IP Library Granted Patent US 8,933,801
Granted Patent B2
US 8,933,801 · App. 13/866,388 · Granted Jan 13, 2015

Fall detection system and method

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Quick Facts
Patent No.
US 8,933,801
App. No.
13/866,388
Granted
Jan 13, 2015
Kind
B2
Abstract

A fall detection method determines a fall detection algorithm based on sensor data aggregated from a plurality of fall detection devices. Sensor data is obtained from one of the plurality of fall detection devices not included in the aggregated sensor data. A probable fall event of the obtained sensor data is determined based on the fall detection algorithm. An alarm signal is generated based upon the determination of the probable fall event. A validity of the probable fall event is determined, and the fall detection algorithm is refined using the obtained sensor data and the validity of the probable fall event each time sensor data is obtained from any of the plurality of fall detection devices.

Claims (44)

1. A fall detection method comprising:

determining a fall detection algorithm based on sensor data aggregated from a plurality of fall detection devices;

obtaining sensor data from one of the plurality of fall detection devices not included in the aggregated sensor data;

determining a probable fall event of the obtained sensor data based on the fall detection algorithm;

generating an alarm signal based upon the determination of the probable fall event;

determining a validity of the probable fall event; and

refining the fall detection algorithm using the obtained sensor data and the validity of the probable fall event each time sensor data is obtained from any of the plurality of fall detection devices.

2. The method of claim 1 , wherein the probable fail event determination is based on a most recently refined fall detection algorithm.

3. The method of claim 1 , wherein the refined fall detection algorithm is based on an ever increasing sample size of sensor data in aggregate.

4. The method of claim 1 is a progressive fall detection method that applies a plurality of versions of the fall detection algorithm to detect a fall.

5. The method of claim 1 , wherein the validity of the probable fall event indicates that the obtained sensor data represents either a false-positive fall event, a false-negative fall event, or confirms the fall event.

6. The method of claim 1 , wherein the fall detection algorithm is further refined based on user characteristics and user fall history.

7. The method of claim 1 , wherein the validity of the probable fall event is provided by a user of the fall detection device.

8. The method of claim 1 , wherein the determination of the probable fall event is executed among a distributed intelligence.

9. The method of claim 1 , further comprising:

customizing the refined fall detection algorithm to each user.

10. The method of claim 1 , wherein the sensor data includes accelerometer data including a drop phase, land phase and stay phase.

11. A fall detection system comprising:

a plurality of fall detection devices each including a corresponding sensor;

a relay device providing communication between the fall detection device and a server;

the server determining a fall detection algorithm based on sensor data aggregated from the plurality of fall detection devices, wherein

one of the fall detection devices obtains sensor data not included in the aggregated sensor data; and

the server includes a processor to determine a probable fall event of the obtained sensor data based on the fall detection algorithm, generate an alarm signal based upon the determination of the probable fall event, determine a validity of the probable fall event and refine the fall detection algorithm using the obtained sensor data and the validity of the probable fall event each time sensor data is obtained from any of the plurality of fall detection devices.

12. The fall detection system of claim 11 , wherein the probable fall event is determined progressively in that a plurality of versions of the fall detection algorithm are applied to detect a fall.

13. The fall detection system of claim 11 , wherein the server is provided in a cloud-based network.

14. The fall detection system of claim 11 , wherein the server includes memory to store the aggregated sensor data and the refined fall detection algorithm.

15. The fall detection system of claim 11 , wherein the refined fall detection algorithm is based on an ever increasing sample size of sensor data in aggregate.

16. The fall detection system of claim 11 , wherein the fall detection device is further refined based on user characteristics and user fall history.

17. The fall detection system of claim 11 , wherein a transmitter of the fall detection device transmits the validity of the probable fall event.

18. The fall detection system of claim 11 , wherein the fall detection device is worn around a neck of a user.

19. A fall detection determining device comprising:

a receiver receiving sensor data aggregated from a plurality of fall detection devices and new sensor data from one of the plurality of fall detection devices not included in the aggregated sensor data;

a processor determining a fall detection algorithm based on the sensor data aggregated from the plurality of fall detection devices, and the processor determining a probable fall event of the new sensor data based on the fall detection algorithm;

a transmitter transmitting an alarm signal based upon the determination of the probable fall event,

wherein the receiver receives a validity of the probable fall event, and the processor refines the fall detection algorithm using the new sensor data and the validity of the probable fall event each time sensor data is obtained from any of the plurality of fall detection devices.

20. The fall detection determining device of claim 19 , wherein the fall detection determining device is a relay device providing communication between fall detection device and a cloud-based network.

21. The fall detection determining device of claim 19 , wherein the fall detection determining device is a server provided in a cloud-based network.

