-size bed. In some embodiments, twin mattress 500, or king
mattress 520 can be similar to the mattress 200 of FIG. 2.
[0060] FIG. 6A illustrates the division of the heating coil 600
into zones and subzones, according to one embodiment. Specifically,
the heating coil 600 is divided into two zones 660 and 610, each
corresponding to one user of the bed. Each zone 660 and 610 can be
heated or cooled independently of the other zone in response to the
user's needs. To achieve independent heating of the two zones 660
and 610, the power supply associated with the heating coil 600 is
divided into two zones, each power supply zone corresponding to a
single user zone 660, 610. Further, each zone 660 and 610 is
further subdivided into subzones. Zone 660 is divided into subzones
670, 680, 690, and 695. Zone 610 is divided into subzones 620, 630,
640, and 650. The distribution of coils in each subzone is
configured so that the subzone is uniformly heated. However, the
subzones may differ among themselves in the density of coils. For
example, the data associated with said user subzone 670 has lower
density of coils than subzone 680. This will result in subzone 670
having lower temperature than subzone 680, when the coils are
heated. Similarly, when the coils are used for cooling, subzones
670 will have higher temperature than subzone 680. According to one
embodiment, subzones 680 and 630 with highest coil density
correspond to the user's lower back; and subzones 695 and 650 with
highest coil density correspond to user's feet. According to one
embodiment, even if the users switch sides of the bed, the system
will correctly identify which user is sleeping in which zone by
identifying the user based on any of the following signals alone,
or in combination: heart rate, breathing rate, body motion, or body
temperature associated with said user.
[0061] In another embodiment, the power supply associated with the
heating coil 600 is divided into a plurality of zones, each power
supply zone corresponding to a subzone 620, 630, 640, 650, 670,
680, 690, 695. The user can control the temperature of each subzone
620, 630, 640, 650, 670, 680, 690, 695 independently. Further, each
user can independently specify the temperature preferences for each
of the subzones. Even if the users switch sides of the bed, the
system will correctly identify the user, and the preferences
associated with the user by identifying the user based on any of
the following signals alone, or in combination: heart rate,
breathing rate, body motion, or body temperature associated with
said user.
[0062] FIGS. 6B and 6C illustrate the independent control of the
different subzones in each zone 610, 660, according to one
embodiment. Set of uniform coils 611, connected to power management
box 601, uniformly heats or cools the bed. Another set of coils,
targeting specific areas of the body such as the neck, the back,
the legs, or the feet, is layered on top of the uniform coils 611.
Subzone 615 heats or cools the neck. Subzone 625 heats or cools the
back. Subzone 635 heats or cools the legs, and subzone 645 heats or
cools the feet. Power is distributed to the coils via duty cycling
of the power supply 605. Contiguous sets of coils can be heated or
cooled at different levels by assigning the power supply duty cycle
to each set of coils. The user can control the temperature of each
subzone independently.
[0063] FIG. 7 is a flowchart of the process for deciding when to
heat or cool the bed device, according to one embodiment. At block
700, the process obtains a biological signal associated with a
user, such as presence in bed, motion, breathing rate, heart rate,
or a temperature. The process obtains said biological signal from a
sensor associated with a user. Further, at block 710, the process
obtains environment property, such as the amount of ambient light
and the bed temperature. The process obtains environment property
from and environment sensor associated with the bed device. If the
user is in bed, the bed temperature is low, and the ambient light
is low, the process sends a control signal to the bed device. The
control signal comprises an instruction to heat the bed device to
the average nightly temperature associated with said user.
According to another embodiment, the control signal comprises an
instruction to heat the bed device to a user-specified temperature.
Similarly, if the user is in bed, the bed temperature is high, and
the ambient light is low, the process sends a control signal to the
bed device to cool the bed device to the average nightly
temperature associated with said user. According to another
embodiment, the control signal comprises an instruction to cool the
bed device to a user-specified temperature.
[0064] In another embodiment, in addition to obtaining the
biological signal associated with said user, and the environment
property, the process obtains a history of biological signals
associated with said user. The history of biological signals can be
stored in a database associated with the bed device, or in a
database associated with a user. The history of biological signals
comprises the average bedtime the user went to sleep for each day
of the week; that is, the history of biological signals comprises
the average bedtime associated with said user on Monday, the
average bedtime associated with said user on Tuesday, etc. For a
given day of the week, the process determines the average bedtime
associated with said user for that day of the week, and sends the
control signal to the bed device, allowing enough time for the bed
to reach the desired temperature, before the average bedtime
associated with said user. The control signal comprises an
instruction to heat, or cool the bed to a desired temperature. The
desired temperature may be automatically determined, such as by
averaging the historical nightly temperature associated with a
user, or the desired temperature may be specified by the user.
