U.S. patent application number 15/229373 was filed with the patent office on 2017-01-12 for smart wearable devices and methods for optimizing output.
This patent application is currently assigned to SONY CORPORATION. The applicant listed for this patent is SONY CORPORATION OF AMERICA, SONY CORPORATION. Invention is credited to Udupi Ramanath Bhat, Ludovic Copere, Behram DaCosta, Jacelyn Danielson, Vladimir Elgort, Anton Kalachev, Masaki Kataoka, Nobuo Tanaka, John Wong.
Application Number | 20170010663 15/229373 |
Document ID | / |
Family ID | 53878953 |
Filed Date | 2017-01-12 |
United States Patent
Application |
20170010663 |
Kind Code |
A1 |
Tanaka; Nobuo ; et
al. |
January 12, 2017 |
SMART WEARABLE DEVICES AND METHODS FOR OPTIMIZING OUTPUT
Abstract
A smart wearable devices and methods for output optimization are
presented where the smart wearable device receives input from one
or more sensors, including input related to the user's biological
characteristics. This input is used to determine an optimal output
form. If the determined output form is different from the smart
wearable device's native or default output form, the smart wearable
device transcribes the output into the optimal out using a
transcription engine.
Inventors: |
Tanaka; Nobuo; (Glen Rock,
NJ) ; Elgort; Vladimir; (Staten Island, NY) ;
Danielson; Jacelyn; (San Mateo, CA) ; Kalachev;
Anton; (Burlingame, CA) ; Wong; John;
(Morristown, NJ) ; DaCosta; Behram; (San Jose,
CA) ; Bhat; Udupi Ramanath; (Mountain View, CA)
; Copere; Ludovic; (San Jose, CA) ; Kataoka;
Masaki; (Port Washington, NY) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
SONY CORPORATION
SONY CORPORATION OF AMERICA |
Tokyo
New York |
NY |
JP
US |
|
|
Assignee: |
SONY CORPORATION
Tokyo
NY
SONY CORPORATION OF AMERICA
New York
|
Family ID: |
53878953 |
Appl. No.: |
15/229373 |
Filed: |
August 5, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
PCT/US2015/016597 |
Feb 19, 2015 |
|
|
|
15229373 |
|
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|
61943837 |
Feb 24, 2014 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 1/325 20130101;
G16H 40/63 20180101; G06F 1/1698 20130101; Y02D 10/00 20180101;
G06F 1/3287 20130101; G06F 3/015 20130101; G06F 1/3206 20130101;
H04L 63/0861 20130101; H04L 63/0869 20130101; G06F 1/1637 20130101;
H04W 12/0605 20190101; G06F 1/163 20130101; G08B 7/00 20130101;
G16H 40/67 20180101; G06F 3/011 20130101; G06F 3/016 20130101; G06F
1/1626 20130101 |
International
Class: |
G06F 3/01 20060101
G06F003/01; G06F 1/16 20060101 G06F001/16 |
Claims
1. A smart wearable device, the device comprising: (a) a housing,
wherein the housing encases components of a wearable smart device;
(b) one or more sensors, wherein at least one sensor is a
biological sensor configured to acquire biological input; (c) one
or more output forms; (d) a memory; (e) one or more communications
interfaces; (f) a processor; and (g) programming residing in a
non-transitory computer readable medium, wherein the programming is
executable by the computer processor and configured to: (i) receive
input from the one or more sensors, wherein the input may be
acquired automatically or manually entered by a user and wherein at
least some of the input is related to the user's biology; (ii) use
the received input to determine an optimal output form, wherein at
least some of the input used to determine the optimal output form
is related to the user's biology; and (iii) if the device's native
output form is not already in the determined optimal output form,
transcribe the output into the determined optimal output form using
one or more transcription engines.
2. The device of claim 1, further comprising: one or more
environmental sensors, wherein at least one environmental sensor is
configured to acquire contextual input and wherein said programming
is further configured to: receive input from the one or more
environmental sensors, wherein at least some of the input used to
determine the optimal output form is related to the context in
which the smart wearable device is operating.
3. The device of claim 1, wherein said programming is further
configured to: transmit the optimized output to another smart
wearable or non-wearable device, wherein the other smart wearable
device or non-wearable device is configured to convey the optimal
output form to the user.
4. The device of claim 3, wherein said programming is further
configured to: use information inferred from third party data
sources or past personal preferences to determine the optimal
output form.
5. The device of claim 1, wherein the one or more communications
interfaces are selected from the group consisting of a wired
communications interface, a wireless communications interface, a
cellular communications interface, a WiFi communications interface,
a near field communications interface, an infrared communications
interface, a ZigBee communications interface, a Z-Wave
communications interface and a Bluetooth communications
interface.
