IP Library Granted Patent US 10,758,188
Granted Patent B2
US 10,758,188 · App. 15/709,020 · Granted Sep 1, 2020

Stroke detection and prevention system and method

Inventors: Yasuyuki Kataoka (Palo Alto, CA); Ravi Srivatsav (Palo Alto, CA)
A61B5/7275A61B5/112A61B5/1124A61B5/4064A61B5/4803A61B5/7465G06F19/3418G16H10/60G16H50/20G16H50/30G16H80/00A61B5/0205A61B5/224
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Quick Facts
Patent No.
US 10,758,188
App. No.
15/709,020
Granted
Sep 1, 2020
Kind
B2
Abstract

A stroke detection and prevention system and method are provided in which there may be one or more phases of detection using devices in which the phases include user-friendly, less accurate tests to less user-friendly, more accurate tests.

Claims (30)

1. A stroke detection and prevention system, comprising:

a stroke detection and prevention computer system having a processor and a memory;

one or more computing devices that provide a first type of stroke detection data, a second type of stroke detection data and a third type of stroke detection data to the stroke detection and prevention computer system;

the stroke detection and prevention computer system memory further comprising:

a first phase element having a plurality of lines of computer code executed by the processor that performs a first phase of stroke detection comprising analyzing data from two tests performed by a user that generate the first type of stroke detection data to generate a first set of low accuracy stroke detection data, generating a stroke risk score based on the analyzing, and prompting a user to generate the second type of stroke detection data if a risk of stroke is detected;

the second phase element having a plurality of lines of computer code executed by the processor that performs a second phase of stroke detection comprising analyzing data from a test that generates the second set of higher accuracy stroke detection data, generating a stroke risk score based on the analyzing, and prompting the user to generate the third type of stroke detection data if a risk of stroke is detected; and

the third phase element having a plurality of lines of computer code executed by the processor that performs a third phase of stroke detection that processes the third type of stroke detection data obtained via telemedicine to generate a third set of highest accuracy stroke detection data.

2. The system of claim 1 , wherein the first phase element further comprises a gait analysis tool that receives gait data and a speech analysis tool that receives speech data wherein the gait data and the speech data are a first type of health data.

3. The system of claim 2 , wherein the gait analysis tool is configured to receive arm movement data about a user and gait data about the user and generate the first set of low accuracy stroke detection data based on the arm movement data and the gait data.

4. The system of claim 3 , wherein the computing device that generates the first type of stroke detection data is a wearable health device.

5. The system of claim 4 , wherein the gait analysis tool is further configured to calculate an anomaly score to determine the risk of stroke.

6. The system of claim 5 , wherein the gait analysis tool is further configured to calculate the anomaly score, s, equal to ⅓ *(x+y+z) wherein x measures body balance, y measures arm swing and z measures walking cadence.

7. The system of claim 1 , wherein the second phase element further comprises an arm strength test.

8. The system of claim 7 , wherein the computing device that generates the second type of stroke detection data is a game device.

9. The system of claim 1 , wherein the computing device that generates the third type of stroke detection data is one of a laptop computer, a personal computer and a tablet computer.

10. A stroke detection and prevention method, comprising:

receiving stroke detection data from at least one computing device that captures a first type of health data;

performing a first phase of stroke detection using a first service and a first data analysis module that processes the first type of health data to generate a first set of low accuracy stroke detection data by analyzing data from two tests performed by a user and prompts the user to generate a second type of stroke detection data if a risk of stroke is detected;

receiving stroke detection data from at least one computing device that captures the second type of health data;

performing a second phase of stroke detection using a second service and a second data analysis module that processes the second type of health data to generate a second set of higher accuracy stroke detection data and prompts the user to generate a third type of stroke detection data if a risk of stroke is detected; and

receiving stroke detection data from at least one computing device that captures the third type of health data via telemedicine;

performing a third phase of stroke detection using a third service that processes the third type of health data to generate a third set of highest accuracy stroke detection data.

11. The method of claim 10 , wherein performing the first phase of stroke detection further comprises performing a gait analysis with gait data and speech analysis with speech data wherein the gait data and the speech data are the first type of health data.

12. The method of claim 11 , wherein performing the gait analysis further comprising receiving arm movement data about a user and gait data about the user and generating the first set of low accuracy stroke detection data based on the arm movement data and the gait data.

13. The method of claim 12 further comprising receiving the first type of health data from a wearable health device.

14. The method of claim 13 , wherein performing the gait analysis further comprises calculating an anomaly score to determine the risk of stroke.

15. The method of claim 14 , wherein calculating the anomaly score further comprises calculating the anomaly score, s, equal to ⅓ *(x+y+z) wherein x measures body balance, y measures arm swing and z measures walking cadence.

16. The method of claim 10 , wherein performing the second phase of stroke detection further comprises performing an arm strength test.

17. The method of claim 16 further comprising receiving the second type of health data from a game device.

18. The method of claim 11 further comprising receiving the third type of health data from one of a laptop computer, a personal computer and a tablet computer.

Assignments (2)
CHANGE OF NAME Recorded Apr 14, 2020
From: NTT INNOVATION INSTITUTE, INC.
To: NTT RESEARCH, INC.
Reel/Frame 052396/0582 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 18, 2018
From: KATAOKA, YASUYUKI; SRIVATSAV, RAVI
To: NTT INNOVATION INSTITUTE, INC.
Reel/Frame 045580/0247 →
Continuity (2)
Provisional Application 62396597 · Sep 19, 2016
Related Publication 20180078213A1 · Mar 22, 2018