Bio Signal Processing
[0065] The technology disclosed here categorizes the sleep phase
associated with a user as light sleep, deep sleep, or REM sleep.
Light sleep comprises stage one and stage two sleep. The technology
performs the categorization based on the breathing rate associated
with said user, heart rate associated with said user, motion
associated with said user, and body temperature associated with
said user. Generally, when said user is awake the breathing is
erratic. When the user is sleeping, the breathing becomes regular.
The transition between being awake and sleeping is quick, and lasts
less than 1 minute.
[0066] FIG. 8 is a flowchart of the process for recommending a bed
time to the user, according to one embodiment. At block 800, the
process obtains a history of sleep phase information associated
with said user. The history of sleep phase information comprises an
amount of time the user spent in each of the sleep phases, light
sleep, deep sleep, or REM sleep. The history of sleep phase
information can be stored in a database associated with the user.
Based on this information, the process determines how much light
sleep, deep sleep, and REM sleep, the user needs on average every
day. In another embodiment, the history of sleep phase information
comprises the average bedtime associated with said user for each
day of the week (e.g. the average bedtime associated with said user
on Monday, the average bedtime associated with said user on
Tuesday, etc.). At block 810, the process obtains user-specified
wake-up time, such as the alarm setting associated with said user.
At block 820, the process obtains exercise information associated
with said user, such as the distance the user ran that day, the
amount of time the user exercised in the gym, or the amount of
calories the user burned that day. According to one embodiment, the
process obtains said exercise information from a user phone, a
wearable device, a fitbit bracelet, or a database storing said
exercise information. Based on all this information, at block 830,
the process recommends a bedtime to the user. For example, if the
user has not been getting enough deep and REM sleep in the last few
days, the process recommends an earlier bedtime to the user. Also,
if the user has exercised more than the average daily exercise, the
process recommends an earlier bedtime to the user.
[0067] FIG. 9 is a flowchart of the process for activating a user's
alarm, according to one embodiment. At block 900, the process
obtains the compound bio signal associated with said user. The
compound bio signal associated with said user comprises the heart
rate associated with said user, and the breathing rate associated
with said user. According to one embodiment, the process obtains
the compound bio signal from a sensor associated with said user. At
block 910, the process extracts the heart rate signal from the
compound bio signal. For example, the process extracts the heart
rate signal associated with said user by performing low-pass
filtering on the compound bio signal. Also, at block 920, the
process extracts the breathing rate signal from the compound bio
signal. For example, the process extracts the breathing rate by
performing bandpass filtering on the compound bio signal. The
breathing rate signal includes breath duration, pauses between
breaths, as well as breaths per minute. At block 930, the process
obtains user's wake-up time, such as the alarm setting associated
with said user. Based on the heart rate signal and the breathing
rate signal, the process determines the sleep phase associated with
said user, and if the user is in light sleep, and current time is
at most one hour before the alarm time, at block 940, the process
activates an alarm. Waking up the user during the deep sleep or REM
sleep is detrimental to the user's health because the user will
feel disoriented, groggy, and will suffer from impaired memory.
Consequently, at block 950, the process activates an alarm, when
the user is in light sleep and when the current time is at most one
hour before the user specified wake-up time.
[0068] FIG. 10 is a flowchart of the process for turning off an
appliance, according to one embodiment. At block 1000, the process
obtains the compound bio signal associated with said user. The
compound bio signal comprises the heart rate associated with said
user, and the breathing rate associated with said user. According
to one embodiment, the process obtains the compound bio signal from
a sensor associated with said user. At block 1010, the process
extracts the heart rate signal from the compound bio signal by, for
example, performing low-pass filtering on the compound bio signal.
Also, at block 1020, the process extracts the breathing rate signal
from the compound bio signal by, for example, performing bandpass
filtering on the compound bio signal. At block 1030, the process
obtains an environment property, comprising temperature, humidity,
light, sound from an environment sensor associated with said sensor
strip. Based on the environment property and the sleep state
associated with said user, at block 1040, the process determines
whether the user is sleeping. If the user is sleeping, the process,
at block 1050, turns an appliance off. For example, if the user is
asleep and the environment temperature is above the average nightly
temperature, the process turns off the thermostat. Further, if the
user is asleep and the lights are on, the process turns off the
lights. Similarly, if the user is asleep and the TV is on, the
process turns off the TV.
Smart Home
[0069] FIG. 11 is a diagram of a system capable of automating the
control of the home appliances, according to one embodiment. Any
number of user sensors 1140, 1150 monitor biological signals
associated with said user, such as temperature, motion, presence,
heart rate, or breathing rate. Any number of environment sensors
1160, 1170 monitor environment properties, such as temperature,
sound, light, or humidity. According to one embodiment, the
environment sensors 1160, 1170 are placed next to a bed. The user
sensors 1140, 1150 and the environment sensors 1160, 1170
communicate their measurements to the processor 1100. The processor
1100 determines, based on the current biological signals associated
with said user, historical biological signals associated with said
user, user-specified preferences, exercise data associated with
said user, and the environment properties received, a control
signal, and a time to send said control signal to an appliance
1120, 1130.
