U.S. patent application number 16/275153 was filed with the patent office on 2020-08-13 for measuring user respiration at extremities.
This patent application is currently assigned to Vardas Solutions LLC. The applicant listed for this patent is Vardas Solutions LLC. Invention is credited to Alejandro Jimenez, Alex Jones, Jan Niewiadomski, Chad Vardas.
Application Number | 20200253507 16/275153 |
Document ID | 20200253507 / US20200253507 |
Family ID | 1000003881615 |
Filed Date | 2020-08-13 |
Patent Application | download [pdf] |
United States Patent
Application |
20200253507 |
Kind Code |
A1 |
Jones; Alex ; et
al. |
August 13, 2020 |
MEASURING USER RESPIRATION AT EXTREMITIES
Abstract
Systems and methods measure impedance across a user's chest
during respiration to determine a rate of respiration. With
AC-modulation contacts separated from impedance-measuring contacts,
analog filtering to remove EMI, a bridging capacitor to remove DC
noise, and digital filtering to further remove EMI, a user's
respiration may be measured with the AC-modulation contacts and the
impedance-measuring contacts placed at user extremities.
Inventors: |
Jones; Alex; (Carlsbad,
CA) ; Vardas; Chad; (El Dorado Hills, CA) ;
Jimenez; Alejandro; (Maple Grove, MN) ; Niewiadomski;
Jan; (Aquebogue, NY) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Vardas Solutions LLC |
El Dorado Hills |
CA |
US |
|
|
Assignee: |
Vardas Solutions LLC
El Dorado Hills
CA
|
Family ID: |
1000003881615 |
Appl. No.: |
16/275153 |
Filed: |
February 13, 2019 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/0531 20130101;
A61B 5/0816 20130101; A61B 5/7278 20130101; A61B 5/7225 20130101;
A61B 5/681 20130101 |
International
Class: |
A61B 5/08 20060101
A61B005/08; A61B 5/00 20060101 A61B005/00; A61B 5/053 20060101
A61B005/053 |
Claims
1.-10. (canceled)
11. A wrist-mountable device including: electronics including a
processor with memory and instructions; a first user contact
disposed on a first side of the device; a second user contact
disposed on a second side of the device; a third user contact
disposed on the first side of the device; and a fourth user contact
disposed on the second side of the device or a third side of the
device, wherein: when the device is mounted on the user, and the
first side of the device is positioned against a first arm of the
user, the first user contact and the third user contact make
contact with the first arm of the user and are not accessible by a
second arm of the user, and the second user contact and fourth user
contact are accessible by the second arm; and the instructions,
when executed by the processor with the first and third user
contacts in contact with the first arm and the second and fourth
user contacts in contact with the second arm, cause the electronics
to: provide an AC current between the first and second user
contacts, the AC current causing an impedance to develop between
the third and the fourth user contacts; detect the impedance
between the third and the fourth user contacts, the impedance
changing with time; and based on the detected change of the
impedance with time, create a signal indicating a respiration rate
of the user.
12. The device of claim 11, wherein the instructions further cause
the electronics to: create an impedance signal from the detected
impedance between the third and the fourth user contacts; filter
the impedance signal to remove a DC component; and filter the
impedance signal through a low-pass filter.
13. The device of claim 12, wherein the low-pass filter has a
cut-off frequency of two hertz and the attenuation is minus forty
decibels per decade above three hertz.
14.-19. (canceled)
20. The device of claim 11, wherein the electronics includes a
Texas Instruments ADS1292R analog-to-digital converter and an Arm
Cortex M4 processor and first through fourth electronics contacts
are on the Texas Instruments ADS1292R analog-to-digital
converter.
21. A method comprising: providing a user with a wrist-mountable
device including: electronics including a processor with memory and
instructions; a first user contact disposed on a first side of the
device; a second user contact disposed on a second side of the
device; a third user contact disposed on the first side of the
device; and a fourth user contact disposed on the second side of
the device or a third side of the device, wherein: when the device
is mounted on the user, and the first side of the device is
positioned against a first arm of the user, the first user contact
and the third user contact make contact with the first arm of the
user and are not accessible by a second arm of the user, and the
second user contact and fourth user contact are accessible by the
second arm; bringing the first and third user contacts in contact
with the first arm and the second and fourth user contacts in
contact with the second arm: providing, by the wrist-mountable
device, an AC current between the first and second user contacts,
the AC current causing an impedance to develop between the third
and the fourth user contacts; detecting, by the wrist-mountable
device, the impedance between the third and the fourth user
contacts, the impedance changing with time; and based on the
detected change of the impedance with time, creating, by the
wrist-mountable device, a signal indicating a respiration rate of
the user.
22. The method of claim 21, further including: creating, by the
wrist-mountable device, an impedance signal from the detected
impedance between the third and the fourth user contacts;
filtering, by the wrist-mountable device, the impedance signal to
remove a DC component; and filtering, by the wrist-mountable
device, the impedance signal through a low-pass filter.
23. The method of claim 22, wherein the low-pass filter has a
cut-off frequency of two hertz and the attenuation is minus forty
decibels per decade above three hertz.
24. The method of claim 21, wherein the electronics includes a
Texas Instruments ADS1292R analog-to-digital converter and an Arm
Cortex M4 processor and first through fourth electronics contacts
are on the Texas Instruments ADS1292R analog-to-digital
converter.
25. A non-transitory computer-readable medium encoded with a
plurality of instructions which, when executed by a processor of a
wrist-mounted device including: electronics including the processor
and memory; a first user contact disposed on a first side of the
device; a second user contact disposed on a second side of the
device; a third user contact disposed on the first side of the
device; and a fourth user contact disposed on the second side of
the device or a third side of the device, wherein: when the device
is mounted on the user, and the first side of the device is
positioned against a first arm of the user, the first user contact
and the third user contact make contact with the first arm of the
user and are not accessible by a second arm of the user, and the
second user contact and fourth user contact are accessible by the
second arm; and with the first and third user contacts in contact
with the first arm and the second and fourth user contacts in
contact with the second arm, cause the wrist-mounted device to:
provide an AC current between the first and second user contacts,
the AC current causing an impedance to develop between the third
and the fourth user contacts; detect the impedance between the
third and the fourth user contacts, the impedance changing with
time; and based on the detected change of the impedance with time,
create a signal indicating a respiration rate of the user.
