IP Library › Granted Patent US 12,419,543
Granted Patent B2
US 12,419,543 · App. 18/355,892 · Granted Sep 23, 2025

System, method and computer program product for processing a mobile phone user's condition

Inventors: Yuval Naveh (Haifa, IL); Shahar Davidson (Rehovot, IL); Tomer Shussman (Kfar Saba, IL)
Assignee: Celloscope Ltd.
A61B5/1117A61B5/681A61B5/7275G08B21/182A61B2562/0219
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Quick Facts
Patent No.
US 12,419,543
App. No.
18/355,892
Filed
Jul 20, 2023
Granted
Sep 23, 2025
Kind
B2
Art Unit
2632
USPC
709/203
Abstract

A stroke detection system operative to detect strokes suffered by mobile communication device users, the system comprising: a hardware processor operative in conjunction with a mobile communication device having at least one built-in sensor; the hardware processor being configured to, typically repeatedly and typically without being activated by the device's user, compare data derived from the at least one sensor to at least one baseline value for at least one indicator of user well-being, stored in memory accessible to the processor, and/or make a stroke risk level evaluation; and/or perform at least one action if and only if the stroke risk level is over a threshold.

Claims (42)

1. A risky condition assessment and monitoring system operative to detect propensities of mobile communication device users for falls, the system comprising:

a hardware processor operative in conjunction with a mobile communication device having at least one built-in sensor, the hardware processor being configured to, repeatedly, and without being activated by the device's user,

make a fall propensity evaluation evaluating level of risk that the user will fall; and

perform at least one action, if and only if said level of risk is over a threshold,

wherein the system is configured to perform, at least once, an action which comprises prompting the user to cooperate in a validation process, including asking the user to take a test to yield more data to validate estimation of risk.

2. The system of claim 1 wherein the system initiates user cooperation to validate said evaluation, and changes said evaluation for at least one user, responsive to that user's cooperation.

3. The system of claim 1 wherein the system connects to at least one additional wearable to validate said evaluation, and changes said evaluation for at least one user, responsive to data provided by said at least one additional wearable.

4. The system of claim 3 wherein said wearable comprises a smartwatch, pedometer, or heartbeat monitor.

5. The system of claim 1 wherein said at least one sensor comprises plural sensors.

6. The system of claim 5 wherein said plural sensors include at least one of the following: IMU, camera, microphone.

7. The system of claim 5 wherein said plural sensors include at least two of the following: IMU, camera, microphone.

8. The system of claim 1 wherein the hardware processor receives as input, and uses for said evaluation, passive measurements, including passive gait monitoring.

9. The system of claim 1 wherein the hardware processor receives as input, and uses for said evaluation, at least one controlled measurement of Reaction time in walking.

10. The system of claim 1 wherein said sensor comprises a motion sensor.

11. The system of claim 10 wherein said motion sensor comprises at least one of: gyroscope, accelerometer.

12. The system of claim 1 wherein said sensor comprises at least one of: camera, microphone, or keypad of said communication device.

13. The system of claim 1 wherein the hardware processor correlates or learns associations of input signals with specific preventive actions.

14. The system of claim 1 wherein said risk level evaluation relies only on said at least one built-in sensor, thereby to obviate any need for any sensor not already deployed in mobile phones.

15. The system of claim 1 wherein said action comprises prompting the user to cooperate in a validation process.

16. The system of claim 1 wherein an auxiliary software platform enables recruitment of mobile phone users to subscribe to said system, thereby to allow an organization affiliated with a multiplicity of mobile phone users, to require or incentivize mobile phone users affiliated therewith to subscribe to said system.

17. The system of claim 1 wherein the hardware processor correlates or learns associations of input signals with gait analysis data.

18. The system of claim 1 wherein the hardware processor correlates or learns associations of input signals with documentation of actual falls.

19. The system of claim 1 wherein said hardware processor comprises the mobile communication device's processor, onto which cell app software has been downloaded, wherein said software is configured to:

compare data derived from said at least one sensor to at least one baseline value for at least one indicator of user well-being, stored in memory accessible to the processor,

make a fall risk level evaluation; and

perform at least one action, if and only if the fall risk level is over a threshold.

20. The system of claim 1 wherein the hardware processor comprises all or any subset of:

a condition estimation component which at least once estimates the user's condition,

a passive signal component operative, typically continuously, to extract signals from at least one said built-in sensor and feed said signals into at least one other component such as said condition estimation component;

an action component which takes action depending on a current state of the user condition estimation component; and

a validation component, triggered by the action component and configured to generate active signals which in turn feed into the condition estimation component.

21. The system of claim 20 wherein the mobile communication device comprises a phone and wherein at least one of said components comprises logic configuring a hardware processor such as the phone's own processor.

22. A risky condition assessment and monitoring method operative to detect propensities of mobile communication device users for falls, the method comprising:

using a hardware processor in conjunction with a mobile communication device having at least one built-in sensor, the hardware processor being configured to, repeatedly, and without being activated by the device's user,

make a fall propensity evaluation evaluating level of risk that the user will fall; and

perform at least one action, if and only if said level of risk is over a threshold; and

at least once, prompting the user to cooperate in a validation process, including asking the user to take a test to yield more data to validate estimation of risk.

23. A computer program product, comprising a non-transitory tangible computer readable medium having computer readable program code embodied therein, the computer readable program code adapted to be executed to implement a method operative to detect strokes suffered by mobile communication device users, the method comprising:

using a hardware processor in conjunction with a mobile communication device having at least one built-in sensor, the hardware processor being configured to, repeatedly, and without being activated by the device's user,

make a fall propensity evaluation evaluating level of risk that the user will fall; and

perform at least one action, if and only if said level of risk is over a threshold; and

at least once, prompting the user to cooperate in a validation process, including asking the user to take a test to yield more data to validate estimation of risk.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 27, 2023
From: NAVEH, YUVAL; DAVIDSON, SHAHAR; SHUSSMAN, TOMER
To: CELLOSCOPE LTD.
Reel/Frame 065040/0245 →
Continuity (4)
Continuation In Part 16814114 · Mar 10, 2020
Continuation In Part 16659832 · Oct 22, 2019
Provisional Application 62816227 · Mar 11, 2019
Related Publication 20240008766A1 · Jan 11, 2024
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