[0070] The processor 1100 is any type of microcontroller, or any
processor in a mobile terminal, fixed terminal, or portable
terminal including a mobile handset, station, unit, device,
multimedia computer, multimedia tablet, Internet node, cloud
computer, communicator, desktop computer, laptop computer, notebook
computer, netbook computer, tablet computer, personal communication
system (PCS) device, personal navigation device, personal digital
assistants (PDAs), audio/video player, digital camera/camcorder,
positioning device, television receiver, radio broadcast receiver,
electronic book device, game device, the accessories and
peripherals of these devices, or any combination thereof.
[0071] The processor 1100 can be connected to the user sensor 1140,
1150, or the environment sensor 1160, 1170 by a computer bus, such
as an I2C bus. Also, the processor 1100 can be connected to the
user sensor 1140, 1150, or environment sensor 1160, 1170 by a
communication network 1110. By way of example, the communication
network 1110 connecting the processor 1100 to the user sensor 1140,
1150, or the environment sensor 1160, 1170 includes one or more
networks such as a data network, a wireless network, a telephony
network, or any combination thereof. The data network may be any
local area network (LAN), metropolitan area network (MAN), wide
area network (WAN), a public data network (e.g., the Internet),
short range wireless network, or any other suitable packet-switched
network, such as a commercially owned, proprietary packet-switched
network, e.g., a proprietary cable or fiber-optic network, and the
like, or any combination thereof. In addition, the wireless network
may be, for example, a cellular network and may employ various
technologies including enhanced data rates for global evolution
(EDGE), general packet radio service (GPRS), global system for
mobile communications (GSM), Internet protocol multimedia subsystem
(IMS), universal mobile telecommunications system (UMTS), etc., as
well as any other suitable wireless medium, e.g., worldwide
interoperability for microwave access (WiMAX), Long Term Evolution
(LTE) networks, code division multiple access (CDMA), wideband code
division multiple access (WCDMA), wireless fidelity (WiFi),
wireless LAN (WLAN), Bluetooth.RTM., Internet Protocol (IP) data
casting, satellite, mobile ad-hoc network (MANET), and the like, or
any combination thereof.
[0072] FIG. 12 is an illustration of the system capable of
controlling an appliance and a home, according to one embodiment.
The appliances, that the system disclosed here can control,
comprise an alarm, a coffee machine, a lock, a thermostat, a bed
device, a humidifier, or a light. For example, the system detects
that the user has fallen asleep, the system sends a control signal
to the lights to turn off, to the locks to engage, and to the
thermostat to lower the temperature. According to another example,
if the system detects that the user has woken up and it is morning,
the system sends a control signal to the coffee machine to start
making coffee.
[0073] FIG. 13 is a flowchart of the process for controlling an
appliance, according to one embodiment. In one embodiment, at block
1300, the process obtains history of biological signals, such as at
what time does the user go to bed on a particular day of the week
(e.g. the average bedtime associated with said user on Monday, the
average bedtime associated with said user on Tuesday etc.). The
history of biological signals can be stored in a database
associated with the user, or in a database associated with the bed
device. In another embodiment, at block 1300, the process also
obtains user specified preferences, such as the preferred bed
temperature associated with said user. Based on the history of
biological signals and user-specified preferences, the process, at
block 1320, determines a control signal, and a time to send said
control signal to an appliance. It block 1330, the process
determines whether to send a control signal to an appliance. For
example, if the current time is within half an hour of average
bedtime associated with said user on that particular day of the
week, the process, at block 1340, sends a control signal to an
appliance. For example, the control signal comprises an instruction
to turn on the bed device, and the user specified bed temperature.
Alternatively, the bed temperature is determined automatically,
such as by calculating the average nightly bed temperature
associated with a user.
[0074] According to another embodiment, at block 1300, the process
obtains a current biological signal associated with a user from a
sensor associated with said user. At block 1310, the process also
obtains environment data, such as the ambient light, from an
environment sensor associated with a bed device. Based on the
current biological signal, the process identifies whether the user
is asleep. If the user is asleep and the lights are on, the process
sends an instruction to turn off the lights. In another embodiment,
if the user is asleep, the lights are off, and the ambient light is
high, the process sends an instruction to the blinds to shut. In
another embodiment, if the user is asleep, the process sends an
instruction to the locks to engage.