26. The computer-readable medium of claim 25, the instructions
further causing the wrist-mounted device to: create an impedance
signal from the detected impedance between the third and the fourth
user contacts; filter the impedance signal to remove a DC
component; and filter the impedance signal through a low-pass
filter.
27. The computer-readable medium of claim 26, wherein the low-pass
filter has a cut-off frequency of two hertz and the attenuation is
minus forty decibels per decade above three hertz.
28. The computer-readable medium of claim 25, wherein the
electronics includes a Texas Instruments ADS1292R analog-to-digital
converter and an Arm Cortex M4 processor and first through fourth
electronics contacts are on the Texas Instruments ADS1292R
analog-to-digital converter.
29. The device of claim 11, wherein the second user contact and
fourth user contact being accessible by the second arm includes the
second user contact and fourth user contact being accessible by one
or more fingers on a hand of the second arm.
30. The method of claim 21, wherein the second user contact and
fourth user contact being accessible by the second arm includes the
second user contact and fourth user contact being accessible by one
or more fingers on a hand of the second arm.
31. The computer-readable medium of claim 25, wherein the second
user contact and fourth user contact being accessible by the second
arm includes the second user contact and fourth user contact being
accessible by one or more fingers on a hand of the second arm.
Description
CROSS-REFERENCE TO RELATED CASES
[0001] The present application is related to International
Application Number PCT/US18/37156, entitled "METHODS AND SYSTEMS
FOR PROVIDING A BREATHING RATE CALIBRATED TO A RESONANCE BREATHING
FREQUENCY," filed on Jun. 12, 2018, and to U.S. patent application
Ser. No. 16/006,558, entitled "METHODS AND SYSTEMS FOR PROVIDING A
BREATHING RATE CALIBRATED TO A RESONANCE BREATHING FREQUENCY,"
filed on Jun. 12, 2018 which is a continuation-in-part of U.S.
patent application Ser. No. 15/428,115, entitled "STRESS MANAGEMENT
USING BIOFEEDBACK," filed on Feb. 8, 2017, which claims priority to
U.S. Provisional Patent Application No. 62/292,450, entitled
"WEARABLE APPARATUS WITH BIOFEEDBACK," filed on Feb. 8, 2016, each
of which is hereby incorporated by reference.
TECHNICAL FIELD
[0002] The present disclosure relates to the field of sensors,
including, more particularly, to methods and systems for measuring
a user's respiration.
BACKGROUND
[0003] It is desirable to be able to measure the respiration rate
of a user. For example, heart rate generally increases upon
inhalation and decreases upon exhalation, i.e., some heart rate
variation is induced by respiration. Heart Rate Variability (HRV)
is the variation of the time intervals between heart beats. An
increase in HRV is desirable because it is indicative of a heart
rate that is variable and responsive to physiological demands. HRV
is greatest when individuals breathe at a frequency that is
particular to that individual--their resonance breathing frequency
(or "resonance breathing rate"). Respiratory Sinus Arrhythmia (RSA)
occurs when Heart Rate Variability (HRV) is in synchrony with
respiration, shown when variability on an ECG is shortened during
inspiration ("inhalation") and prolonged during expiration
("exhalation"). Thus, it may be desirable to determine a user's
respiration rate and whether that rate is in synchrony with
HRV.
[0004] Some existing systems and methods for measuring a user's
respiration rate rely on a change in the impedance of the user's
chest. That change in impedance is caused by two aspects of a
user's respiration: a change in the volume of gas in relation to
the surrounding tissue; and a change in the electrical path length
across the chest that is caused by the expansion of the chest. The
impedance increases as the gas volume and path length increase. To
measure that change, electrodes may be placed on the user on either
side of the chest and modulation signals (excitation signals of an
alternating current signal at a known frequency) may be passed
between the electrodes. A base voltage signal is created between
the electrodes by the impedance of the user's chest to the AC
current when the user has completely exhaled. A respiration voltage
signal is imposed on the base voltage signal by the increase in
impedance caused by the user's respiration. To determine the
respiration voltage signal, the resulting combined voltage signal
is demodulated. The respiration frequency is determined from the
resulting demodulated voltage signal.
[0005] FIG. 1 is a prior art circuit diagram for a Texas
Instruments ADS1292R from the data sheet for the Texas Instruments
ADS1292R, which is a low-power, 2-channel, 24-bit analog-to-digital
converter. The datasheet for a Texas Instruments ADS1292R discloses
that a feature of the ADS1292R is an integrated respiration
impedance measurement. FIG. 1 depicts FIG. 56 from the data sheet
for the TI ADS1292R. The pin assignments from the ADS1292R are
provided in TABLE 1.
TABLE-US-00001 TABLE 1 NAME; TERMINAL; FUNCTION; DESCRIPTION AVDD;
12; Supply; Analog supply AVSS; 13; Supply; Analog ground CLK; 17;
Digital input; Master clock input CLKSEL; 14; Digital input; Master
clock select CS; 18; Digital input; Chip select DGND; 24; Supply;
Digital ground DIN; 19; Digital input; SPI data in DOUT; 21;
Digital output; SPI data out DRDY; 22; Digital output; Data ready;
active low DVDD; 23; Supply; Digital power supply GPIO1/RCLK1; 26;
Digital input/output; General-purpose I/O 1 or resp clock 1
(ADS1292R) GPIO2/RCLK2; 25; Digital input/output; General-purpose
I/O 2 or resp clock 2 (ADS1292R) IN1N.sup.(1); 3; Analog input;
Differential analog negative input 1 IN1P.sup.(1); 4; Analog input;
Differential analog positive input 1 IN2N.sup.(1); 5; Analog input;
Differential analog negative input 2 IN2P.sup.(1); 6; Analog input;
Differential analog positive input 2 PGA1N; 1; Analog output; PGA1
inverting output PGA1P; 2; Analog output; PGA1 noninverting output
PGA2N; 7; Analog output; PGA2 inverting output PGA2P; 8; Analog
output; PGA2 noninverting output PWDN/RESET; 15; Digital input;
Power-down or system reset; active low RESP_MODN/IN3N.sup.(1); 32;
Analog input/output; N-side respiration excitation signal for
respiration or auxiliary input 3N RESP_MODP/IN3P.sup.(1); 31;
Analog input/output; P-side respiration excitation signal for
respiration or auxiliary input 3P RLDIN/RLDREF; 29; Analog input;
Right leg drive input to MUX or RLD amplifier noninverting input;
connect to AVDD if not used RLDINV; 28; Analog input; Right leg
drive inverting input; connect to AVDD if not used RLDOUT; 30;
Analog input; Right leg drive output SCLK; 20; Digital input; SPI
clock START; 16; Digital input; Start conversion VCAP1; 11; --;
Analog bypass capacitor VCAP2; 27; --; Analog bypass capacitor
VREFN; 10; Analog input; Negative reference voltage; must be
connected to AVSS VREFP; 9; Analog input/output; Positive reference
voltage .sup.(1)Connect unused analog inputs to AVDD.