6. The device of claim 1, wherein said programming is further
configured to: select an optimal combination of transcription
engines using embedded dedicated intelligence and processing
algorithms, wherein the selection is made based on input from the
user sensed in real-time and the user's characteristics.
7. The device of claim 1, wherein said programming is further
configured to: (a) receive a feedback input from the user to rate
the quality of the determined optimal output form; and (b) use the
feedback input as a learning parameter to iteratively improve its
determination of optimal output forms.
8. The device of claim 1, wherein the transcription engine is
accessed by the smart wearable device through a stand-alone
wireless connection or tethered through a wireless-enabled
non-wearable device.
9. The device of claim 1, wherein the transcription engine is a
natively-embedded application or queried remotely through a
cloud-based access.
10. The device of claim 1, wherein one or more transcription
engines are selected from the group consisting of a text to speech
and speech to text engine, a natural language processing engine, an
image generating engine, a sound generating engine, a vibration
generating engine, a smell generating engine and an integrated
third party application programming interface.
11. The device of claim 1, wherein the smart wearable device has a
platform selected from the group consisting of hand worn devices,
finger worn devices, wrist worn devices, head worn devices, arm
worn devices, leg worn devices, ankle worn devices, foot worn
devices, toe worn devices, watches, eyeglasses, rings, bracelets,
necklaces, articles of jewelry, articles of clothing, shoes, hats,
contact lenses, and gloves.
12. A computer implemented method for determining the most optimal
output form from a smart wearable device, the method comprising:
(a) providing a smart wearable device, the smart wearable device
comprising: (i) a housing, wherein the housing encases components
of a wearable smart device; (ii) one or more sensors, wherein at
least one sensor is a biological sensor configured to acquire
biological input; (iii) one or more output forms; (iv) a memory;
(v) one or more communications interfaces; and (vi) a processor;
(b) receiving input from the one or more sensors associated with a
smart wearable device, wherein at least one sensor is a biological
sensor configured to acquire biological input and wherein the input
may be acquired automatically or manually entered by a user; (c)
using the received input to determine an optimal output form,
wherein at least some of the input used to determine the optimal
output form is related to the user's biology; and (d) if the output
information is not already in the determined optimal output form,
transcribing output information into the determined optimal output
form using one or more transcription engines; (e) wherein said
method is performed by executing programming on at least one
computer processor, said programming residing on a non-transitory
medium readable by the computer processor.
13. The method of claim 12, further comprising: receiving input
from one or more environmental sensors associated with the smart
wearable device, wherein at least one environmental sensor is
configured to acquire contextual input and wherein at least some of
the input used to determine the optimal output form is related to
the context in which the smart wearable device is operating.
14. The method of claim 12, wherein the one or more communications
interfaces are selected from the group consisting of a wired
communications interface, a wireless communications interface, a
cellular communications interface, a WiFi communications interface,
a near field communications interface, an infrared communications
interface, ZigBee communications interface, a Z-Wave communications
interface and a Bluetooth communications interface.
15. The method of claim 12, further comprising: selecting an
optimal combination of transcription engines using embedded
dedicated intelligence and processing algorithms, wherein the
selection is made based on input from the user sensed in real-time
and the user's characteristics.
16. The method of claim 12, further comprising: (a) receiving a
feedback input from the user to rate the quality of the determined
optimal output form; and (b) using the feedback input as a learning
parameter to iteratively improve its determination of optimal
output forms.
17. The method of claim 12, wherein the transcription engine is
accessed by the smart wearable device through a stand-alone
wireless connection or tethered through a wireless-enabled
non-wearable device.
18. The method of claim 12, wherein the transcription engine is a
natively-embedded application or queried remotely through a
cloud-based access.
19. The method of claim 12, wherein one or more transcription
engines are selected from the group consisting of a text to speech
and speech to text engine, a natural language processing engine, an
image generating engine, and an integrated third party application
programming interface.
20. The method of claim 12, wherein the smart wearable device has a
platform selected from the group consisting of hand worn devices,
finger worn devices, wrist worn devices, head worn devices, arm
worn devices, leg worn devices, ankle worn devices, foot worn
devices, toe worn devices, watches, eyeglasses, rings, bracelets,
necklaces, articles of jewelry, articles of clothing, shoes, hats,
contact lenses, and gloves.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a 35 U.S.C. .sctn.111(a) continuation of
PCT international application number PCT/US2015/016597 filed on
Feb. 19, 2015, incorporated herein by reference in its entirety,
which claims priority to, and the benefit of, U.S. provisional
patent application Ser. No. 61/943,837 filed on Feb. 24, 2014,
incorporated herein by reference in its entirety. Priority is
claimed to each of the foregoing applications.