[0075] In another embodiment, the process, at block 1300, obtains
history of biological signals, such as at what time the user goes
to bed on a particular day of the week (e.g. the average bedtime
associated with said user on Monday, the average bedtime associated
with said user on Tuesday etc.). The history of biological signals
can be stored in a database associated with the bed device, or in a
database associated with a user. Alternatively, the user may
specify a bedtime for the user for each day of the week. Further,
the process obtains the exercise data associated with said user,
such as the number of hours the user spent exercising, or the heart
rate associated with said user during exercising. According to one
embodiment, the process obtains the exercise data from a user
phone, a wearable device, fitbit bracelet, or a database associated
with said user. Based on the average bedtime for that day of the
week, and the exercise data during the day, the process, at block
1320, determines the expected bedtime associated with said user
that night. The process then sends an instruction to the bed device
to heat to a desired temperature, before the expected bedtime. The
desired temperature can be specified by the user, or can be
determined automatically, based on the average nightly temperature
associated with said user.
[0076] FIG. 14 is a flowchart of the process for controlling an
appliance, according to another embodiment. The process, at block
1400, receives current biological signal associated with said user,
such as the heart rate, breathing rate, presence, motion, or
temperature, associated with said user. Based on the current
biological signal, the process, at block 1410, identifies current
sleep phase, such as light sleep, deep sleep, or REM sleep. The
process, at block 1420 also receives a current environment property
value, such as the temperature, the humidity, the light, or the
sound. The process, at block 1430, accesses a database, which
stores historical values associated with the environment property
and the current sleep phase. That is, the database associates each
sleep phase with an average historical value of the different
environment properties. The database maybe associated with the bed
device, maybe associated with the user, or maybe associated with a
remote server. The process, at block 1440, then calculates a new
average of the environment property based on the current value of
the environment property and the historical value of the
environment property, and assigns the new average to the current
sleep phase in the database. If there is a mismatch between the
current value of the environment property, and the historical
average, the process, at block 1450, regulates the current value to
match the historical average. For example, the environment property
can be the temperature associated with the bed device. The database
stores the average bed temperature corresponding to each of the
sleep phase, light sleep, deep sleep, REM sleep. If the current bed
temperature is below the historical average, the process sends a
control signal to increase the temperature of the bed to match the
historical average.
Monitoring of Biological Signals
[0077] Biological signals associated with a person, such as a heart
rate or a breathing rate, indicate said person's state of health.
Changes in the biological signals can indicate an immediate onset
of a disease, or a long-term trend that increases the risk of a
disease associated with said person. Monitoring the biological
signals for such changes can predict the onset of a disease, can
enable calling for help when the onset of the disease is immediate,
or can provide advice to the person if the person is exposed to a
higher risk of the disease in the long-term.
[0078] FIG. 15 is a diagram of a system for monitoring biological
signals associated with a user, and providing notifications or
alarms, according to one embodiment. Any number of user sensors
1530, 1540 monitor bio signals associated with said user, such as
temperature, motion, presence, heart rate, or breathing rate. The
user sensors 1530, 1540 communicate their measurements to the
processor 1500. The processor 1500 determines, based on the bio
signals associated with said user, historical biological signals
associated with said user, or user-specified preferences whether to
send a notification or an alarm to a user device 1520. In some
embodiments, the user device 1520 and the processor 1500 can be the
same device.
[0079] The user device 1520 is any type of a mobile terminal, fixed
terminal, or portable terminal including a mobile handset, station,
unit, device, multimedia computer, multimedia tablet, Internet
node, communicator, desktop computer, laptop computer, notebook
computer, netbook computer, tablet computer, personal communication
system (PCS) device, personal navigation device, personal digital
assistants (PDAs), audio/video player, digital camera/camcorder,
positioning device, television receiver, radio broadcast receiver,
electronic book device, game device, the accessories and
peripherals of these devices, or any combination thereof.
[0080] The processor 1500 is any type of microcontroller, or any
processor in a mobile terminal, fixed terminal, or portable
terminal including a mobile handset, station, unit, device,
multimedia computer, multimedia tablet, Internet node, cloud
computer, communicator, desktop computer, laptop computer, notebook
computer, netbook computer, tablet computer, personal communication
system (PCS) device, personal navigation device, personal digital
assistants (PDAs), audio/video player, digital camera/camcorder,
positioning device, television receiver, radio broadcast receiver,
electronic book device, game device, the accessories and
peripherals of these devices, or any combination thereof.
[0081] The processor 1500 can be connected to the user sensor 1530,
1540 by a computer bus, such as an I2C bus. Also, the processor
1500 can be connected to the user sensor 1530, 1540 by a
communication network 1510. By way of example, the communication
network 1510 connecting the processor 1500 to the user sensor 1530,
1540 includes one or more networks such as a data network, a
wireless network, a telephony network, or any combination thereof.