[0006] According to the data sheet for the TI ADS1292R, the
modulation signals are supplied by RESP_MODP and RESP_MODN.
Exemplary modulation frequencies are 32 kHz and 64 kHz. Also,
according to the data sheet for the TI ADS1292R, if the Right Arm
Lead and Left Arm Lead are intended to measure respiration and ECG
signals, the two leads are each wired into channel 1 for
respiration signals and channel 2 for ECG signals. Accordingly,
FIG. 1 depicts the Right Arm Lead wired into IN2N and IN1N and the
Left Arm Lead wired into IN1P and IN2P. FIG. 1 further depicts that
the Right Arm Lead is also wired into RESP_MODP and that the Left
Arm Lead is also wired into RESP_MODP.
[0007] However, Applicant determined that the result of the circuit
disclosed in the data sheet for the TI ADS1292R was unsatisfactory
for measuring respiration with the contacts placed at a user's
extremities. Thus, there is a need for a system and method for
measuring a user's respiration from extremities.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] The embodiments are illustrated by way of example and not
limitation in the figures of the accompanying drawings, in which
like references indicate similar elements, and in which:
[0009] FIG. 1 is a prior art circuit diagram;
[0010] FIG. 2 is a circuit diagram illustrating aspects of an
embodiment of a system for measuring the respiration of a user;
[0011] FIG. 3 is a circuit diagram further illustrating aspects of
the embodiment of a system for measuring the respiration of a user
of FIG. 2;
[0012] FIG. 4 illustrates an embodiment of a method for measuring
the respiration of a user;
[0013] FIG. 5 illustrates an embodiment of a method for measuring
the respiration of a user;
[0014] FIG. 6 illustrates an embodiment of a method for measuring
the respiration of a user;
[0015] FIG. 7 illustrates an embodiment of a method for measuring
the respiration of a user;
[0016] FIG. 8 is a simplified, exemplary block diagram of an
embodiment of a system for measuring the respiration of a user;
[0017] FIG. 9 is an exemplary block diagram of a computing device
from the system of FIG. 8;
[0018] FIG. 10 includes front, back, top, bottom, and right views
of an embodiment of a biometric analysis device implementing
embodiments of the systems and methods disclosed herein; and
[0019] FIG. 11 is a perspective view of the biometric analysis
device of FIG. 10.
DETAILED DESCRIPTION
[0020] Applicant desired to measure a user's respiration and ECG
signals at the user's wrist using a wrist-mounted device. For
Applicant, the circuit disclosed in the data sheet for the TI
ADS1292R was unsatisfactory for measuring a user's respiration at
this extremity because excessive electromagnetic interference (EMI)
resulted in noise in the demodulated signal. The noise was large
enough to cause errors in the determination of a user's respiration
rate. Applicant surmised that the ability of the human body to act
as an antenna contributed to the excessive EMI and that attempting
to measure respiration from an extremity (i.e., the wrist) further
exacerbated the EMI.
[0021] Embodiments within disclose improved systems and methods for
measuring respiration that are suitable for measuring respiration
at the user's extremities. The embodiments are discussed using the
Texas Instruments ADS1292R processor, but the ADS1292R is an
exemplary electronics device and the systems and methods disclosed
within may be practiced using other processors, processor sets,
circuitry (both digital and analog), or combinations of these.
Thus, "processing electronics" may include one or more processors,
processor sets, circuitry (both digital and analog), or
combinations of these. The improvements may include one or more of
the following: 1) providing user-excitation contacts for the AC
modulation signals where the user-excitation contacts are separate
and distinct from user impedance-measuring contacts; 2) adding a
low-pass filter between each user impedance-measuring contact and
the respective input into the processing electronics; 3) adding a
capacitance between the inputs into the processing electronics; 4)
filtering a digital impedance signal within the processing
electronics to remove a DC component; 5) filtering the digital
impedance signal within the processing electronics with a low-pass
filter to remove further noise; and 6) creating long and short
running averages of the impedance signal and, from these,
determining that the user is inhaling when the short running
average is greater than the long running average and that the user
is exhaling when the short running average is less than the long
running average.
[0022] FIG. 2 and FIG. 3 are circuit diagrams illustrating aspects
of an embodiment of a system for measuring a user's respiration
from extremities. FIG. 2 illustrates an embodiment of a modulation
circuitry 200, which provides user-excitation contacts for the AC
modulation signals that are separate and distinct from user
impedance-measuring contacts that are wired into the respiration
channel of processing electronics 201. It was determined that
providing contacts for the AC-modulation signals that are separate
from the impedance-measuring contacts, by itself, significantly
reduced noise (e.g., due to EMI) in the impedance measurement. In
FIG. 2, modulation circuitry 200 includes a first user-excitation
contact (RL) 202 coupled to a respiration modulation excitation
signal source 206 from electronics 201 (e.g., a TI ADS1292R)
through a capacitance and a resistance 218. In an embodiment the
capacitance includes a first capacitor 210 and a second capacitor
214. In FIG. 2, a second user-excitation contact (LL) 204 is
coupled to a respiration modulation excitation signal source 208
through a capacitance and a resistance 220. In an embodiment the
capacitance includes a first capacitor 212 and a second capacitor
216. In the embodiment of FIG. 2, to provide AC modulation signals
that result in an impedance across the user's chest,
user-excitation contacts 202 and 204 are placed in contact with the
skin of a user and on either side of the user's chest. In an
embodiment, a contact may be made, e.g., at each wrist of the user,
or at one wrist and a finger of the opposing arm. Exemplary
modulation frequencies for the user-excitation signals include 32
kHz and 64 kHz. In an embodiment, resistances 218, 220 may be 40
k.OMEGA., capacitors 210, 212 may be 100 nF, and capacitors 214,
216 may be 2200 pF.