[0002] The above-referenced PCT international application was
published as PCT International Publication No. WO 2015/127062 A1 on
Aug. 27, 2015, which publication is incorporated herein by
reference in its entirety.
INCORPORATION-BY-REFERENCE OF COMPUTER PROGRAM APPENDIX
[0003] Not Applicable
NOTICE OF MATERIAL SUBJECT TO COPYRIGHT PROTECTION
[0004] A portion of the material in this patent document is subject
to copyright protection under the copyright laws of the United
States and of other countries. The owner of the copyright rights
has no objection to the facsimile reproduction by anyone of the
patent document or the patent disclosure, as it appears in the
United States Patent and Trademark Office publicly available file
or records, but otherwise reserves all copyright rights whatsoever.
The copyright owner does not hereby waive any of its rights to have
this patent document maintained in secrecy, including without
limitation its rights pursuant to 37 C.F.R. .sctn.1.14.
BACKGROUND
[0005] 1. Field of the Technology
[0006] This technology pertains generally to smart wearable devices
and more specifically to smart wearable devices that use sensorial
input to optimize output.
[0007] 2. Discussion
[0008] Smart wearable devices are extremely limited and ridged in
the way they output information, recommendations and feedback to
the user. The devices have either a very basic output interface
attached to them (such as a screen, audio speaker or motor
actuator) or they rely on an external mobile application (installed
on a smartphone or tablet for instance) or a Web interface for a
richer, more graphical output. This can make the operation of smart
wearable devices difficult for some people because they are
required to learn another user interface and/or language paradigm
and may even have to rely on the use of an external device (such as
a smartphone) in order to get the full potential from their device.
Accordingly, this can limit the desire to use smart wearable
devices. For example, children may not be able to read or
understand textual information and may prefer to have a device
display information in pictograms, videos or with entertaining
icons.
[0009] Users of smart wearable devices may not be able to
understand the raw information, such as number of steps taken in
day or body temperature, which is output by current wearable
devices. Disabled people are excluded from using some of the most
current wearable devices as well. For instance, blind people who
cannot get visual feedback from smart-watches, deaf people unable
to hear audible feedback from smart glasses, tetraplegic people
unable to feel the haptic feedback from their personal trackers,
etc. Therefore, it is desirable to have smart wearable device that
can determine the optimal output form for a specific user.
BRIEF SUMMARY
[0010] An aspect of the present disclosure is a smart wearable
devices and methods for output optimization. In one exemplary
embodiment, a smart wearable device receives input from one or more
sensors, including input related to the user's biological
characteristics. This input can be used to determine an optimal
output form. If the determined output form is different from the
smart wearable device's native or default output form, the smart
wearable device may transcribe the output into the optimal output
using a transcription engine. Examples of transcription engines
include, but are not limited to, text to speech and speech to text
engine, a natural language processing engine, an image generating
engine, a sound generating engine, a vibration generating engine, a
smell generating engine and an integrated third party application
programming interface.
[0011] Further aspects of the technology will be brought out in the
following portions of the specification, wherein the detailed
description is for the purpose of fully disclosing preferred
embodiments of the technology without placing limitations
thereon.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)
[0012] The technology described herein will be more fully
understood by reference to the following drawings which are for
illustrative purposes only:
[0013] FIG. 1 is a schematic diagram of an embodiment of a smart
wearable network described herein.
[0014] FIG. 2 is a functional block diagram of an embodiment of a
smart wearable device described herein.
[0015] FIG. 3 is a schematic diagram illustrating an embodiment of
a smart wearable device optimizing output given specific input
related to a user.
[0016] FIG. 4 is a flow diagram of an exemplary method of a smart
wearable device optimizing output given specific input related to a
user.
DETAILED DESCRIPTION
[0017] The present disclosure generally pertains to wearable
devices that are capable of, for example, performing an action
based on one or more biological or physiological characteristics of
the user wearing the device. Using one or more sensors, a
processor, and code executable on the processor, a wearable device
can be configured to sense and process characteristics that
include, but are not limited to, a wearer's physical
characteristics such as gender, weight, height, body temperature,
skin temperature, heart rate, respiration, blood sugar level, blood
glucose level, stress/fatigue, galvanic skin response, ingestion
(protein), digestion rate, metabolic rate, blood chemistry, sweat,
core and skin temperature, vital signs, eye dryness, tooth decay,
gum disease, energy storage, calorie burn rate, mental alertness,
cardiac rhythm, sleep patterns, caffeine content, vitamin content,
hydration, blood oxygen saturation, blood coritzol level, blood
pressure, cholesterol, lactic acid level, body fat, protein level,
hormone level, muscle mass, pH, etc. Such conditions may also
include, but are not limited to, position (e.g., prone, upright),
movement, or physical state (e.g., sleeping, exercising), etc.