The data network may be any local area network (LAN), metropolitan
area network (MAN), wide area network (WAN), a public data network
(e.g., the Internet), short range wireless network, or any other
suitable packet-switched network, such as a commercially owned,
proprietary packet-switched network, e.g., a proprietary cable or
fiber-optic network, and the like, or any combination thereof. In
addition, the wireless network may be, for example, a cellular
network and may employ various technologies including enhanced data
rates for global evolution (EDGE), general packet radio service
(GPRS), global system for mobile communications (GSM), Internet
protocol multimedia subsystem (IMS), universal mobile
telecommunications system (UMTS), etc., as well as any other
suitable wireless medium, e.g., worldwide interoperability for
microwave access (WiMAX), Long Term Evolution (LTE) networks, code
division multiple access (CDMA), wideband code division multiple
access (WCDMA), wireless fidelity (WiFi), wireless LAN (WLAN),
Bluetooth.RTM., Internet Protocol (IP) data casting, satellite,
mobile ad-hoc network (MANET), and the like, or any combination
thereof.
[0082] FIG. 16 is a flowchart of a process for generating a
notification based on a history of biological signals associated
with a user, according to one embodiment. The process, at block
1600, obtains a history of biological signals, such as the presence
history, motion history, breathing rate history, or heart rate
history, associated with said user. The history of biological
signals can be stored in a database associated with a user. At
block 1610, the process determines if there is an irregularity in
the history of biological signals within a timeframe. If there is
an irregularity, at block 1620, the process generates a
notification to the user. The timeframe can be specified by the
user, or can be automatically determined based on the type of
irregularity. For example, the heart rate associated with said user
goes up within a one day timeframe when the user is sick. According
to one embodiment, the process detects an irregularity,
specifically, that a daily heart rate associated with said user is
higher than normal. Consequently, the process warns the user that
the user may be getting sick. According to another embodiment, the
process detects an irregularity, such as that an elderly user is
spending at least 10% more time in bed per day over the last
several days, than the historical average. The process generates a
notification to the elderly user, or to the elderly user's
caretaker, such as how much more time the elderly user is spending
in bed. In another embodiment, the process detects an irregularity
such as an increase in resting heart rate, by more than 15 beats
per minute, over a ten-year period. Such an increase in the resting
heart rate doubles the likelihood that the user will die from a
heart disease, compared to those people whose heart rates remained
stable. Consequently, the process warns the user that the user is
at risk of a heart disease.
[0083] FIG. 17 is a flowchart of a process for generating a
comparison between a biological signal associated with a user and a
target biological signal, according to one embodiment. The process,
at block 1700, obtains a current biological signal associated with
a user, such as presence, motion, breathing rate, temperature, or
heart rate, associated with said user. The process obtains said
current biological signal from a sensor associated with said user.
The process, at block 1710, then obtains a target biological
signal, such as a user-specified biological signal, a biological
signal associated with a healthy user, or a biological signal
associated with an athlete. According to one embodiment, the
process obtains said target biological signal from a user, or a
database storing biological signals. The process, at block 1720,
compares current bio signal associated with said user and target
bio signal, and generates a notification based on the comparison
1730. The comparison of the current bio signal associated with said
user and target bio signal comprises detecting a higher frequency
in the current biological signal then in the target biological
signal, detecting a lower frequency in the current biological
signal than in the target biological signal, detecting higher
amplitude in the current biological signal than in the target
biological signal, or detecting lower amplitude in the current
biological signal than in the target biological signal.
[0084] According to one embodiment, the process of FIG. 17 can be
used to detect if an infant has a higher risk of sudden infant
death syndrome ("SIDS"). In SIDS victims less than one month of
age, heart rate is higher than in healthy infants of same age,
during all sleep phases. SIDS victims greater than one month of age
show higher heart rates during REM sleep phase. In case of
monitoring an infant for a risk of SIDS, the process obtains the
current bio signal associated with the sleeping infant, and a
target biological signal associated with the heart rate of a
healthy infant, where the heart rate is at the high end of a
healthy heart rate spectrum. The process obtains the current bio
signal from a sensor strip associated with the sleeping infant. The
process obtains said target biological signal from a database of
biological signals. If the frequency of the biological signal of
the infant exceeds the target biological signal, the process
generates a notification to the infant's caretaker, that the infant
is at higher risk of SIDS.
[0085] According to another embodiment, the process of FIG. 17 can
be used in fitness training A normal resting heart rate for adults
ranges from 60 to 100 beats per minute. Generally, a lower heart
rate at rest implies more efficient heart function and better
cardiovascular fitness. For example, a well-trained athlete might
have a normal resting heart rate closer to 40 beats per minute.
Thus, a user may specify a target rest heart rate of 40 beats per
minute. The process FIG. 17 generates a comparison between the
actual bio signal associated with said user and the target bio
signal 1720, and based on the comparison, the process generates a
notification whether the user has reached his target, or whether
the user needs to exercise more 1730.
