IP Library › Granted Patent US 12,667,314
Granted Patent B2
US 12,667,314 · App. 17/853,083 · Granted Jun 30, 2026

System and method to detect changes in health parameters and activate lifesaving measures

Inventor: Robert Sampson (Stony Brook, NY)
Assignee: SHERLOCK SOLUTIONS LLC
A61B5/721A61B5/0022A61B5/0205A61B5/0261A61B5/14551A61B5/282A61B5/6803A61B5/681A61B5/7221A61B5/7264A61B5/7275A61B5/7282A61B5/746A61B5/7475G16H40/63A61B5/02438A61B5/366A61B5/7203A61B2560/0228
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Quick Facts
Patent No.
US 12,667,314
App. No.
17/853,083
Filed
Jun 29, 2022
Granted
Jun 30, 2026
Kind
B2
Art Unit
3792
USPC
600/301
Abstract

Certain exemplary embodiments can provide an apparatus wearable by a user. The apparatus can comprise a biometric sensor constructed to generate signals based upon measurements of the user. The apparatus can comprise a processor constructed to determine a significant detrimental change in the user via an algorithm based upon the signals.

Claims (50)

1 . A system comprising:

a commonly worn object capable of being worn by a user, said commonly worn object including a biometric sensor calibrated based on a physically-measured value of said user measured during a calibration period, said biometric sensor configured to measure biometric data from said user and generate one or more signals based on said biometric data, said biometric sensor is situationally calibratable based on user activity;

a transmitter housed in said commonly worn object and in communication with said biometric sensor, said transmitter configured to transmit said one or more signals from said biometric sensor; and

at least one processor configured to receive said one or more signals from said biometric sensor via said transmitter, said at least one processor configured to determine whether said user has experienced a change that is a physiological and detrimental change by comparing a plurality of snapshots of one or more health parameters of said user, said one or more health parameters generated based on said one or more signals, said at least one processor configured to notify at least one of said user or an emergency medical system when it is determined that said user has experienced said physiological and detrimental change.

2 . The system of claim 1 , wherein:

said at least one processor is configured to determine whether said change indicates said user has fallen.

3 . The system of claim 1 , wherein:

said change includes a confidence interval.

4 . The system of claim 1 , wherein:

said comparing of said plurality of snapshots includes comparing at least one of said plurality of snapshots to a standard snapshot.

5 . The system of claim 1 , wherein:

said biometric sensor is situationally calibrated upon detection of said movement of said user consistent with a physical activity, and

said detection of said movement is performed via an accelerometer or a gyroscope.

6 . The system of claim 1 , wherein:

said biometric sensor is calibratable by a response of said user to a request to position said biometric sensor on at least two different parts of a body of said user.

7 . The system of claim 1 , wherein:

said at least one processor is configured to relay information concerning said change to said commonly worn object.

8 . The system of claim 1 , wherein:

responsive to user signals from said user, said commonly worn object is configured to calibrate said biometric sensor based on demographical and medical information received from said user, wherein a calibration includes a determination of differences between a signal of said biometric sensor and a standard.

9 . The system of claim 1 , wherein:

said biometric sensor is a heart rate monitor.

10 . The system of claim 1 , wherein:

said biometric sensor is a laser Doppler flowmeter.

11 . The system of claim 1 , wherein:

said biometric sensor is a capacitive sensor with two electrodes mounted on said user.

12 . The system of claim 1 , wherein:

said commonly worn object is configured to prompt said user to submit past medical history.

13 . The system of claim 1 , wherein:

said one or more health parameters includes at least one of photoplethysmogram sensor data or electrocardiogram sensor data.

14 . The system of claim 1 , wherein:

said commonly worn object is configured to allow said user to cancel an information transmission to the emergency medical system.

15 . The system of claim 1 , further comprising:

a signal filter configured to average signals from said biometric sensor.

16 . The system of claim 1 , wherein:

said commonly worn object prompts said user for information responsive to information from said biometric sensor.

17 . The system of claim 1 , wherein:

said commonly worn object is a watch.

18 . The system of claim 1 , wherein:

said biometric sensor is situationally calibrated upon detection of a movement of said user consistent with a physical activity of said user,

said commonly worn object is configured to create a calibration profile for said one or more health parameters of said user based upon information from said biometric sensor,

said calibration profile configured for use in situationally calibrating said biometric sensor, and

said situationally calibrating enabling said at least one processor to distinguish between said physiological and detrimental change and a physiological and not detrimental change.

