IP Library › Granted Patent US 12,702,326
Granted Patent B2
US 12,702,326 · App. 17/415,183 · Granted Aug 11, 2026

Stroke detection sensor

Inventors: Petter Ericson (Limhamn, SE); Johan Wasselius (Lund, SE); Karl Astrom (Lund, SE); Rikard Berthilsson (Furulund, SE)
Assignee: UMAN SENSE AB
A61B5/11A61B5/162A61B5/4064A61B5/4094A61B5/681A61B5/6824A61B5/6828A61B5/7275A61B5/747A61B5/7475G16H40/67
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,702,326
App. No.
17/415,183
Filed
Jun 17, 2021
Granted
Aug 11, 2026
Kind
B2
Art Unit
3791
USPC
600/595
Abstract

A stroke detection apparatus for determining that a stroke is occurring or has recently occurred to a user, wherein the apparatus comprises a data processing device comprising a processor and at least one wearable sensor configured to be worn by a user and configured to transmit a movement data of the user to the data processing device. The data processing device is configured to process the movement data to determine a first probability of a user stroke over a first time period and a second probability of a user stroke over a second time period. A stroke detection signal is then generated in dependence on at least the first probability and second probability.

Claims (37)

1 . A stroke detection apparatus comprising:

at least one wearable sensor configured to be worn by a user and configured to generate a movement data of the user, the at least one wearable sensor comprising,

a sensor package configured to measure an acceleration of the user,

a data processing device comprising a system memory, and

a power source configured to power the data processing device,

the sensor package configured to transmit the movement data to the data processing device, the data processing device configured to cause the stroke detection apparatus to:

receive the movement data,

filter the movement data to remove acceleration resulting from gravitational force,

process the movement data to determine a probability of a user stroke, the probability indicates a percentage chance of stroke occurrence, and

store the movement data on the system memory at a fidelity dependent on the probability of the user stroke,

wherein the fidelity of the stored movement data comprises at least one of a sample rate, a sample size, or a bit rate of the movement data,

wherein when the probability of the user stroke is determined to be below a first probability threshold, the stroke detection apparatus is further configured to

operate in a first mode where the movement data is stored at a first fidelity,

wherein when the probability of the user stroke is determined to be above the first probability threshold, the stroke detection apparatus is configured to

operate in a second mode where the movement data is stored at a second fidelity,

wherein the first probability threshold is a determined percentage chance of stroke occurrence, and

wherein the second fidelity is higher than the first fidelity, to reduce power consumption from the power source in the first mode.

2 . The stroke detection apparatus of claim 1 , wherein the stroke detection apparatus is configured to generate one or more user tests once a threshold for the probability of the user stroke has been exceeded, wherein the one or more user tests comprises at least one of a reaction time test, an arithmetic test, a reading test, a comprehension test, a memory test, or a user response test.

3 . The stroke detection apparatus of claim 2 , wherein the stroke detection apparatus is configured to generate a stroke escalation signal where the user fails the one or more of the user tests.

4 . The stroke detection apparatus according to claim 1 , wherein the stroke detection apparatus is configured to operate in the first mode wherein the processed movement data is limited to a single dimension, and

wherein the stroke detection apparatus is configured to

operate in the second mode wherein the processed movement data is 3-dimensional, and

determine the probability of the user stroke in dependence on the processed movement data according to the first mode and determine a user gesture in dependence on the processed movement data according to the second mode.

5 . The stroke detection apparatus according to claim 1 , wherein the stroke detection apparatus is configured to operate in a third mode when the stroke detection apparatus is monitoring the user for a specific movement.

6 . The stroke detection apparatus according to claim 5 , wherein the stroke detection apparatus is configured to operate in the third mode when the stroke detection apparatus has prompted the user to perform the specific movement in order to pass a test.

7 . The stroke detection apparatus according to claim 5 , wherein the movement data of the user from the at least one wearable sensor is stored at a third fidelity in the third mode, wherein the third fidelity is higher than a first fidelity and a second fidelity.

8 . A method for generating a stroke detection signal comprising:

generating, using at least one wearable sensor device configured to be worn by a user, a movement data of the user;

transmitting the movement data to a processing device being powered by a power source;

receiving the movement data at the processing device;

filtering the movement data to remove acceleration resulting from gravitational force;

processing the movement data at the processing device to determine a probability of a user stroke, the probability indicates a percentage chance of stroke occurrence, the method further comprising,

storing the movement data at a fidelity dependent on the probability of the user stroke, wherein the fidelity of the stored movement data comprises at least one of a sample rate, a sample size, or a bit rate;

in a first operating mode, storing the movement data at a first fidelity on a system memory of the data processing device when the probability of a user stroke is determined to be below a first threshold; and

in a second operating mode, storing the movement data at a second fidelity on the system memory when the probability of a user stroke is determined to be above the first threshold,

wherein the first probability threshold is a determined percentage chance of stroke occurrence, and