[0086] FIG. 18 is a flowchart of a process for detecting the onset
of a disease, according to one embodiment. The process, at block
1800, obtains the current bio signal associated with a user, such
as presence, motion, temperature, breathing rate, or heart rate,
associated with said user. The process obtains the current bio
signal from a sensor associated with said user. Further, the
process, at block 1810, obtains a history of bio signals associated
with said user from a database. The history of bio signals
comprises the bio signals associated with said user, accumulated
over time. The history of biological signals can be stored in a
database associated with a user. The process, at block 1820, then
detects a discrepancy between the current bio signal and the
history of bio signals, where the discrepancy is indicative of an
onset of a disease. The process, at block 1830, then generates an
alarm to the user's caretaker. The discrepancy between the current
bio signal and the history of bio signals comprises a higher
frequency in the current bio signal than in the history of bio
signals, or a lower frequency in the current bio signal than in the
history of bio signals.
[0087] According to one embodiment, the process of FIG. 18 can be
used to detect an onset of an epileptic seizure. A healthy person
has a normal heart rate between 60 and 100 beats per minute. During
epileptic seizures, the median heart rate associated with said
person exceeds 100 beats per minute. The process of FIG. 18 detects
that the heart rate associated with said user exceeds the normal
heart rate range associated with said user. The process then
generates an alarm to the user's caretaker that the user is having
an epileptic seizure. Although rare, epileptic seizures can cause
the median heart rate associated with a person to drop below 40
beats per minute. Similarly, the process of FIG. 18 detects if the
current heart rate is below the normal heart rate range associated
with said user. The process then generates an alarm to the user's
caretaker that the user is having an epileptic seizure.
[0088] FIG. 19 is a diagrammatic representation of a machine in the
example form of a computer system 1900 within which a set of
instructions, for causing the machine to perform any one or more of
the methodologies or modules discussed herein, may be executed.
[0089] In the example of FIG. 19, the computer system 1900 includes
a processor, memory, non-volatile memory, and an interface device.
Various common components (e.g., cache memory) are omitted for
illustrative simplicity. The computer system 1900 is intended to
illustrate a hardware device on which any of the components
described in the example of FIGS. 1-18 (and any other components
described in this specification) can be implemented. The computer
system 1900 can be of any applicable known or convenient type. The
components of the computer system 1900 can be coupled together via
a bus or through some other known or convenient device.
[0090] This disclosure contemplates the computer system 1900 taking
any suitable physical form. As example and not by way of
limitation, computer system 1900 may be an embedded computer
system, a system-on-chip (SOC), a single-board computer system
(SBC) (such as, for example, a computer-on-module (COM) or
system-on-module (SOM)), a desktop computer system, a laptop or
notebook computer system, an interactive kiosk, a mainframe, a mesh
of computer systems, a mobile telephone, a personal digital
assistant (PDA), a server, or a combination of two or more of
these. Where appropriate, computer system 1900 may include one or
more computer systems 1900; be unitary or distributed; span
multiple locations; span multiple machines; or reside in a cloud,
which may include one or more cloud components in one or more
networks. Where appropriate, one or more computer systems 1900 may
perform without substantial spatial or temporal limitation one or
more steps of one or more methods described or illustrated herein.
As an example and not by way of limitation, one or more computer
systems 1900 may perform in real time or in batch mode one or more
steps of one or more methods described or illustrated herein. One
or more computer systems 1900 may perform at different times or at
different locations one or more steps of one or more methods
described or illustrated herein, where appropriate.
[0091] The processor may be, for example, a conventional
microprocessor such as an Intel Pentium microprocessor or Motorola
power PC microprocessor. One of skill in the relevant art will
recognize that the terms "machine-readable (storage) medium" or
"computer-readable (storage) medium" include any type of device
that is accessible by the processor.
[0092] The memory is coupled to the processor by, for example, a
bus. The memory can include, by way of example but not limitation,
random access memory (RAM), such as dynamic RAM (DRAM) and static
RAM (SRAM). The memory can be local, remote, or distributed.
[0093] The bus also couples the processor to the non-volatile
memory and drive unit. The non-volatile memory is often a magnetic
floppy or hard disk, a magnetic-optical disk, an optical disk, a
read-only memory (ROM), such as a CD-ROM, EPROM, or EEPROM, a
magnetic or optical card, or another form of storage for large
amounts of data. Some of this data is often written, by a direct
memory access process, into memory during execution of software in
the computer 1900. The non-volatile storage can be local, remote,
or distributed. The non-volatile memory is optional because systems
can be created with all applicable data available in memory. A
typical computer system will usually include at least a processor,
memory, and a device (e.g., a bus) coupling the memory to the
processor.