[0023] FIG. 3 is a circuit diagram further illustrating aspects of
the embodiment of a system for measuring a user's respiration from
extremities of FIG. 2. FIG. 3 illustrates circuitry 300, which
includes circuitry for measuring the impedance of a user at
extremities using a first user-extremity contact 302 and a second
user-extremity contact 304. In the embodiment of FIG. 3, to measure
the impedance that results from the AC modulation signals across
the user's chest, user-extremity contacts 302 and 304 are placed in
contact with the skin of the user and on either side of the user's
chest. In an embodiment, a contact may be made, e.g., at each wrist
of the user, or at one wrist and a finger of the opposing arm. FIG.
3 further illustrates that modulation circuitry 200 is completely
separate and distinct from the impedance-measuring circuitry
between user contacts 302, 304 up to electronics 201. In FIG. 3,
for measuring impedance, user-extremity contact 302 is coupled to
an impedance-measuring input 310 to electronics 201. In this
particular embodiment, input 310 is differential analog negative
input 1 to the TI ADS1292R. Second user-extremity contact 304 is
coupled to a second input 312 to electronics 201. In this
particular embodiment, input 312 is differential analog positive
input 1 to the TI ADS1292R. Between contact 302 and input 310 the
circuitry further includes a capacitance, voltage biasing
circuitry, and a low-pass filter 318. In this particular
embodiment, the capacitance includes two capacitors 342, 344. The
voltage biasing circuitry includes two resistors 350, 352, each
coupled at one end between the capacitance and low-pass filter 318,
with resistor 350 coupled to an analog supply voltage 340 and
resistor 352 coupled to an analog ground 338. And low-pass filter
318 includes a resistor 330 coupled between the voltage biasing
circuitry and input 310 and includes a capacitor 332 coupled
between resistor 330 and input 310 at one end and to ground 338 at
the other. Between contact 304 and input 312 the circuitry mimics
that between contact 302 and input 310, further including a
capacitance, voltage biasing circuitry, and a low-pass filter 320.
In this particular embodiment, the capacitance includes two
capacitors 346, 348. The voltage biasing circuitry includes two
resistors 354, 356, each coupled at one end between the capacitance
and low-pass filter 320, with resistor 354 coupled to an analog
supply voltage 340 and resistor 356 coupled to an analog ground
338. And low-pass filter 320 includes a resistor 334 coupled
between the voltage biasing circuitry and input 312 and includes a
capacitor 336 coupled between resistor 334 and input 312 at one end
and to ground 338 at the other.
[0024] In the embodiment of FIG. 3, the series capacitance (e.g.,
capacitors 342, 344 and 346, 348) prevents a potential DC current
being applied to the user, with the redundancy of two capacitors
protecting against the short-circuiting of one of the capacitors.
The voltage-biasing circuitry establishes a pre-determined voltage
between the two resistors (e.g., between resistors 350 and 352 and
between resistors 354 and 356) that, in this embodiment, is
half-way between analog ground 338 and analog supply voltage 340.
Low-pass filters (e.g., low-pass filter 318 and 320) reduce EMI
significantly, which contributes to the ability of the embodiment
to measure a user's respiration when user-contacts 302, 304 are
placed on the user's extremities. Embodiments may further include a
capacitance between the impedance-sensing inputs to the electronics
that is sized to reduce DC noise. In FIG. 3, such a capacitance is
represented by a capacitor 358 coupled between inputs 310 and
312.
[0025] In an embodiment, the elements of circuit 300 may have the
following values: capacitors 342, 346 may be 100 nF; capacitors
344, 348 may be 2200 pF; resistors 350, 352, 354, 356 may be 10
M.OMEGA.; resistors 330, 334 may be 220 k.OMEGA.; capacitors 332,
336 may be 22 pF; and capacitor 358 may be 10 pF.
[0026] Thus, in the specific embodiment of FIG. 3, low-pass filters
318, 320 have cut-off frequencies 32.9 kHz. In other embodiments,
low-pass filters 318, 320 may have other cut-off frequencies and
still reduce EMI sufficiently to allow measuring a user's
respiration at extremities. In general, the cut-off frequencies of
low-pass filters 318, 320 are chosen to narrow the band that must
be filtered later by digital filters within electronics 201. By
narrowing the band, digital filters with better response may be
chosen. In an embodiment, the cut-off frequencies may be between
thirty and thirty-five kilohertz. Thus, in an embodiment, low-pass
filters 318, 320 work in combination with signal-processing logic
within electronics 201 to even further reduce EMI because low-pass
filters 318, 320 may have cut-off frequencies determined to work
synergistically with signal-processing logic within electronics
201. In an embodiment, low-pass filters 318, 320 have cut-off
frequencies chosen to reduce relatively high-frequency EMI, e.g.,
EMI frequencies of from 100 kHz to 1000 kHz, and the digital
filtering discussed within is directed to filtering out
substantially lower frequencies, e.g., with cutoff frequencies of
from 0.4 Hz to 20 Hz. The hardware low-pass filters 318, 320 filter
out most of the noise that comes from the user's body to the
circuit and the digital filters within electronics 201 may then be
optimized (e.g., with filters that have improved response times) to
address board noise of substantially lower frequencies, primarily
24 Hz and 60 Hz. The two different low pass filtering systems work
together to provide a usable respiration signal. Further smoothing
of that signal is applied digitally as discussed within, e.g.,
regarding FIGS. 4-7.
[0027] FIG. 3 further illustrates an embodiment of a system for
measuring a user's ECG at extremities. For reasons that are similar
to those when measuring respiration at extremities, measuring a
user's ECG at extremities suffers from increased EMI. In FIG. 3,
circuitry 300 illustrates an embodiment of ECG-measuring circuitry
for measuring the impedance of a user at extremities using first
user-extremity contact 302 and second user-extremity contact 304
when user contacts 302, 304 are placed in contact with the skin of
the user and on either side of the user's chest, e.g., at each
wrist of the user, or at one wrist and a finger of the opposing
arm. In FIG. 3, for measuring a user's ECG, a low-pass filter 314
is coupled between user-extremity contact 302 and an input 306 to
electronics 201. In this particular embodiment, input 306 is
differential analog negative input 2 to the TI ADS1292R chip.
