A Deep Learning Approach for Table Tennis Forehand Stroke Evaluation System Using an IMU Sensor

Table 4

Basic information of the dataset.

Dataset	Strokes’ name	Samples’ number	Percentage	Feature size
(1) Sensory data	Basic	740	48%
	Topspin	393	26%
	Push	392	26%
	Total	1525	100%
(2) Quality scores	Criteria’s name	Criteria’s number	—	Range of scores value
	C1	1525	—	(0–100)%
	C2
	C3
	C4
	C5
(3) Labels	Labels’ name	Labels’ number	—	Percentage
	B	740	—	48%
	T	393		26%
	P	392		26%