[0094] Software is typically stored in the non-volatile memory
and/or the drive unit. Indeed, storing and entire large program in
memory may not even be possible. Nevertheless, it should be
understood that for software to run, if necessary, it is moved to a
computer readable location appropriate for processing, and for
illustrative purposes, that location is referred to as the memory
in this paper. Even when software is moved to the memory for
execution, the processor will typically make use of hardware
registers to store values associated with the software, and local
cache that, ideally, serves to speed up execution. As used herein,
a software program is assumed to be stored at any known or
convenient location (from non-volatile storage to hardware
registers) when the software program is referred to as "implemented
in a computer-readable medium." A processor is considered to be
"configured to execute a program" when at least one value
associated with the program is stored in a register readable by the
processor.
[0095] The bus also couples the processor to the network interface
device. The interface can include one or more of a modem or network
interface. It will be appreciated that a modem or network interface
can be considered to be part of the computer system 1900. The
interface can include an analog modem, isdn modem, cable modem,
token ring interface, satellite transmission interface (e.g.
"direct PC"), or other interfaces for coupling a computer system to
other computer systems. The interface can include one or more input
and/or output devices. The I/O devices can include, by way of
example but not limitation, a keyboard, a mouse or other pointing
device, disk drives, printers, a scanner, and other input and/or
output devices, including a display device. The display device can
include, by way of example but not limitation, a cathode ray tube
(CRT), liquid crystal display (LCD), or some other applicable known
or convenient display device. For simplicity, it is assumed that
controllers of any devices not depicted in the example of FIG. 9
reside in the interface.
[0096] In operation, the computer system 1900 can be controlled by
operating system software that includes a file management system,
such as a disk operating system. One example of operating system
software with associated file management system software is the
family of operating systems known as Windows.RTM. from Microsoft
Corporation of Redmond, Wash., and their associated file management
systems. Another example of operating system software with its
associated file management system software is the Linux.TM.
operating system and its associated file management system. The
file management system is typically stored in the non-volatile
memory and/or drive unit and causes the processor to execute the
various acts required by the operating system to input and output
data and to store data in the memory, including storing files on
the non-volatile memory and/or drive unit.
[0097] Some portions of the detailed description may be presented
in terms of algorithms and symbolic representations of operations
on data bits within a computer memory. These algorithmic
descriptions and representations are the means used by those
skilled in the data processing arts to most effectively convey the
substance of their work to others skilled in the art. An algorithm
is here, and generally, conceived to be a self-consistent sequence
of operations leading to a desired result. The operations are those
requiring physical manipulations of physical quantities. Usually,
though not necessarily, these quantities take the form of
electrical or magnetic signals capable of being stored,
transferred, combined, compared, and otherwise manipulated. It has
proven convenient at times, principally for reasons of common
usage, to refer to these signals as bits, values, elements,
symbols, characters, terms, numbers, or the like.
[0098] It should be borne in mind, however, that all of these and
similar terms are to be associated with the appropriate physical
quantities and are merely convenient labels applied to these
quantities. Unless specifically stated otherwise as apparent from
the following discussion, it is appreciated that throughout the
description, discussions utilizing terms such as "processing" or
"computing" or "calculating" or "determining" or "displaying" or
"generating" or the like, refer to the action and processes of a
computer system, or similar electronic computing device, that
manipulates and transforms data represented as physical
(electronic) quantities within the computer system's registers and
memories into other data similarly represented as physical
quantities within the computer system memories or registers or
other such information storage, transmission or display
devices.
[0099] The algorithms and displays presented herein are not
inherently related to any particular computer or other apparatus.
Various general purpose systems may be used with programs in
accordance with the teachings herein, or it may prove convenient to
construct more specialized apparatus to perform the methods of some
embodiments. The required structure for a variety of these systems
will appear from the description below. In addition, the techniques
are not described with reference to any particular programming
language, and various embodiments may thus be implemented using a
variety of programming languages.
[0100] In alternative embodiments, the machine operates as a
standalone device or may be connected (e.g., networked) to other
machines. In a networked deployment, the machine may operate in the
capacity of a server or a client machine in a client-server network
environment, or as a peer machine in a peer-to-peer (or
distributed) network environment.
[0101] The machine may be a server computer, a client computer, a
personal computer (PC), a tablet PC, a laptop computer, a set-top
box (STB), a personal digital assistant (PDA), a cellular
telephone, an iPhone, a Blackberry, a processor, a telephone, a web
appliance, a network router, switch or bridge, or any machine
capable of executing a set of instructions (sequential or
otherwise) that specify actions to be taken by that machine.
[0102] While the machine-readable medium or machine-readable
storage medium is shown in an exemplary embodiment to be a single
medium, the term "machine-readable medium" and "machine-readable
storage medium" should be taken to include a single medium or
multiple media (e.g., a centralized or distributed database, and/or
associated caches and servers) that store the one or more sets of
instructions. The term "machine-readable medium" and
"machine-readable storage medium" shall also be taken to include
any medium that is capable of storing, encoding or carrying a set
of instructions for execution by the machine and that cause the
machine to perform any one or more of the methodologies or modules
of the presently disclosed technique and innovation.