[0018] A wearable device may include one or more output devices
that include, but are not limited to, haptic output devices (e.g.,
offset motors, electroactive polymers, capacitive voltage
generators, Peltier temperature elements, contracting materials,
Braille coding actuators), telemetry devices, visual devices,
audible devices, and other output devices.
[0019] A wearable device include artificial intelligence so that
the device can learn and adapt to the wearer. The device may be
configured to accurately discriminate between erroneous
(accidental, unintended, etc.) and valid sensory inputs, thereby
developing accurate conclusions about a wearer's physical state or
characteristics (e.g., the device does not interpret a wearer
rolling over in their sleep as the wearer exercising). The device
may also include one or more cameras or other visual sensors for
facial, user, or other image recognition. A wearable device may
also be configured to transmit information to and/or retrieve
information from a wearer's digital health history.
[0020] A wearable device may be configured to output information to
a user, to another wearable device, to a non-wearable device, or to
a network according to the particular features and function of the
device.
[0021] A. Generalized System Implementation.
[0022] FIG. 1 illustrates a generalized networked infrastructure
(e.g., system) 100 that includes a network 102. The network could,
for example, be a local area network or a wide area network such as
the Internet. One or more smart wearable devices 104-1 through
104-n according to embodiments of the technology described herein
may be enabled to communicate with the network 102 through a wired
or wireless connection 106. Further, one or more of the smart
wearable devices may be enabled to communicate with another smart
wearable device through the network 102 or by means of a direct
wired or wireless connection 108.
[0023] One or more of the smart wearable devices 104-1 through
104-n also may be enabled to communicate with one or more
non-wearable devices 110-1 through 110-n. The non-wearable devices,
which are beyond the scope of this disclosure, may be any
conventional "smart" device with a processor, associated operating
system, and communications interface. Examples of non-wearable
devices include Smartphones, tablet computers, laptop computers,
desktop computers, and set top boxes. Any of the non-wearable
devices may be of a type enabled to communicate with an external
device through a wired or wireless connection. In that case, one or
more of the smart wearable devices may be enabled to communicate
with one or more of the non-wearable devices by means of a direct
wired or wireless connection 112. Further, one or more of the
non-wearable devices may be of a type enabled to communicate with
the network 102 through a standard wired or wireless connection
114. In that case, one or more of the smart wearable devices may be
enabled to communicate with one or more of the non-wearable devices
through the network 102.
[0024] One or more servers 116-1 through 116-n may be provided in a
client-server configuration and connected to the network by means
of a wired or wireless connection 118. The servers may include
standalone servers, cluster servers, networked servers, or servers
connected in an array to function like a large computer. In that
case, one or more of the smart wearable devices may be enabled to
communicate with one or more of the servers.
[0025] FIG. 2 illustrates a generalized embodiment of a smart
wearable device according to the technology described herein. It
will be appreciated that the embodiment shown may be modified or
customized to enable performing the functions described herein. In
the exemplary embodiment shown, the smart wearable device includes
an "engine" 200 having a processor 202, memory 204, and application
software code 206. The processor 202 can be any suitable
conventional processor. The memory 204 may include any suitable
conventional RAM type memory and/or ROM type memory with associated
storage space for storing the application programming code 206.
[0026] A conventional wired or wireless communications module 208
(e.g., transmitter or receiver or transceiver) may be included as
needed for performing one or more of the functions of the smart
wearable device described herein. Examples of wireless
communication capabilities that can be provided include, but are
not limited to, Bluetooth, Wi-Fi, infrared, cellular, ZigBee,
Z-Wave and near field communication. One or more conventional
interfaces or controllers 210 may also be provided if needed.
Examples of interfaces or controllers include, but are not limited
to, analog to digital converters, digital to analog converters,
buffers, etc.
[0027] The device may include at least one input 212 for a
biological or physiological sensor for providing input to the
device to perform one or more of the functions described herein.
Sensor inputs 214-1 through 214-n for optional sensors may be
included as well. These optional input sensors may include, but are
not limited to, accelerometers, temperature sensors, altitude
sensors, motion sensors, position sensors, and other sensors to
perform the function(s) described herein. One or more conventional
interfaces or controllers 216 may be provided if needed for the
sensors. Examples of interfaces or controllers include, but are not
limited to, analog to digital converters, digital to analog
converters, buffers, etc.
