Consumer Wi‐Fi device based action quality recognition: An illustrative example of seated dumbbell press action

Abstract A system called WiSDP, which is based on Wi‐Fi signals, to detect whether a Seated Dumbbell Press action is standard by using inexpensive consumer Wi‐Fi devices is proposed. Compared with the scheme based on high speed cameras and wearable sensors, Wi‐Fi devices are insensitive to light and colour, do not need wear any device, and decrease the risk of disclosing privacy. WiSDP senses environment changes through the Channel State Information which is fine‐grained physical layer information comparing to frequently used Received Signal Strength Indicator. Compared to the action recognition, action quality recognition depends on slight differences between a non‐standard action and standard actions, which makes it challenging. The authors propose an improved sliding window algorithm calculating action energy to extract Seated Dumbbell Press actions from the Channel State Information streams, estimate action quality by choosing an appropriate classifier and use Principal Component Analysis and Butterworth low‐pass filter to remove noise. The authors conduct experiments in two different scenarios and the average true positive rate of WiSDP are 94.66% and 95.11%, respectively.