[0103] In general, the routines executed to implement the
embodiments of the disclosure, may be implemented as part of an
operating system or a specific application, component, program,
object, module or sequence of instructions referred to as "computer
programs." The computer programs typically comprise one or more
instructions set at various times in various memory and storage
devices in a computer, and that, when read and executed by one or
more processing units or processors in a computer, cause the
computer to perform operations to execute elements involving the
various aspects of the disclosure.
[0104] Moreover, while embodiments have been described in the
context of fully functioning computers and computer systems, those
skilled in the art will appreciate that the various embodiments are
capable of being distributed as a program product in a variety of
forms, and that the disclosure applies equally regardless of the
particular type of machine or computer-readable media used to
actually effect the distribution.
[0105] Further examples of machine-readable storage media,
machine-readable media, or computer-readable (storage) media
include but are not limited to recordable type media such as
volatile and non-volatile memory devices, floppy and other
removable disks, hard disk drives, optical disks (e.g., Compact
Disk Read-Only Memory (CD ROMS), Digital Versatile Disks, (DVDs),
etc.), among others, and transmission type media such as digital
and analog communication links.
[0106] In some circumstances, operation of a memory device, such as
a change in state from a binary one to a binary zero or vice-versa,
for example, may comprise a transformation, such as a physical
transformation. With particular types of memory devices, such a
physical transformation may comprise a physical transformation of
an article to a different state or thing. For example, but without
limitation, for some types of memory devices, a change in state may
involve an accumulation and storage of charge or a release of
stored charge. Likewise, in other memory devices, a change of state
may comprise a physical change or transformation in magnetic
orientation or a physical change or transformation in molecular
structure, such as from crystalline to amorphous or vice versa. The
foregoing is not intended to be an exhaustive list of all exam page
on ples in which a change in state for a binary one to a binary
zero or vice-versa in a memory device may comprise a
transformation, such as a physical transformation. Rather, the
foregoing is intended as illustrative examples.
[0107] A storage medium typically may be non-transitory or comprise
a non-transitory device. In this context, a non-transitory storage
medium may include a device that is tangible, meaning that the
device has a concrete physical form, although the device may change
its physical state. Thus, for example, non-transitory refers to a
device remaining tangible despite this change in state.
Remarks
[0108] In many of the embodiments disclosed in this application,
the technology is capable of allowing multiple different users to
use the same piece of furniture equipped with the presently
disclosed technology. For example, different people can sleep in
the same bed. In addition, two different users can switch the side
of the bed that they sleep on, and the technology disclosed here
will correctly identify which user is sleeping on which side of the
bed. The technology identifies the users based on any of the
following signals alone or in combination: heart rate, breathing
rate, body motion, or body temperature associated with each
user.
[0109] The foregoing description of various embodiments of the
claimed subject matter has been provided for the purposes of
illustration and description. It is not intended to be exhaustive
or to limit the claimed subject matter to the precise forms
disclosed. Many modifications and variations will be apparent to
one skilled in the art. Embodiments were chosen and described in
order to best describe the principles of the invention and its
practical applications, thereby enabling others skilled in the
relevant art to understand the claimed subject matter, the various
embodiments, and the various modifications that are suited to the
particular uses contemplated.
[0110] While embodiments have been described in the context of
fully functioning computers and computer systems, those skilled in
the art will appreciate that the various embodiments are capable of
being distributed as a program product in a variety of forms, and
that the disclosure applies equally regardless of the particular
type of machine or computer-readable media used to actually effect
the distribution.
[0111] Although the above Detailed Description describes certain
embodiments and the best mode contemplated, no matter how detailed
the above appears in text, the embodiments can be practiced in many
ways. Details of the systems and methods may vary considerably in
their implementation details, while still being encompassed by the
specification. As noted above, particular terminology used when
describing certain features or aspects of various embodiments
should not be taken to imply that the terminology is being
redefined herein to be restricted to any specific characteristics,
features, or aspects of the invention with which that terminology
is associated. In general, the terms used in the following claims
should not be construed to limit the invention to the specific
embodiments disclosed in the specification, unless those terms are
explicitly defined herein. Accordingly, the actual scope of the
invention encompasses not only the disclosed embodiments, but also
all equivalent ways of practicing or implementing the embodiments
under the claims.
[0112] The language used in the specification has been principally
selected for readability and instructional purposes, and it may not
have been selected to delineate or circumscribe the inventive
subject matter. It is therefore intended that the scope of the
invention be limited not by this Detailed Description, but rather
by any claims that issue on an application based hereon.
Accordingly, the disclosure of various embodiments is intended to
be illustrative, but not limiting, of the scope of the embodiments,
which is set forth in the following claims.
* * * * *