[0028] Additionally, the device may include one or more outputs
218-1 through 218-n to drive one or more output devices (and
include those output devices). These output devices may include,
but are not limited to, haptic output devices, telemetry devices,
visual devices, audible devices, and other output devices to
perform the functions described herein. One or more conventional
interfaces or controllers 220 may be provided if needed for the
output devices. Examples of interfaces or controllers include, but
are not limited to, analog to digital converters, digital to analog
converters, buffers, etc.
[0029] A user input 222 may be provided according to the functions
described herein. The user input may, for example, initiate one or
more functions, terminate one or more functions, or intervene in a
running process. The user input can be any conventional input
device, including but not limited to, manual switches, touch
sensors, magnetic sensors, proximity sensors, etc. One or more
conventional interfaces or controllers 224 may be provided if
needed for the output devices. Examples of interfaces or
controllers include, but are not limited to, analog to digital
converters, digital to analog converters, buffers, etc.
[0030] Depending on the function(s) described herein, the engine
200 may also include a feedback loop 226 for machine learning or
other adaptive functions. The feedback loop may also provide for
device calibration.
[0031] It will be appreciated that a smart wearable device as
described herein would necessarily include a housing or carrier for
the above-described components. It will further be appreciated
that, as used herein, the term "smart wearable device" means a
device that would be worn or otherwise associated with the body of
a user and be "connected" to the user by means of at least one
sensor for sensing one or more biological or physiological
conditions of the user.
[0032] The particular form of the housing or carrier (i.e.,
wearable platform) can vary according to choice and suitability for
performing the functions described herein. Examples of wearable
platforms include, but are not limited to, hand worn devices,
finger worn devices, wrist worn devices, head worn devices, arm
worn devices, leg worn devices, ankle worn devices, foot worn
devices, toe worn devices, watches, eyeglasses, rings, bracelets,
necklaces, articles of jewelry, articles of clothing, shoes, hats,
contact lenses, gloves, etc.
[0033] It will further be appreciated that the input sensors and
output devices may be integrated into the wearable platform, or may
be external to the wearable platform, as is desired and/or suitable
for the function(s) of the smart wearable device.
[0034] B. Smart Wearable Device and Methods for Output
Optimization.
[0035] A smart wearable device that can automatically or
semi-automatically translate, transcribe, render or otherwise adapt
its output from its "native form" to another type (or multiple
types) of output form which can be more easily, quickly or deeply
understood (and acted upon) by the specific user is described
herein. This includes, but is not limited to: transforming text
into a dynamically-generated picture or video, transforming visual
output into audio or haptics (or vice versa), reducing the
complexity of the information (or increasing it in the case it is
to be read by professionals such as health providers), etc. The
smart wearable device can determine which output form is optimal
for a particular user by analyzing the sensor input from the user.
Such input can be acquired automatically or may be manually entered
into the device by the user.
[0036] Referring now to FIG. 3, a schematic diagram 300 is show in
which a wearable smart device 104-1 may include sensors 214-1,
214-n for acquiring input, including but not limited to, biological
sensors 212 that are configured to collect input related to
biological characteristics of the user 302 (see also FIG. 2). Such
biological characteristics may be, but are not limited to, age,
gender, education level, mental status, health conditions, etc. The
smart wearable device may also use third party information, such as
information from social media or e-mail messages, to optimize an
output form. Optionally, past personal preferences, such as a
favorite type of output given a specific situation or saved manual
preset output forms, may be used to optimize a particular output
form. In the example embodiment shown in FIG. 3, the smart wearable
device may automatically acquire input 304 from one of its sensors,
such as a biological sensor 212. A user may also enter any desired
input manually into the smart wearable device, such as personal
characteristics or schedules. The smart wearable device can then
use this input 304 to determine the optimal form for the device's
output. The optimal output form selected by the smart wearable
device may be, but is not limited to, images 306, sound, such as
music tones or voices 308, haptic signals 310 and lights 312, or a
combination of these output form examples.
[0037] If the native or default output form is determined to be
different than the determined optimal output form, the smart
wearable device may transcribe the output information into the
optimal output form using one or more transcription engines. This
transcription engine may be accessed by the smart wearable device
through a stand-alone wireless connection or tethered through a
wireless-enabled non-wearable device, for example. The
transcription engine may also be a natively-embedded application or
queried remotely through a cloud-based access. The smart wearable
device may select a specific transcription engine, such as a text
to speech and speech to text engine, a natural language processing
engine, an image generating engine, a sound generating engine, a
vibration generating engine, a smell generating engine or an
integrated third party application programming interface, such as a
medical dictionary, foreign language dictionary, or sign language
directory. The image generation image engine can combine a set of
basic patterns and images (either stored locally or remotely) into
a visual image/video output. For example, the device could pull the
user's Facebook picture, extract the user's face, and assemble it
with a colored background to visually indicate positive (or
negative) feedback.