22. The fall detection determining device of claim 19 , wherein the refined fall detection algorithm is based on an ever increasing sample size of sensor data in aggregate.

23. A fall detection system comprising:

a plurality of fall detection devices each including a corresponding sensor,

wherein each of the fall detection devices obtains respective sensor data not included in the aggregated sensor data;

a relay device providing communication between the fall detection device and a server; and

the fall detection devices, the relay device and the server each including a processor, wherein any combination of the fall detection device, the relay device and the server determines a fall detection algorithm based on sensor data aggregated from the plurality of fall detection devices, determines a probable fall event of the obtained sensor data based on the fall detection algorithm, generates an alarm signal based upon the determination of the probable fall event, determines a validity of the probable fall event and refines the fall detection algorithm using the obtained sensor data and the validity of the probable fall event each time sensor data is obtained from any of the plurality of fall detection devices.

24. The fall detection system of claim 23 , wherein any combination of the fall detection device, the relay device and the server provides storage into respective memory for the obtained sensor data, the aggregated sensor data, the fall detection algorithm, the probable fall event, the validity of the probable fall event, and the refined fall detection algorithm.

Assignments (7)
CHANGE OF NAME Recorded Jan 9, 2024
From: NORTEK SECURITY & CONTROL LLC
To: NICE NORTH AMERICA LLC
Reel/Frame 066242/0513 →
TERMINATION AND RELEASE OF INTELLECTUAL PROPERTY SECURITY AGREEMENT SUPPLEMENT Recorded Sep 28, 2021
From: BANK OF AMERICA, N.A.
To: NORTEK, INC.; 2GIG TECHNOLOGIES, INC.; BROAN-NUTONE LLC; CES GROUP, LLC; CORE BRANDS, LLC; ERGOTRON, INC.; HUNTAIR, INC.; LINEAR LLC; MAGENTA RESEARCH LTD.; NORDYNE LLC
Reel/Frame 057640/0399 →
NOTICE OF RELEASE OF SECURITY INTEREST IN PATENTS Recorded Jan 11, 2017
From: WELLS FARGO BANK, NATIONAL ASSOCIATION
To: NORTEK, INC.; BARCOM ASIA HOLDINGS, LLC; BARCOM CHINA HOLDINGS, LLC; BNSS LP, INC.; BNSS GP, INC.; BROAN-NUTONE LLC; BROAN-NUTONE STORAGE SOLUTIONS LP; CES GROUP, LLC (SUCCESSOR BY MERGER TO HUNTAIR, INC.); CES INTERNATIONAL LTD.; CORE BRANDS, LLC; ERGOTRON, INC.; GEFEN, LLC; GTO ACCESS SYSTEMS, LLC (F/K/A GATES THAT OPEN, LLC); HUNTAIR MIDDLE EAST HOLDINGS, INC.; LINEAR LLC; MAGENTA RESEARCH LTD.; NORTEK INTERNATIONAL, INC.; NORDYNE INTERNATIONAL, INC.; NORDYNE LLC; OPERATOR SPECIALTY COMPANY, INC.; PACIFIC ZEPHYR RANGE HOOD, INC.; REZNOR LLC; TV ONE BROADCAST SALES CORPORATION; ZEPHYR VENTILATION, LLC
Reel/Frame 041346/0048 →
CHANGE OF NAME Recorded Mar 2, 2015
From: LINEAR LLC
To: NORTEK SECURITY & CONTROL LLC
Reel/Frame 035114/0695 →
INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded May 13, 2014
From: LINEAR LLC; GTO ACCESS SYSTEMS, LLC (F/K/A GATES THAT OPEN, LLC); BROAN-NUTONE LLC; CORE BRANDS, LLC; ERGOTRON, INC.; CES GROUP, LLC (SUCCESSOR BY MERGER TO HUNTAIR, INC.); TV ONE BROADCAST SALES CORPORATION; NORDYNE LLC; CES GROUP, LLC; REZNOR LLC
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
Reel/Frame 032891/0753 →
INTELLECTUAL PROPERTY SECURITY AGREEMENT SUPPLEMENT Recorded May 2, 2014
From: NORTEK, INC.; 2GIG TECHNOLOGIES, INC.; BROAN-NUTONE LLC; CES GROUP, LLC; CORE BRANDS, LLC; ERGOTRON, INC.; HUNTAIR, INC.; LINEAR LLC; MAGENTA RESEARCH LTD.; NORDYNE LLC
To: BANK OF AMERICA, N.A.
Reel/Frame 032814/0539 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 19, 2013
From: SWEENEY, JEFFREY M.; HAFLINGER, JAMES J.
To: LINEAR, LLC.
Reel/Frame 030252/0718 →