Low-pass filter 314 includes a resistor 322 coupled between user
contact 302 and input 306 and includes a capacitor 324 coupled
between resistor 322 and input 306 at one end and to ground 338 at
the other. Between contact 304 and input 308 the circuitry mimics
that between contact 302 and input 306, with low-pass filter 316
including a resistor 326 coupled between user contact 304 and input
308 and includes a capacitor 328 coupled between resistor 326 and
input 308 at one end and to ground 338 at the other. In an
embodiment, low-pass filters 314, 316 have cutoff frequencies that
are chosen for anti-aliasing the signals to inputs 306, 308, which
means their cutoff frequencies are substantially higher than those
of low-pass filters 318, 320. For example, in an embodiment, the
cutoff frequencies of low-pass filters 314, 316 may be 60,000
Hz.
[0028] In the embodiment of FIG. 2 and FIG. 3, electronics 201
includes instructions, which, when contacts 202, 204, 302, 304 are
in contact with a user, cause electronics 201 to determine the
impedance between user extremity contacts 302 and 304 and measure
the user's respiration rate. The instructions are further discussed
regarding FIGS. 4-7.
[0029] In an embodiment, electronics 201 may include a first
processor and a second processor. In the embodiment, the first
processor includes electronics contacts 206, 208, 310, 312. The
first processor creates a digital impedance signal corresponding to
analog impedance data from user contacts 302, 304 and provides the
digital impedance signal to the second processor for subsequent
digital signal processing. In an embodiment, the first processor
may be a TI ADS1292R analog-to-digital converter and the second
processor may be an Arm Cortex M4.
[0030] FIG. 4 illustrates an embodiment of a method 400 for
measuring a user's respiration from an extremity of the user. In
the embodiment, method 400 is performed with first and second user
contacts on opposing sides of the user's chest and the third and
fourth user contacts also on opposing sides of the user's chest. In
method 400, at step 410, an AC current is provided between first
and second user contacts, causing an impedance to develop between
third and the fourth user contacts. In an embodiment, the contacts
may be at a user's extremity, e.g., a user's wrist, or a user's
finger. In step 412, the impedance is detected between the third
and the fourth user contacts, the impedance changing with time due
to the respiration of the user. In step 414, based on the detected
change of the impedance with time, a signal is created that may be
used to indicate the respiration rate of the user. The signal is
created, in part, by demodulating the detected impedance to
separate the contribution from the user's respiration from the
contribution from the AC modulation signal. In step 416, at least
one step from the following steps may be performed: the signal is
stored in memory; the signal is displayed with an electronic
device, and the signal is provided to a processor for further
processing.
[0031] It was determined that the impedance measurement of method
400 is improved (i.e., has less noise) when performed using the
embodiments of the system described regarding FIG. 2 and FIG. 3.
Thus, in an embodiment, steps 410-416 may be performed using an
embodiment of a system described in FIG. 2 and FIG. 3, with the
embodiment providing a signal indicating a respiration rate of the
user and benefitting from noise-reduction contributions provided by
embodiments of the system described regarding FIG. 2 and FIG.
3.
[0032] FIG. 4 indicates additional steps, one or more of which may
be added between steps 412 and 414 to assist in creating the signal
that may be used to indicate the respiration rate of the user. In
step 418, an impedance signal may be created from the impedance
detected in step 412 between the third and the fourth user
contacts. In step 420, the impedance signal may be filtered to
remove a DC component, which was determined to exist even after
demodulation. In an embodiment, the filtering to remove a DC
component may use a digital filter. In an embodiment, the digital
filter may be an infinite impulse response (IIR) filter for DC
current with a filtering constant of 0.992. In step 422, the
impedance signal may be filtered through a low-pass filter, e.g.,
to further remove EMI. In an embodiment, the low-pass filter may be
a digital filter. In an embodiment, the digital low-pass filter may
be a finite impulse response (FIR) low-pass filter. In an
embodiment, the filter is chosen to permit frequencies associated
with breathing rates, including the particularly desired (or
"targeted") breathing rates. In an embodiment, the FIR may be a
179.sup.th order filter with a gain of 1 with 5 dB from 0 to 0.5 Hz
and a gain of 0 from 3 Hz and above and with -40 dB attenuation. In
an embodiment, the FIR may be a 179.sup.th order filter with a gain
of 1 with 5 dB from 0 to 2 Hz and a gain of 0 from 3 Hz and above
and with -40 dB attenuation. In an embodiment, the impedance signal
may be filtered by a band-pass filter. In an embodiment, the
band-pass filter may be a digital filter. In an embodiment, the
digital band-pass filter may be a combination of the IIR filter for
DC current and the FIR low-pass filter.
[0033] It was determined that steps 420, 422 are effective in
reducing noise in the impedance measurement, both individually and
in combination. Thus, in embodiments, one or both of steps 420, 422
may be performed with steps 410-416 to provide a signal indicating
a respiration rate of the user and benefitting from noise-reduction
contribution from each added step.
[0034] It was also determined that the benefits in reduced noise
provided by steps 420, 422 were additive to the improvements
provided using the embodiments of the system described regarding
FIG. 2 and FIG. 3. Thus, in an embodiment, steps 410-416 may be
performed using an embodiment of a system described in FIG. 2 and
FIG. 3, with the embodiment of method and system providing a signal
indicating a respiration rate of the user and benefitting from the
noise-reduction contributions of step 420 or step 422 or both.
[0035] FIG. 5 illustrates an embodiment of a method 500 for
measuring a user's respiration from extremities. In FIG. 500
describes steps that may be performed on an impedance signal
created from the detected impedance between the third and fourth
user contacts (as in any of the signals created in steps 412, 418,
420, or 422, before they are provided to step 414) from which a
signal indicting a respiration rate of the user is created as in
step 414. In step 502, from an impedance signal created from the
time-varying impedance detected between the third and fourth user
contacts, a first running average is created over a first running
period of time. In step 504, from the same impedance signal of step
502, a second running average is created from a second running
period of time, where the second running period of time is
substantially shorter than the first running period of time. In
step 506, the first and second running averages are compared and if
the second running average is greater than the first, it is
determined that the user is inhaling. Conversely, in step 508, if
the second running average is less that the first, it is determined
that the user is exhaling. In step 510, the durations of time
between the determinations of when the user is inhaling and
exhaling are used to create the signal indicating the respiration
rate of the user.