[0038] Referring back to FIG. 3, once the output has been
optimized, the smart wearable device may convey the optimized
output to the user 302 itself or it may transmit 316 the optimized
output to one or more non-wearable devices 110-1, 110-n or another
smart wearable device 104-n and that device may then convey the
optimized output to the user 302.
[0039] Referring now to FIG. 4, a flow diagram 400 is shown, which
illustrates how one embodiment of the smart wearable device and
methods may be used to optimize its output. The smart wearable
device may receive input from a sensor that may be internal or
external to the smart wearable device 410. Although at least one of
the sensors may be biological, acquiring biological input from the
user, other sensors may also be used to collect input, such as an
environmental sensor that may collect input related to the context
in which the output will be conveyed 420. The smart wearable device
may use this received input to determine an optimal output form
430. If the smart wearable device's native or default output form
is different from the determined optimal output form, the smart
wearable device may then transcribe the output into the optimal
form using one or more transcription engines 440. Once the optimal
output is achieved, the smart wearable device may convey the
optimized output to a user itself 450 or the smart wearable may
transmit the optimized output to an alternative device 460 and that
device may then convey the optimized output 450.
[0040] A smart wearable device may reduce barriers to using the
device by providing outputs specifically tailored to the user.
Additionally, it will enable a single model of device to be used in
a variety of ways and by a broader population and may also make
wearable devices' outputs (especially in case of health/fitness
monitoring) useful for both the consumer wearer ("B2C" output type)
as well as potential healthcare professionals ("B2B" output).
[0041] In one embodiment, the smart wearable device may measure,
via GPS or other mechanism, the distance travelled by a user during
a run. If the wearer has a personal trainer helping the wearer
train for a marathon, for example, the distance information can be
communicated to the trainer's wearable or non-wearable device in
the optimized format of a map displaying the running route. The map
information can provide richer detail to the trainer who can use
this information to develop better training routines for the wearer
in training.
[0042] In another embodiment, the watch and biological sensor
components of the smart wearable device can measure the pulse rate
of the wearer. Instead of displaying the pulse rate data on the
screen, the smart wearable device can communicate the pulse rate to
the wearer aurally or with a haptic output. Although communicating
a wearer's actual heart rate by haptic feedback may be overwhelming
(e.g. 140 beats per minute in haptic feedback or a tone sounding
140 times in one minutes), the wearable device can be programmed to
determine which of two or three bands the wearer's pulse rate fits
within and generate a tone or haptic response specific to that
particular band. An example of the pulse bands could be: <100
beats/min; 100-120 beats/min; 130-140 beats/min; >140 beats/min.
In some cases, the aural mode may be optimum because the user has
selected this mode as the preferred communication mode (rather than
looking at the watch display). On the other hand, a low light
environment could be determined by the programming and
automatically switch the device to an aural or haptic output mode
so that the bright display doesn't distract the wearer or drain
power from the battery unnecessarily by running the bright
display.
[0043] In another embodiment of the smart wearable device, the user
could rate the output optimization decision that the smart wearable
device has made and the smart wearable device may then improve its
automated output transcription.
[0044] Embodiments of the present technology may be described with
reference to flowchart illustrations of methods and systems
according to embodiments of the technology, and/or algorithms,
formulae, or other computational depictions, which may also be
implemented as computer program products. In this regard, each
block or step of a flowchart, and combinations of blocks (and/or
steps) in a flowchart, algorithm, formula, or computational
depiction can be implemented by various means, such as hardware,
firmware, and/or software including one or more computer program
instructions embodied in computer-readable program code logic. As
will be appreciated, any such computer program instructions may be
loaded onto a computer, including without limitation a general
purpose computer or special purpose computer, or other programmable
processing apparatus to produce a machine, such that the computer
program instructions which execute on the computer or other
programmable processing apparatus create means for implementing the
functions specified in the block(s) of the flowchart(s).
[0045] Accordingly, blocks of the flowcharts, algorithms, formulae,
or computational depictions support combinations of means for
performing the specified functions, combinations of steps for
performing the specified functions, and computer program
instructions, such as embodied in computer-readable program code
logic means, for performing the specified functions. It will also
be understood that each block of the flowchart illustrations,
algorithms, formulae, or computational depictions and combinations
thereof described herein, can be implemented by special purpose
hardware-based computer systems which perform the specified
functions or steps, or combinations of special purpose hardware and
computer-readable program code logic means.
