Fall detection system and method

• US 10,524,698 B2
• Filed: 05/23/2014
• Issued: 01/07/2020
• Est. Priority Date: 06/06/2013
• Status: Active Grant

• Current Assignee: Lifeline Systems Company (Koninklijke Philips N.V.)
• Original Assignee: Koninklijke Philips N.V.
• Inventors: Annegarn, Janneke, Baldus, Heribert, Ten Kate, Warner Rudolf Theophile
• Primary Examiner(s): Cerioni, Daniel L
• Application Number:
  US14/895,369
• Publication Number:
  US 20160113551A1
• Time in Patent Office: 2,055 Days
• Field of Search: 600595
• CPC Class Codes: A61B 2017/00207 with hand gesture control or hand gesture recognition
• CPC Class Codes: A61B 2560/0475 Special features of memory means, e.g. removable memory cards
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/1117 Fall detection
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: G08B 21/043 detecting an emergency event, e.g. a fall
• CPC Class Codes: G08B 21/0446 worn on the body to detect changes of posture, e.g. a fall, inclination, acceleration, gait
• CPC Class Codes: G08B 31/00 Predictive alarm systems characterised by extrapolation or other computation using updated historic data
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

There is provided a fall detection system, comprising a user device comprising one or more sensors for measuring the movements of a user; and the system further comprising a processing unit configured to operate in a first mode in which the processing unit processes the measured movements to determine if the user has fallen and a further mode in which the processing unit processes measured movements obtained during a user-specified time period to determine the risk of the user falling.

Claims

1. A fall detection system designed to be worn or carried by a user, comprising:

a user device comprising one or more sensors configured to measure movements of the user;

a memory device; and

a processing unit configured to;

operate in a first mode in which the processing unit processes the measured movements to determine if the user has fallen;

detect a first input from the user specifying a start of a user-specified time period, wherein the user-specified time period has a predetermined length during which the user will perform one or more specified exercises and/or movements used to assess fall risk;

operate in a data collection mode in which the processing unit stores a sub-set of the measured movements, which includes only the measured movements obtained during the user-specified time period having the predetermined length, in the memory device;

detect a subsequent input from the user specifying a subsequent start of a subsequent user-specified time period, wherein the subsequent user-specified time period has a subsequent predetermined length during which the user will perform the one or more specified exercises and/or movements used to assess the fall risk;

operate in the data collection mode in which the processing unit stores a subsequent sub-set of the measured movements, which includes only the measured movements obtained during the subsequent user-specified time period having the subsequent predetermined length, in the memory device;

detect a second different input from the user after lapse of the user-specified time period; and

operate in a data analysis mode in which the processing unit processes the sub-set of the measured movements stored in the memory device and the subsequent sub-set of the measured movements stored in the memory device to determine a risk of the user falling.

2. The fall detection system as claimed in claim 1, the processing unit is configured to concurrently operate in the first mode and in the data collection mode.

3. The fall detection system as claimed in claim 1, wherein on detection of the first input from the user specifying the start of the time period, the processing unit is further configured to start a timer.

4. The fall detection system as claimed in claim 3, wherein the processing unit is configured to resume operating in the first mode when the timer reaches a predetermined value.

5. The fall detection system as claimed in claim 1, the system further comprising a display that is controlled by the processing unit, the processing unit being configured to provide instructions to the user via the display for one or more exercises and/or movements for the user to perform while the processing unit is operating in the data collection mode.

6. The fall detection system as claimed in claim 5, wherein the processing unit is configured to adapt the instructions for the one or more exercises and/or movements based on a previously-determined fall risk for the user.

7. The fall detection system as claimed in claim 1, wherein the processing unit is configured to continue processing the measured movements to determine if the user has fallen while operating in the data collection mode.

8. The fall detection system as claimed in claim 1, wherein the user provides an input by performing a predefined gesture or movement with the user device, and wherein the processing unit is configured to process the measured movements to detect whether the user has performed a predefined gesture or movement with the user device.

9. The fall detection system as claimed in claim 8, wherein the predefined gesture or movement comprises one of:

shaking the user device, turning the user device over, moving the user device in a circle or moving the user device in a figure-of-eight.

10. The fall detection system as claimed in claim 1, wherein the processing unit is configured such that, when operating in the analysis mode, the processing unit processes the measured movements obtained during the user-specified time period to identify whether the user has performed one or more movements and/or exercises used to assess fall risk, and in the event that a movement or exercise is identified, the processing unit evaluates how well the user performed said movement or exercise to determine the risk of the user falling.

11. The fall detection system as claimed in claim 1, wherein the processing unit is configured to continue processing the measured movements to determine if the user has fallen while operating in the data analysis mode.

12. The fall detection system as claimed in claim 1, further comprising:

a user interface, wherein the processing unit is further configured to provide an indication of a level of the determined fall risk with the user interface.

13. The fall detection system as claimed in claim 1, wherein the one or more sensors are from a group consisting of an accelerometer, a pressure sensor, a gyroscope, and a magnetic field sensor.

14. The fall detection system as claimed in claim 1, wherein the user device is from a group consisting of a pendant, a wrist band, and chest band.

15. A method of operating a fall detection system designed to be worn by a user, the method comprising:

measuring, with one or more sensors of a user device, movements of the user;

operating, with a processing unit of the user device, the system in a first mode in which the measured movements are processed to determine if the user has fallen;

detecting, with the processing unit of the user device, a first input from the user specifying a start of a user-specified time period, wherein the user-specified time period has a predetermined length during which the user will perform one or more specified exercises and/or movements used to assess fall risk;

operating, with the processing unit of the user device, the system in a data collection mode in which the processing unit stores a sub-set of the measured movements, which includes only the measured movements obtained during the user-specified time period having the predetermined length, in a memory;

detecting, with the processing unit of the user device, a subsequent input from the user specifying a subsequent start of a subsequent user-specified time period, wherein the user-specified time period has a subsequent predetermined length during which the user will perform the one or more specified exercises and/or movements used to assess the fall risk; and

operating, with the processing unit of the user device, in the data collection mode in which the processing unit stores a subsequent sub-set of the measured movements, which includes only the measured movements obtained during the subsequent user-specified time period having the subsequent predetermined length, in the memory;

detecting, with the processing unit of the user device, a second different input from the user after lapse of the user-specified time period; and

operating, with the processing unit of the user device, the system in a data analysis mode in which the processing unit processes the stored sub-set of the measured and the stored subsequent sub-set of the measured movements to determine a risk of the user falling.

16. The method as claimed in claim 15, wherein the user performs a gesture to input the start of the time period.