[0036] In the embodiment of FIG. 5, the longer running average is
taken over a period of time with a duration sufficient to determine
the average impedance of at least one entire wave, i.e., an entire
respiration cycle. This effectively provides the center amplitude
of the wave (or the "baseline"). Thus, taking the longer running
average is a form of a DC component filtering over and above the
IIR filter mentioned earlier. In the embodiment, the shorter
running average is taken over a period of time with a duration that
reduces noise without filtering out the impedance change caused by
the user's respiration. In an embodiment, the shorter running
average is taken over a 2-second window and the longer running
average is taken over an 11-second window. The shorter running
average is also a form of filtering that is over and above the FIR
filter mentioned earlier.
[0037] In embodiments, the methods discussed regarding FIG. 4, or
FIG. 5, or both, may be performed by embodiments of systems
discussed regarding FIG. 2 and FIG. 3. In embodiments, the methods
of FIG. 4 and FIG. 5 may be performed by electronics 201 where
electronics 201 includes a first processor and a second processor.
In these embodiments, the first processor includes electronics
contacts 206, 208, 310, 312. The first processor creates a digital
impedance signal corresponding to analog impedance data from user
contacts 302, 304 and provides the digital impedance signal to the
second processor for subsequent digital signal processing. In an
embodiment, the first processor may be a TI ADS1292R
analog-to-digital converter and the second processor may be an Arm
Cortex M4.
[0038] In an embodiment, the filtering power of low-pass filters
318, 320 is increased (or the filtering is "front loaded"), which
allows the digital filtering described regarding FIG. 4 and FIG. 5
to be fine-tuned and directed to the remaining noise, thus
enhancing the overall noise-reducing effect of the embodiment over
changes to just the circuits 200, 300 or to just the methods 400,
500.
[0039] FIG. 6 illustrates an embodiment of a method 600 for
measuring the respiration of a user. The embodiment of FIG. 6 is
directed to processing that may be performed on a digital signal
created from the changes in impedance caused by a user's
respiration, e.g., a digital signal created from the impedance from
step 412 of method 400, or a digital impedance signal created by
electronics 201 and further processed by software within
electronics 201. In FIG. 6, in step 602, a data point indicative of
an impedance is received (or taken) at a pre-determined frequency,
e.g., every 2 ms (i.e., the sampling rate is 500 Hz). In step 604,
a pre-determined number of data points are summed, e.g., 10 data
points may be summed. In step 606, after the data points are
summed, a filter is implemented that produces a filtered data point
at a predetermined frequency, e.g., every 20 ms (i.e., 50 Hz). In
step 608, a single-order IIR filtering is performed on the data
from step 606 to reduce DC noise. In an embodiment, this IIR filter
is an IIR filter from Texas Instruments included with the TI
ADS1292R digital-to-analog converter. In step, 610, the data stream
from step 608 is further filtered using a low-pass FIR filter,
e.g., a 179.sup.th-order low-pass FIR filter with a cut-off
frequency of 0.4 Hz. With the data being sampled at a sufficiently
high frequency, e.g., 50 Hz, an FIR filter may be employed with
such a low cut-off frequency without the number of taps being too
large for the processor to accommodate (i.e., a lower-order FIR
filter). In step 612, a running average, e.g., a 10-sample running
average, is used to smooth the output from the FIR filter and
prepare the data for a differentiation filter. In step 614, the
data is filtered with a differentiation filter, e.g., a
5.sup.th-order differentiation filter, which removes high-frequency
components from the data. If the output of step 614 is larger than
0, then the user is determined to be inhaling. Otherwise the user
is exhaling. In step 616, the data is integrated using a moving
window integrator with, e.g., a 50-sample window, which at this
sampling rate is 1 second of data. The output of step 616 may be
used to compare the phase angle of the user's respiration with a
target respiration. In an embodiment, the user's respiration rate
may be determined using the time between zero-transitions with the
data from step 614. In an embodiment, the determined user
respiration rate may be compared to the changes in the user's HRV
to determine whether the user's HRV is in synchrony with the user's
respiration (i.e., whether the user is in RSA). In an embodiment,
the signal from step 412 may be processed as described in steps
608-614 with the resulting signal supplied to step 414. In an
embodiment, the signal from step 412 may be processed as described
in steps 602-614 with the resulting signal supplied to step
414.
[0040] FIG. 7 illustrates an embodiment of a method 700 for
measuring the respiration of a user that corrects for (or "cancels
out") skewing that might be induced due the user's skin varying in
a level of moistness while respiration is being measured. Method
700 builds on method 600. In step 702, the zeroes in the
differentiation-filtered output of step 614 are used to find the
local minimums and maximums of the user's respiration. In step 704,
a running average is created from the local minimums and a running
average is created from the local maximums. In step 706, the output
of step 614 is rescaled by dividing positive values by the running
average of the local maximums and by dividing negative values by
the running average of the local minimums. The result of step 706
is that the respiration data will be a scaled wave that ranges from
-1 to 1, where positive values indicate the user is inhaling and
negative values indicate the user is exhaling. With the respiration
data being maintained between -1 and 1, the skew is eliminated. In
an embodiment, the running average of step 704 is constructed using
the last ten (10) local minimums and last ten (10) local
maximums.
[0041] FIG. 8 is a simplified, exemplary block diagram of an
embodiment of a system 800 for implementing the embodiments of
systems and methods disclosed herein. System 800 may include a
number of sensors, e.g., a respiration rate sensor 805 (e.g., as
described within this disclosure) and a heart rate sensor 810
(e.g., as described within this disclosure), for developing data
regarding a user. Sensors 805, 810, and 820 are in communication
with a computing device 815. Computing device 815 may further be in
control of a haptic device 825 and a buzzer or speaker (not shown)
for communicating with the user. System 800 may be referred to as a
Biometric Analysis Device.
