Brian Anthony Todd,John Vincenzo Capodilupo,Emily Rachel Capodilupo,William Ahmed
申请号：
US16778251
公开号：
US20200237262A1
申请日:
2020.01.31
申请国别(地区):
US
年份:
2020
代理人:
摘要：
A variety of techniques are used automate the collection and classification of workout data gathered by a wearable physiological monitor. The classification process is staged in order to correctly and efficiently characterize a workout type. Initially, a generalized workout event is detected using motion and heart rate data. Then a location of the monitor on a user is determined. An artificial intelligence engine can then be conditionally applied (if a workout is occurring and a suitable device location is detected) to identify the type of workout. In addition to improved speed and accuracy, a workout detection process implemented in this manner can be realized with a sufficiently small computational footprint for deployment on a wearable physiological monitor.
