A supervised approach to automatically extract a set of rules to support fall detection in an mHealth system
A cheap and portable approach to detect fall detection in real time is proposed. Acceleration data are gathered by a wearable sensor and sent to a mobile device. A set of IF-THEN rules is automatically extracted from acceleration data. This set of rules can be used in our real-time mobile monitoring system. If occurrence of a fall is detected by a rule, an alarm is automatically produced.
mhealth system if-then rules fall recording knowledge extraction real-time monitoring