[0046] Furthermore, these computer program instructions, such as
embodied in computer-readable program code logic, may also be
stored in a computer-readable memory that can direct a computer or
other programmable processing apparatus to function in a particular
manner, such that the instructions stored in the computer-readable
memory produce an article of manufacture including instruction
means which implement the function specified in the block(s) of the
flowchart(s). The computer program instructions may also be loaded
onto a computer or other programmable processing apparatus to cause
a series of operational steps to be performed on the computer or
other programmable processing apparatus to produce a
computer-implemented process such that the instructions which
execute on the computer or other programmable processing apparatus
provide steps for implementing the functions specified in the
block(s) of the flowchart(s), algorithm(s), formula(e), or
computational depiction(s).
[0047] It will further be appreciated that "programming" as used
herein refers to one or more instructions that can be executed by a
processor to perform a function as described herein. The
programming can be embodied in software, in firmware, or in a
combination of software and firmware. The programming can be stored
local to the device in non-transitory media, or can be stored
remotely such as on a server, or all or a portion of the
programming can be stored locally and remotely. Programming stored
remotely can be downloaded (pushed) to the device by user
initiation, or automatically based on one or more factors, such as,
for example, location, a timing event, detection of an object,
detection of a facial expression, detection of location, detection
of a change in location, or other factors. It will further be
appreciated that as used herein, that the terms processor, central
processing unit (CPU), and computer are used synonymously to denote
a device capable of executing the programming and communication
with input/output interfaces and/or peripheral devices.
[0048] From the discussion above it will be appreciated that the
technology can be embodied in various ways, including but not
limited to the following:
[0049] 1. A smart wearable device, the device comprising: (a) a
housing, wherein the housing encases components of a wearable smart
device; (b) one or more sensors, wherein at least one sensor is a
biological sensor configured to acquire biological input; (c) one
or more output forms; (d) a memory; (e) one or more communications
interfaces; (f) a processor; and (g) programming residing in a
non-transitory computer readable medium, wherein the programming is
executable by the computer processor and configured to: (i) receive
input from the one or more sensors, wherein the input may be
acquired automatically or manually entered by a user and wherein at
least some of the input is related to the user's biology; (ii) use
the received input to determine an optimal output form, wherein at
least some of the input used to determine the optimal output form
is related to the user's biology; and (iii) if the device's native
output form is not already in the determined optimal output form,
transcribe the output into the determined optimal output form using
one or more transcription engines.
[0050] 2. The device of any preceding embodiments, further
comprising: one or more environmental sensors, wherein at least one
environmental sensor is configured to acquire contextual input and
wherein said programming is further configured to: receive input
from the one or more environmental sensors, wherein at least some
of the input used to determine the optimal output form is related
to the context in which the smart wearable device is operating.
[0051] 3. The device of any preceding embodiments, wherein said
programming is further configured to: transmit the optimized output
to another smart wearable or non-wearable device, wherein the other
smart wearable device or non-wearable device is configured to
convey the optimal output form to the user.
[0052] 4. The device of any preceding embodiments, wherein said
programming is further configured to: use information inferred from
third party data sources or past personal preferences to determine
the optimal output form.
[0053] 5. The device of any preceding embodiments, wherein the one
or more communications interfaces are selected from the group
consisting of a wired communications interface, a wireless
communications interface, a cellular communications interface, a
WiFi communications interface, a near field communications
interface, an infrared communications interface, a ZigBee
communications interface, a Z-Wave communications interface and a
Bluetooth communications interface.
[0054] 6. The device of any preceding embodiments, wherein said
programming is further configured to: select an optimal combination
of transcription engines using embedded dedicated intelligence and
processing algorithms, wherein the selection is made based on input
from the user sensed in real-time and the user's
characteristics.
[0055] 7. The device of any preceding embodiments, wherein said
programming is further configured to: (a) receive a feedback input
from the user to rate the quality of the determined optimal output
form; and (b) use the feedback input as a learning parameter to
iteratively improve its determination of optimal output forms.
[0056] 8. The device of any preceding embodiments, wherein the
transcription engine is accessed by the smart wearable device
through a stand-alone wireless connection or tethered through a
wireless-enabled non-wearable device.
[0057] 9. The device of any preceding embodiments, wherein the
transcription engine is a natively-embedded application or queried
remotely through a cloud-based access.
[0058] 10. The device of any preceding embodiments, wherein one or
more transcription engines are selected from the group consisting
of a text to speech and speech to text engine, a natural language
processing engine, an image generating engine, a sound generating
engine, a vibration generating engine, a smell generating engine
and an integrated third party application programming
interface.