wherein the second fidelity is higher than the first fidelity, to reduce power consumption from the power source in the first operating mode.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 18, 2021
From: ERICSON, PETTER; WASSELIUS, JOHAN; ASTROM, KARL; BERTHILSSON, RIKARD
To: UMAN SENSE AB
Reel/Frame 056586/0888 →
Priority Claims (2)
GB 1820892 · Dec 20, 2018 · national
SE 193037-0 · Nov 12, 2019 · national
Continuity (1)
Related Publication 20220061738A1 · Mar 3, 2022
References Cited (128)
US 6301964B1 · Fyfe et al. · 2001 [cited by applicant]
US 6703939B2 · Lehrman et al. · 2004 [cited by applicant]
US 6836744B1 · Asphahani et al. · 2004 [cited by applicant]
US 7203541B2 · Sowelam et al. · 2007 [cited by applicant]
US 7421369B2 · Clarkson · 2008 [cited by applicant]
US 7503900B2 · Goswami · 2009 [cited by applicant]
US 7516038B2 · Lehtonen et al. · 2009 [cited by applicant]
US 7753861B1 · Kahn et al. · 2010 [cited by applicant]
US 7878990B2 · Al-Obaidi et al. · 2011 [cited by applicant]
US 7921716B2 · Morris Bamberg et al. · 2011 [cited by applicant]
US 7974689B2 · Volpe et al. · 2011 [cited by applicant]
US 7981058B2 · Akay · 2011 [cited by applicant]
US 8011229B2 · Lieberman et al. · 2011 [cited by applicant]
US 8032199B2 · Linti et al. · 2011 [cited by applicant]
US 8060337B2 · Kulach et al. · 2011 [cited by applicant]
US 8187209B1 · Giuffrida · 2012 [cited by applicant]
US 8204710B2 · Walthert · 2012 [cited by applicant]
US 8409116B2 · Wang et al. · 2013 [cited by applicant]
US 8608671B2 · Kinoshita et al. · 2013 [cited by applicant]
US 8715208B2 · Hodgins et al. · 2014 [cited by applicant]
US 8738118B2 · Moon et al. · 2014 [cited by applicant]
US 8801636B2 · Lewicke et al. · 2014 [cited by applicant]
US 8909330B2 · McCombie et al. · 2014 [cited by applicant]
US 8961439B2 · Yang et al. · 2015 [cited by applicant]
US 8968218B2 · Wukasch et al. · 2015 [cited by applicant]
US 9060714B2 · Bajcsy et al. · 2015 [cited by applicant]
US 9107615B2 · Buckman · 2015 [cited by applicant]
US 9173596B1 · Berme et al. · 2015 [cited by applicant]
US 9179862B2 · Stergiou et al. · 2015 [cited by applicant]
US 9186096B2 · Solinsky · 2015 [cited by applicant]
US 9265448B2 · Bonnet · 2016 [cited by applicant]
US 9314394B2 · Hirata et al. · 2016 [cited by applicant]
US 9375570B2 · Kiani et al. · 2016 [cited by applicant]
US 9392966B2 · Ten Kate · 2016 [cited by applicant]
US 9445720B2 · Janna et al. · 2016 [cited by applicant]
US 9554731B2 · Malchau et al. · 2017 [cited by applicant]
US 9591993B2 · Morris Bamberg et al. · 2017 [cited by applicant]
US 9723987B2 · Goetz · 2017 [cited by applicant]
US 9802040B2 · Ichimura et al. · 2017 [cited by applicant]
US 9826921B2 · Griffiths et al. · 2017 [cited by applicant]
US 9877523B2 · Ellis · 2018 [cited by applicant]
US 9877668B1 · Sarkar et al. · 2018 [cited by applicant]
US 9901290B2 · Najafi et al. · 2018 [cited by applicant]
US 9936912B2 · Roovers et al. · 2018 [cited by applicant]
US 9974478B1 · Brokaw et al. · 2018 [cited by applicant]
US 9993181B2 · Ross · 2018 [cited by applicant]
US 10026292B2 · Baker et al. · 2018 [cited by applicant]
US 20050240086A1 · Akay · 2005 [cited by applicant]
US 20070076270A1 · Poletto · 2007 [cited by applicant]
US 20070276270A1 · Tran · 2007 [cited by applicant]
US 20090062696A1 · Nathan et al. · 2009 [cited by applicant]
US 20090137921A1 · Kramer et al. · 2009 [cited by applicant]
US 20090227890A1 · Lanfermann · 2009 [cited by examiner]
US 20090319221A1 · Kahn · 2009 [cited by examiner]
US 20110190593A1 · McNair · 2011 [cited by applicant]
US 20110245629A1 · Giftakis et al. · 2011 [cited by applicant]
US 20120215076A1 · Yang et al. · 2012 [cited by applicant]
US 20130060167A1 · Dracup et al. · 2013 [cited by applicant]
US 20130154827A1 · Housley · 2013 [cited by applicant]
US 20130218053A1 · Kaiser et al. · 2013 [cited by applicant]
US 20140039274A1 · Sarrafzadeh et al. · 2014 [cited by applicant]
US 20140249452A1 · Marsh et al. · 2014 [cited by applicant]