19 . A system comprising:

a commonly worn object capable of being worn by a user, said commonly worn object including a biometric sensor calibrated based on a physically-measured value of said user measured during a calibration period, said biometric sensor configured to measure biometric data from said user and generate one or more signals based on said biometric data, said biometric sensor is calibratable for a movement of said user consistent with a physical activity, and said detection of said movement is performed via an accelerometer or a gyroscope;

a transmitter housed in said commonly worn object and in communication with said biometric sensor, said transmitter configured to transmit said one or more signals from said biometric sensor; and

at least one processor configured to receive said one or more signals from said biometric sensor via said transmitter, said at least one processor configured to determine whether said user has experienced a change that is a physiological and detrimental change by comparing a plurality of snapshots of one or more health parameters of said user, said one or more health parameters generated based on said one or more signals, said at least one processor configured to notify at least one of said user or an emergency medical system when it is determined that said user has experienced said physiological and detrimental change.

20 . A system comprising:

a commonly worn object capable of being worn by a user, said commonly worn object including a biometric sensor calibrated based on a physically-measured value of said user measured during a calibration period, said biometric sensor configured to measure biometric data from said user and generate one or more signals based on said biometric data, said biometric sensor is calibratable for a movement of said user consistent with the user performing a type of physical activity;

a transmitter housed in said commonly worn object and in communication with said biometric sensor, said transmitter configured to transmit said one or more signals from said biometric sensor; and