[0042] Respiration rate sensor 805 may be an impedance-based sensor
as discussed within this specification. Heart rate sensor 810 may
be, e.g., a plurality of sensors sufficient to produce an
electrocardiogram (ECG, as discussed within), a chest-mounted
device, or a wrist-mounted device, so long as the device provides
heart rate data with sufficient accuracy and precision. Sensor 820
is representative of additional sensors that may be included, such
as sensors for determining galvanic skin response, temperature,
blood pressure, hydration, sleep, exercise activity, brain
activity, nutrient levels, or blood analysis. Sensors 805, 810, and
820 may supply data to computing device 815 via communication links
830.
[0043] Computing device 815 may include a user interface and
software, which may implement the steps of the methods disclosed
within. Computing device 815 may receive data from sensors 805,
810, and 820, via communication links 830, which may be hardwire
links, optical links, satellite or other wireless communications
links, wave propagation links, or any other mechanisms for
communication of information. Various communication protocols may
be used to facilitate communication between the various components
shown in FIG. 8. Distributed system 800 in FIG. 8 is merely
illustrative of an embodiment and does not limit the scope of the
systems and methods as recited in the claims. In an embodiment, the
elements of system 800 are incorporated into a single, wearable
Biometric Analysis Device (e.g., as described regarding FIGS. 10
and 11). One of ordinary skill in the art would recognize other
variations, modifications, and alternatives. For example, more than
one computing device 815 may be employed. As another example,
sensors 805, 810, and 820 may be coupled to computing device 815
via a communication network (not shown) or via some other server
system.
[0044] Computing device 815 may be responsible for receiving data
from sensors 805, 810, and 820, performing processing required to
implement the steps of the methods, and for interfacing with the
user. In some embodiments, computing device 815 may receive
processed data from sensors 805, 810, and 820. In some embodiments,
the processing required is performed by computing device 815. In
such embodiments, computing device 815 runs an application for
receiving user data, performing the steps of the method, and
interacting with the user. In other embodiments, computing device
815 may be in communication with a server, which performs the
required processing, with computing device 815 being an
intermediary in communications between the user and the processing
server.
[0045] System 800 enables users to access and query information
developed by the disclosed methods. Some example computing devices
815 include desktop computers, portable electronic devices (e.g.,
mobile communication devices, smartphones, tablet computers,
laptops) such as the Samsung Galaxy Tab.RTM., Google Nexus devices,
Amazon Kindle.RTM., Kindle Fire.RTM., Apple iPhone.RTM., the Apple
iPad.RTM., Microsoft Surface.RTM., the Palm Pre.TM., or any device
running the Apple iOS.RTM., Android.RTM. OS, Google Chrome.RTM. OS,
Symbian OS.RTM., Windows Mobile.RTM. OS, Windows Phone,
BlackBerry.RTM. OS, Embedded Linux, Tizen, Sailfish, webOS, Palm
OS.RTM. or Palm Web OS.RTM.; or wearable devices such as smart
watches, smart fitness or medical bands, and smart glasses.
[0046] FIG. 9 is an exemplary block diagram of a computing device
815 from the system of FIG. 8. In an embodiment, a user interfaces
with the system through computing device 815, which also receives
data and performs the computational steps of the embodiments.
Computing device 815 may include a display, screen, or monitor 905,
housing 910, input device 915, sensors 950, and a security
application 945. Housing 910 houses familiar computer components,
some of which are not shown, such as a processor 920, memory 925,
battery 930, speaker, transceiver, antenna 935, microphone, ports,
jacks, connectors, camera, input/output (I/O) controller, display
adapter, network interface, mass storage devices 940, and the like.
In an embodiment, sensors 950 may include sensors 805, 810, and 820
incorporated into computing device 815, and haptic device 825 may
also be incorporated into device 815. In an embodiment, housing 910
is the housing of the wearable biometric analysis device 1000 of
FIGS. 10 and 11.
[0047] Input device 915 may also include a touchscreen (e.g.,
resistive, surface acoustic wave, capacitive sensing, infrared,
optical imaging, dispersive signal, or acoustic pulse recognition),
keyboard (e.g., electronic keyboard or physical keyboard), buttons,
switches, stylus, or combinations of these.
[0048] Display 904 may include dedicated LEDs for providing
directing signals and feedback to a user.
[0049] Mass storage devices 940 may include flash and other
nonvolatile solid-state storage or solid-state drive (SSD), such as
a flash drive, flash memory, or USB flash drive. Other examples of
mass storage include mass disk drives, floppy disks, magnetic
disks, optical disks, magneto-optical disks, fixed disks, hard
disks, CD-ROMs, recordable CDs, DVDs, recordable DVDs (e.g., DVD-R,
DVD+R, DVD-RW, DVD+RW, HD-DVD, or Blu-ray Disc), battery-backed-up
volatile memory, tape storage, reader, and other similar media, and
combinations of these.
[0050] System 900 may also be used with computer systems having
configurations that are different from computing device 815, e.g.,
with additional or fewer subsystems. For example, a computer system
could include more than one processor (i.e., a multiprocessor
system, which may permit parallel processing of information) or a
system may include a cache memory. The computing device 815 shown
in FIG. 9 is but an example of a computer system suitable for use.
For example, in a specific implementation, computing device 815 is
a wrist-mounted Biometric Analysis Device in communication with or
incorporating the sensors of FIG. 9. An example of such a Biometric
Analysis Device is discussed regarding device 1000 of FIGS. 10 and
11. Other configurations of subsystems suitable for use will be
readily apparent to one of ordinary skill in the art. In other
specific implementations, computing device 815 is a mobile
communication device such as a smartphone or tablet computer. Some
specific examples of smartphones include the Droid Incredible and
Google Nexus One.RTM., provided by HTC Corporation, the iPhone.RTM.
or iPad.RTM., both provided by Apple, BlackBerry Z10 provided by
BlackBerry (formerly Research In Motion), and many others. The
Biometric Analysis Device may be a laptop or a netbook. In another
specific implementation, the Biometric Analysis Device is a
non-portable computing device such as a desktop computer or
workstation.
[0051] In an embodiment, system 900 may be incorporated into a
single module. The module may have four user contacts (or
"electrodes") placed to allow a user to make contact with two
contacts with one user extremity and with the other two contacts
with the other user extremity. This module can be contained within
numerous types of wristband straps (leather, etc.) and form factors
(such as key chain, steering wheel cover, etc.). The module, or the
strap or other form factor, may also include a small OLED display
to display the current time. The module may execute software that
performs an embodiment of the method. Accordingly, the module may
provide the user with feedback, e.g., an indication of the user's
respiration rate or heart rate or both.
