Non-obtrusive gait monitoring methods and systems for reducing risk of falling
AssigneeSHFT II ApS
InventorsTony MOTZFELDT, Stefan BARFRED, Micky KELAGER
Life of this patent
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Abstract
A method and system for dynamic, non-obtrusive monitoring of locomotion of a person using wearable sensor units includes motion sensors arranged to generate a sensor signal, and a wearable communication unit configured to process the sensor signal using a signal processing unit to extract and transmit biometric data to a mobile device that can analyze it using a machine learning-based risk prediction algorithm to identify patterns related to falling and thereby identify a fall event or calculate risk of falling of the person.
Claims21
1-15. (canceled)
A computer-implemented method for dynamic, non-obtrusive monitoring of locomotion of a person, the method comprising:
- obtaining, by a wearable communication unit, at least one sensor signal comprising a temporal sequence of sensor data from at least one wearable sensor unit arranged to measure locomotion of a person;
- processing, by a signal processing unit of the wearable communication unit, the sensor signal to extract biometric data relating to locomotion of the person;
- transmitting the biometric data to a mobile device;
- analyzing the biometric data, using a machine learning-based risk prediction algorithm executed on a processor of the mobile device or called by the processor of the mobile device from a remote server, to identify patterns related to falling of the person;
- and
- calculating risk of falling of the person based on the identified patterns.
A system for dynamic, non-obtrusive monitoring of locomotion of a person, the system comprising:
- at least one wearable sensor unit arranged to measure locomotion of a person and to generate a sensor signal comprising a temporal sequence of sensor data;
- a wearable communication unit configured to obtain a sensor signal, to process the sensor signal using a signal processing unit to extract biometric data relating to locomotion of the person, and to transmit the biometric data to a mobile device;
- and
- a mobile device comprising:
- a processor configured to analyze, using a machine learning-based risk prediction algorithm executed on the processor or called by the processor from a remote server, the biometric data to identify patterns related to falling and to calculate risk of falling of the person based on the identified patterns;
- and
- a user interface configured to present feedback to the person based on the calculated risk of falling.
Dependencies are inferred from the claim text.