at least one processor configured to receive said one or more signals from said biometric sensor via said transmitter, said at least one processor configured to determine whether said user has experienced a change that is a physiological and detrimental change by comparing a plurality of snapshots of one or more health parameters of said user, said one or more health parameters generated based on said one or more signals, said situationally calibrating enabling said at least one processor to distinguish between said physiological and detrimental change and a physiological and not detrimental change, and said at least one processor configured to notify at least one of said user or an emergency medical system when it is determined that said user has experienced said physiological and detrimental change.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 29, 2022
From: SAMPSON, ROBERT
To: SHERLOCK SOLUTIONS LLC
Reel/Frame 060355/0661 →
Continuity (4)
Continuation 16687344 · Nov 18, 2019
Continuation 14748230 · Jun 23, 2015
Provisional Application 62015844 · Jun 23, 2014
Related Publication 20220401035A1 · Dec 22, 2022
References Cited (91)
US 3832994A · Bicher et al. · 1974 [cited by applicant]
US 5351695A · Mills et al. · 1994 [cited by applicant]
US 5515858A · Myllymaki · 1996 [cited by applicant]
US 7869864B2 · Tseng et al. · 2011 [cited by applicant]
US 7894888B2 · Chan et al. · 2011 [cited by applicant]
US 8055331B2 · Satin et al. · 2011 [cited by applicant]
US 8332020B2 · Zdeblick · 2012 [cited by applicant]
US 8626274B2 · Chiu et al. · 2014 [cited by applicant]
US 8738118B2 · Moon et al. · 2014 [cited by applicant]
US 9041530B2 · Sprigg et al. · 2015 [cited by applicant]
US 9317110B2 · Lutnick et al. · 2016 [cited by applicant]
US 10051410B2 · Booth et al. · 2018 [cited by applicant]
US 10478127B2 · Sampson · 2019 [cited by applicant]
US 10534819B2 · Ricci · 2020 [cited by applicant]
US 20040130446A1 · Chen et al. · 2004 [cited by applicant]
US 20050116810A1 · Beenau et al. · 2005 [cited by applicant]
US 20060052983A1 · Vock et al. · 2006 [cited by applicant]
US 20060152373A1 · King · 2006 [cited by applicant]
US 20060161065A1 · Elion · 2006 [cited by applicant]
US 20060281996A1 · Kuo et al. · 2006 [cited by applicant]
US 20070116330A1 · Takiguchi · 2007 [cited by applicant]
US 20070276270A1 · Tran · 2007 [cited by applicant]
US 20080004904A1 · Tran · 2008 [cited by applicant]
US 20090048526A1 · Aarts et al. · 2009 [cited by applicant]
US 20090105558A1 · Riley-Doucet et al. · 2009 [cited by applicant]
US 20090131759A1 · Sims et al. · 2009 [cited by applicant]
US 20090322513A1 · Hwang et al. · 2009 [cited by applicant]
US 20100076331A1 · Chan et al. · 2010 [cited by applicant]
US 20100249542A1 · Thijs et al. · 2010 [cited by applicant]
US 20110004072A1 · Fletcher et al. · 2011 [cited by applicant]
US 20110066009A1 · Moon et al. · 2011 [cited by applicant]
US 20110066010A1 · Moon et al. · 2011 [cited by applicant]
US 20120002791A1 · Kraus et al. · 2012 [cited by applicant]
US 20120092157A1 · Tran · 2012 [cited by applicant]
US 20120150244A1 · Freeman et al. · 2012 [cited by applicant]
US 20120330109A1 · Tran · 2012 [cited by applicant]
US 20130009783A1 · Tran · 2013 [cited by applicant]
US 20130072807A1 · Tran · 2013 [cited by applicant]
US 20130083009A1 · Geisner et al. · 2013 [cited by applicant]
US 20130178755A1 · Waters · 2013 [cited by applicant]
US 20130211291A1 · Tran · 2013 [cited by applicant]
US 20130231574A1 · Tran · 2013 [cited by applicant]
US 20130231578A1 · Takayanagi et al. · 2013 [cited by applicant]
US 20130281816A1 · Strauss et al. · 2013 [cited by applicant]
US 20130307685A1 · Sholder · 2013 [cited by applicant]
US 20130345578A1 · Nadkarni et al. · 2013 [cited by applicant]
US 20140058280A1 · Chefles et al. · 2014 [cited by applicant]
US 20140077946A1 · Tran · 2014 [cited by applicant]
US 20140104059A1 · Tran · 2014 [cited by applicant]
US 20140107457A1 · Raghunathan · 2014 [cited by applicant]
US 20140142403A1 · Brumback et al. · 2014 [cited by applicant]
US 20140163425A1 · Tran · 2014 [cited by applicant]
US 20140247154A1 · Proud · 2014 [cited by applicant]
US 20140249429A1 · Tran · 2014 [cited by applicant]
US 20140277582A1 · Leuthardt et al. · 2014 [cited by applicant]
US 20140288391A1 · Hong et al. · 2014 [cited by applicant]
US 20140310186A1 · Ricci · 2014 [cited by applicant]
US 20150025394A1 · Hong et al. · 2015 [cited by applicant]
US 20150049114A1 · Geisner et al. · 2015 [cited by applicant]
US 20150068069A1 · Bach et al. · 2015 [cited by applicant]
US 20150094914A1 · Abreu · 2015 [cited by applicant]
US 20150257654A1 · Bennett-Guerrero · 2015 [cited by applicant]
US 20150279187A1 · Kranz · 2015 [cited by applicant]
US 20150285659A1 · Curtis et al. · 2015 [cited by applicant]
US 20150317515A1 · Lake et al. · 2015 [cited by applicant]
US 20150351698A1 · Cronin · 2015 [cited by applicant]
US 20150366518A1 · Sampson · 2015 [cited by applicant]
US 20160071392A1 · Hankey et al. · 2016 [cited by applicant]
US 20160071393A1 · Kaplan et al. · 2016 [cited by applicant]
US 20160093197A1 · See et al. · 2016 [cited by applicant]
US 20160292850A1 · Perez et al. · 2016 [cited by applicant]
US 20170066406A1 · Ricci · 2017 [cited by applicant]
US 20170116845A1 · See et al. · 2017 [cited by applicant]
US 20170150893A1 · McCombie et al. · 2017 [cited by applicant]
US 20170193705A1 · Mullins et al. · 2017 [cited by applicant]
US 20170347886A1 · Tran · 2017 [cited by applicant]
US 20180184907A1 · Tran · 2018 [cited by applicant]
US 20190038133A1 · Tran · 2019 [cited by applicant]
US 20190113973A1 · Coleman et al. · 2019 [cited by applicant]
US 20190192075A1 · Kranz · 2019 [cited by applicant]
US 20200077892A1 · Tran · 2020 [cited by applicant]
US 20200218350A1 · Coleman et al. · 2020 [cited by applicant]
US 20210186329A1 · Tran et al. · 2021 [cited by applicant]
KR 20130010207A · 2013 [cited by applicant]
WO 2013165474A1 · 2013 [cited by applicant]
Curone, et al. “Heart rate and accelerometer data fusion for activity assessment of rescuers during emergency interventions.” IEEE Transactions on Information Technology in Biomedicine 14.3 (2010): 702-710. [cited by applicant]
Curone, et al. “An activity classifier based on heart rate and accelerometer data fusion.” International Journal of Bioelectromagnetism 15.1 (2013): 7-12. [cited by applicant]
Sweeney, et al. “Identification of sleep apnea events using discrete wavelet transform of respiration, ecg and accelerometer signals.” 2013 IEEE International Conference on Body Sensor Networks. IEEE, 2013. [cited by applicant]
Das, et al. “A Smart and Wearable Cardiac Healthcare System with Monitoring of Sudden Fall for Elderly and Post-Operative Patients.” IOSR Journal of Computer Engineering 16.2 (2014): 126-133. [cited by applicant]
Kher, et al. An Investigation on Impact of Body Movement Activities on Wearable Ambulatory Electrocardiogram (A-ECG). Diss. Sardar Patel University. [cited by applicant]
Sun, X., et al. “Robust heart beat detection from photoplethysmography interlaced with motion artifacts based on empirical mode decomposition.” Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and He… [cited by applicant]