US 20150018723A1 · Lee et al. · 2015 [cited by applicant]
US 20150099945A1 · Hawkins, III et al. · 2015 [cited by applicant]
US 20150157252A1 · Sabesan · 2015 [cited by applicant]
US 20150164377A1 · Nathan et al. · 2015 [cited by applicant]
US 20150272511A1 · Najafi et al. · 2015 [cited by applicant]
US 20160038059A1 · Asada et al. · 2016 [cited by applicant]
US 20160038061A1 · Kechichian et al. · 2016 [cited by applicant]
US 20160058324A1 · Cao · 2016 [cited by examiner]
US 20160058326A1 · Winfree et al. · 2016 [cited by applicant]
US 20160166202A1 · Haraikawa et al. · 2016 [cited by applicant]
US 20160213318A1 · Parodi et al. · 2016 [cited by applicant]
US 20160263437A1 · Kow et al. · 2016 [cited by applicant]
US 20160278666A1 · Kozloski et al. · 2016 [cited by applicant]
US 20160278708A1 · Vrazic · 2016 [cited by applicant]
US 20160296156A1 · Conradsen et al. · 2016 [cited by applicant]
US 20160310069A1 · Sinderby et al. · 2016 [cited by applicant]
US 20160317040A1 · Russell et al. · 2016 [cited by applicant]
US 20160324445A1 · Kim et al. · 2016 [cited by applicant]
US 20160331255A1 · Cheatham, III · 2016 [cited by examiner]
US 20170007168A1 · Mirelman et al. · 2017 [cited by applicant]
US 20170042453A1 · Cheung · 2017 [cited by applicant]
US 20170042467A1 · Herr et al. · 2017 [cited by applicant]
US 20170055880A1 · Agrawal et al. · 2017 [cited by applicant]
US 20170146386A1 · Wiard · 2017 [cited by examiner]
US 20170150897A1 · Komaki · 2017 [cited by applicant]
US 20170156662A1 · Goodall et al. · 2017 [cited by applicant]
US 20170188895A1 · Nathan · 2017 [cited by applicant]
US 20170195637A1 · Kusens et al. · 2017 [cited by applicant]
US 20170202724A1 · De Rossi et al. · 2017 [cited by applicant]
US 20170231533A1 · Qu et al. · 2017 [cited by applicant]
US 20170273616A1 · Yang et al. · 2017 [cited by applicant]
US 20170281054A1 · Stever et al. · 2017 [cited by applicant]
US 20170291065A1 · Klopman · 2017 [cited by applicant]
US 20170325749A1 · Shah · 2017 [cited by examiner]
US 20170352240A1 · Carlton-Foss · 2017 [cited by applicant]
US 20180028105A1 · Osorio · 2018 [cited by applicant]
US 20180049671A1 · Markison et al. · 2018 [cited by applicant]
US 20180125386A1 · Lim et al. · 2018 [cited by applicant]
US 20180140842A1 · O Laighin et al. · 2018 [cited by applicant]
US 20180146910A1 · De Vries et al. · 2018 [cited by applicant]
US 20180146914A1 · Snow et al. · 2018 [cited by applicant]
US 20180153477A1 · Nagale et al. · 2018 [cited by applicant]
US 20180177436A1 · Chang et al. · 2018 [cited by applicant]
US 20180220932A1 · Jung · 2018 [cited by applicant]
US 20180249967A1 · Lederman et al. · 2018 [cited by applicant]
US 20180279966A1 · Park et al. · 2018 [cited by applicant]
US 20180317811A1 · Lee et al. · 2018 [cited by applicant]
US 20190029606A1 · Sheth · 2019 [cited by examiner]
US 20210106238A1 · Strasser et al. · 2021 [cited by applicant]
US 20210196182A1 · D'Arcy · 2021 [cited by examiner]
US 20210202090A1 · O'Donovan · 2021 [cited by examiner]
EP 2708185B1 · 2017 [cited by applicant]
EP 3154627B1 · 2018 [cited by applicant]
EP 3308912A1 · 2018 [cited by applicant]
EP 2445405B1 · 2018 [cited by applicant]
WO WO2006134359A1 · 2006 [cited by applicant]
WO WO13045725A2 · 2013 [cited by applicant]
WO WO2013056099A1 · 2013 [cited by applicant]
WO WO2016172557A1 · 2016 [cited by applicant]
WO WO2017123725A1 · 2017 [cited by applicant]
WO WO2017202839A1 · 2017 [cited by applicant]
WO WO18102579A1 · 2018 [cited by applicant]
WO WO2018110925A1 · 2018 [cited by applicant]
International Search Report issued on Mar. 17, 2020 in International Application No. PCT/SE2019/051322. [cited by applicant]
Written Opinion issued on Mar. 17, 2020 in International Application No. PCT/SE2019/051322. [cited by applicant]
José R. Villar, et al., “A hybrid intelligent recognition system for the early detection of strokes,” Integrated Computer-Aided Engineering, pp. 215-277, Jun. 2015. [cited by applicant]