FALL DETECTION SYSTEM AND METHOD

• US 20160220153A1
• Filed: 08/28/2014
• Published: 08/04/2016
• Est. Priority Date: 09/11/2013
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips N.V.
• Inventors: TEN KATE, WARNER RUDOPH THEOPHILE, ANNEGARN, JANNEKE, BALDUS, HERIBERT
• Granted Patent: US 10,335,059 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• 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 5/1118 Determining activity level
• 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: G01P 13/00 Indicating or recording presence, absence, or direction, of movement electric switches H01H; counting moving objects G06M7/00
• 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 29/185 Signal analysis techniques for reducing or preventing false alarms or for enhancing the reliability of the system
• CPC Class Codes: G08B 29/20 Calibration, including self-calibrating arrangements

Abstract

There is provided a fall detection system for use in detecting falls by a user, the fall detection system comprising a processing unit configured to determine context information about the user and/or the environment in which the user is located, and to increase the sensitivity of a fall detection algorithm used to detect falls by a user in the event that the determined context information indicates that the user is or may be at an increased risk of falling, the increase in sensitivity occurring while the increased risk of falling is indicated by the determined context information.

Claims

1. A fall detection system for use in detecting falls by a user, the fall detection system comprising:

a processing unit configured to determine context information about the user and/or the environment in which the user is located, and to increase the sensitivity of a fall detection algorithm used to detect falls by a user in the event that the determined context information indicates that the user is or may be at an increased risk of falling, the increase in sensitivity occurring while the increased risk of falling is indicated by the determined context information.

2. The fall detection system as claimed in claim 1, wherein the context information comprises an indication of whether the user is performing a fall risk assessment test or balance training;

and the processing unit is configured to determine that the user is or may be at an increased risk of falling if the context information indicates that the user is performing a fall risk assessment test or balance training.

3. The fall detection system as claimed in claim 1, wherein the context information comprises an indication of whether the user is walking, and the processing unit is configured to determine that the user is or may be at an increased risk of falling if the context information indicates that the user is walking.

4. The fall detection system as claimed in claim 1, wherein the context information comprises an indication of whether an unusual movement pattern for the user has been detected, and the processing unit is configured to determine that the user is or may be at an increased risk of falling if the context information indicates an unusual movement pattern.

5. The fall detection system as claimed in claim 1, wherein the context information comprises an indication of the current location of the user, and the processing unit is configured to determine that the user is or may be at increased risk of falling if the current location of the user is a known location where the user is at a higher risk of falling.

6. The fall detection system as claimed in claim 1, wherein the context information about the environment in which the user is located comprises an indication of the ambient light in the user'"'"'s location, an indication of how even or uneven the ground is, an indication of the current weather or temperature and/or an indication of the ambient noise level and the processing unit is configured to determine that the user is or may be at increased risk of falling if the ambient light is below a threshold, if the ground is uneven, if the weather is wet or the temperature is below a threshold and/or if ambient noise level is above threshold.

7. The fall detection system as claimed in claim 1, wherein the context information comprises an indication of the current time, and the processing unit is configured to determine that the user is or may be at increased risk of falling if the current time is within one or more specified time periods.

8. The fall detection system as claimed in claim 7, wherein the one or more specified time periods comprises the night time and/or time periods shortly before and/or after a scheduled dose of medication.

9. The fall detection system as claimed in claim 1, wherein the context information comprises an indication of whether the user is making use of a walking aid, whether the user is wearing their glasses, and/or an indication of the type of shoes the user is wearing, and the processing unit is configured to determine that the user is or may be at an increased risk of falling if the user is not using a required walking aid, not wearing their glasses and/or not wearing their regular or the correct shoes.

10. The fall detection system as claimed in claim 1, wherein the context information comprises an indication of the current activity level of the user, and the context information indicates that the user is or may be at increased risk of falling if the current activity level is above a threshold activity level.

11. The fall detection system as claimed in claim 1, wherein the processing unit is further configured to determine if the context information indicates that the user is or may be at a decreased risk of falling, and to decrease the sensitivity of the fall detection algorithm while the decreased risk of falling is indicated by the determined context information.

12. A method of operating a fall detection system to detect falls by a user, the method comprising:

determining context information about the user and/or the environment in which the user is located; and

in the event that the determined context information indicates that the user is or may be at an increased risk of falling, increasing the sensitivity of a fall detection algorithm used to detect falls by a user while the increased risk of falling is indicated by the determined context information.

13. The method as claimed in claim 12, the method further comprising the steps of:

determining further context information about the user and/or the environment in which the user is located; and

resetting or reducing the sensitivity of the fall detection algorithm if the further context information indicates that the user is no longer at an increased risk of falling.

14. The method as claimed in claim 12, the method further comprising the step of:

initially operating the fall detection system with the fall detection algorithm set to a normal sensitivity corresponding to a normal risk of falling for the user;

wherein when the context information indicates that the user is or may be at an increased risk of falling relative to the normal risk of falling for the user, the sensitivity of the fall detection algorithm is increased above the normal sensitivity.

15. A computer program product having computer readable code embodied therein, the computer readable code being configured such that, on execution by a suitable computer or processing unit, the computer or processing unit performs the method of claim 12.