[0052] FIG. 10 includes front, back, top, bottom, and right views
of an embodiment of a wearable biometric analysis device 1000 for
implementing embodiments of the methods disclosed within.
Components and capabilities of biometric analysis device 1000 are
also described with reference to FIGS. 2-9. Biometric Analysis
Device 1000 includes a computing device 1005 and a sensor coupled
to electrical contacts 1010, 1012, 1014, 1016 that acquire data
that may be used to provide a measure of the user's respiration
rate as discussed above. Computing device 1005 processes biometric
data measured by the sensor(s) and produces feedback correlating to
the processed biometric data. By continuously monitoring one or
more biometric values, the user may respond to the data received
and modify their behavior or activity to improve health and
performance. The biometric analysis device 1000 thereby provides
feedback by sensing and reporting a biometric value measured by the
sensor to the user in real time. In an embodiment, contacts 1010,
1012, 1014, 1016 provide data to a TI ADS1292R sensor. As such,
Biometric Analysis Device 1000 may be equipped with both a
respiration rate sensor and a heart rate sensor. Computing device
1005 is in communication with the sensor or sensors associated with
contacts 1010, 1012, 1014, 1016. Computing device 1005 may also
control a haptic device (not shown) for communicating with the
user. Computing device 1005 may include a display 1015, a user
interface, and software, for implementing the steps of the methods
disclosed within. In an embodiment, contacts 1010 and 1012 may
correspond to contacts 202 and 302 as described above, and contacts
1014 and 1016 may correspond to contacts 204 and 304 as described
above. In the embodiment, a method for determining the user's
respiration rate includes the user placing device 1000 on one of
the user's wrists such that contacts 1010, 1012 are in contact with
the user's wrist. Then, the user brings contacts 1014, 1016 in
contact with another part of the user's body such as one or more
fingers on the user's opposing hand. In other words, the user
touches contacts 1014, 1016 to a part of the user's body so that
some or all of the user's chest is between contact pairs 1010, 1012
and 1014, 1016 (the circuits are described with reference to FIGS.
2 and 3 and contact pairs 202, 302 and 204, 304). In an embodiment,
the part of the user's body may be a finger or other part of the
opposing arm, may be a section of the user's torso, or may be a
section of a leg of the user. With both contact pairs 1010, 1012
and 1014, 1016 in such contact with the user, the device then
determines the user's respiration rate, heart rate, or both
according to the methods described within.
[0053] Computing device 1005 may receive data from sensors 1010,
1012, 1014, 1016, perform processing required to implement the
steps of the methods disclosed within, and provide a user interface
via display 1015. In some embodiments, all processing required is
performed by computing device 1005. In such embodiments, computing
device 1005 executes instructions for receiving user data,
performing the steps of the method, and interacting with the user.
In other embodiments, computing device 1005 may be in communication
with a server, which performs part of the required processing, with
computing device 1005 being an intermediary in communications
between the user and the processing server.
[0054] As illustrated, Biometric Analysis Device 1000 generally
comprises a band 1020 configured to be worn about a wrist of the
user. The band 1020 includes an adjustment mechanism 1025, for
adjusting a circumference of the band 1020. A user can thus select,
using adjustment mechanism 1025, a particular size for positioning
band 1020 about the user's wrist. A visual indication, e.g., for
feedback, may be provided by display 1015. In an embodiment, visual
indicators may be further be positioned on the band 1020 to provide
visual signals to the user. Sensor(s) associated with contacts
1010, 1012, 1014, 1016 may be configured to be activated by
computing device 1005. In an embodiment, additional sensors, e.g.,
a temperature sensor or a galvanic response sensor, may be provided
to provide more user data for determining vagal tone. In an
embodiment, one or more translucent windows may be positioned about
the band 1020 to transmit light from one or more indicators
positioned with the band 1020.
[0055] Biometric analysis device 1000, in one embodiment, is used
measure a user's respiration rate. Accordingly, the biometric
analysis device 1000 may provide the user with real-time, personal
biofeedback. In an embodiment, device 1000 may measure both a
user's respiration rate and heart rate and provide feedback
regarding one or both. The biofeedback may allow the user to learn
about the user's personal physiological state and physiological
responses. As a result, the biofeedback provided to the user (by,
e.g., one or more of display 1015, or haptic device, or speaker)
may enable the user to self-regulate the user's activity and
behavior to improve the user's performance or health. In an
embodiment, device 1000 may provide a user with feedback (e.g., a
vibration pattern of frequency, duration, and magnitude) selected
to encourage a desired behavior. In an embodiment, biometric
analysis device 1000 is configured to provide the user with
feedback with reference to previously-collected biometric data,
such as respiration rate or heart rate variability. The biometric
analysis device 1000 may emit vibrations based on the user's actual
respiration rate, or a target respiration rate. For example, a
visual indication from, e.g., display 1015, may be provided and
configured to emit different colors based on when the user is
supposed to inhale and exhale for deep breathing relaxation
techniques. The user may also be capable of changing the breathing
intervals. The visual indication and breathing intervals may be
enabled and adjusted through the user interface.
[0056] FIG. 11 is a perspective view of the biometric analysis
device of FIG. 10.
[0057] FIGS. 10 and 11 illustrate one example embodiment of a
wearable biometric analysis device 1000 that is configured to
measure the respiration rate of a user. In one embodiment,
biometric analysis device 1000 can include each of the elements of
system 800 of FIG. 8 and FIG. 9. In other embodiments, biometric
analysis device 1000 can include other elements that function with
biometric analysis device 1000 to provide biometric measurement and
analysis to assist a user with stress management.
[0058] In the description above and throughout, numerous specific
details are set forth in order to provide a thorough understanding
of an embodiment of this disclosure. It will be evident, however,
to one of ordinary skill in the art, that an embodiment may be
practiced without these specific details. In other instances,
well-known structures and devices are shown in block diagram form
to facilitate explanation. The description of the preferred
embodiments is not intended to limit the scope of the claims
appended hereto. Further, in the methods disclosed herein, various
steps are disclosed illustrating some of the functions of an
embodiment. These steps are merely examples and are not meant to be
limiting in any way. Other steps and functions may be contemplated
without departing from this disclosure or the scope of an
embodiment.
* * * * *