[0059] 11. The device of any preceding embodiments, wherein the
smart wearable device has a platform selected from the group
consisting of hand worn devices, finger worn devices, wrist worn
devices, head worn devices, arm worn devices, leg worn devices,
ankle worn devices, foot worn devices, toe worn devices, watches,
eyeglasses, rings, bracelets, necklaces, articles of jewelry,
articles of clothing, shoes, hats, contact lenses, and gloves.
[0060] 12. A computer implemented method for determining the most
optimal output form from a smart wearable device, the method
comprising: (a) providing a smart wearable device, the smart
wearable device comprising: (i) a housing, wherein the housing
encases components of a wearable smart device; (ii) one or more
sensors, wherein at least one sensor is a biological sensor
configured to acquire biological input; (iii) one or more output
forms; (iv) a memory; (v) one or more communications interfaces;
and (vi) a processor; (b) receiving input from the one or more
sensors associated with a smart wearable device, wherein at least
one sensor is a biological sensor configured to acquire biological
input and wherein the input may be acquired automatically or
manually entered by a user; (c) using the received input to
determine an optimal output form, wherein at least some of the
input used to determine the optimal output form is related to the
user's biology; and (d) if the output information is not already in
the determined optimal output form, transcribing output information
into the determined optimal output form using one or more
transcription engines; (e) wherein said method is performed by
executing programming on at least one computer processor, said
programming residing on a non-transitory medium readable by the
computer processor.
[0061] 13. The method of any preceding embodiments, further
comprising: receiving input from one or more environmental sensors
associated with the smart wearable device, wherein at least one
environmental sensor is configured to acquire contextual input and
wherein at least some of the input used to determine the optimal
output form is related to the context in which the smart wearable
device is operating.
[0062] 14. The method of any preceding embodiments, wherein the one
or more communications interfaces are selected from the group
consisting of a wired communications interface, a wireless
communications interface, a cellular communications interface, a
WiFi communications interface, a near field communications
interface, an infrared communications interface, ZigBee
communications interface, a Z-Wave communications interface and a
Bluetooth communications interface.
[0063] 15. The method of any preceding embodiments, further
comprising: selecting an optimal combination of transcription
engines using embedded dedicated intelligence and processing
algorithms, wherein the selection is made based on input from the
user sensed in real-time and the user's characteristics.
[0064] 16. The method of any preceding embodiments, further
comprising: (a) receiving a feedback input from the user to rate
the quality of the determined optimal output form; and (b) using
the feedback input as a learning parameter to iteratively improve
its determination of optimal output forms.
[0065] 17. The method of any preceding embodiments, wherein the
transcription engine is accessed by the smart wearable device
through a stand-alone wireless connection or tethered through a
wireless-enabled non-wearable device.
[0066] 18. The method of any preceding embodiments, wherein the
transcription engine is a natively-embedded application or queried
remotely through a cloud-based access.
[0067] 19. The method of any preceding embodiments, wherein one or
more transcription engines are selected from the group consisting
of a text to speech and speech to text engine, a natural language
processing engine, an image generating engine, and an integrated
third party application programming interface.
[0068] 20. The method of any preceding embodiments, wherein the
smart wearable device has a platform selected from the group
consisting of hand worn devices, finger worn devices, wrist worn
devices, head worn devices, arm worn devices, leg worn devices,
ankle worn devices, foot worn devices, toe worn devices, watches,
eyeglasses, rings, bracelets, necklaces, articles of jewelry,
articles of clothing, shoes, hats, contact lenses, and gloves.
[0069] Although the description above contains many details, these
should not be construed as limiting the scope of the technology but
as merely providing illustrations of some of the presently
preferred embodiments of this technology. Therefore, it will be
appreciated that the scope of the present technology fully
encompasses other embodiments which may become obvious to those
skilled in the art, and that the scope of the present technology is
accordingly to be limited by nothing other than the appended
claims, in which reference to an element in the singular is not
intended to mean "one and only one" unless explicitly so stated,
but rather "one or more." All structural, chemical, and functional
equivalents to the elements of the above-described preferred
embodiment that are known to those of ordinary skill in the art are
expressly incorporated herein by reference and are intended to be
encompassed by the present claims. Moreover, it is not necessary
for a device or method to address each and every problem sought to
be solved by the present technology, for it to be encompassed by
the present claims. Furthermore, no element, component, or method
step in the present disclosure is intended to be dedicated to the
public regardless of whether the element, component, or method step
is explicitly recited in the claims. No claim element herein is to
be construed under the provisions of 35 U.S.C. 112 unless the
element is expressly recited using the phrase "means for" or "step
for".
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