TABLE VI.

Comparison of PS Classification and EE Estimation Results of Our Proposed Method with Other Similar Studies (RF: Random Forest; LMT: Logistic Model Tree; Inertial sensor includes 3D sensing unit: accelerometers, magnetometers, and gyroscopes; All acceloremeter sensors were 3-D)

Comparison of PS Classification Results
Year	Reference	Used Sensors	Accuracy(%)	Algorithm	Sensor Place	Device
2016	[117]	ACC	81	NN	Wrist	Wrist-mounted 3-D Accelerometers
2015	[118]	ACC,Gyroscope	85	LMT	Neck	MinimaxX S4
2016	[119]	Inertial Sensor	97	DT	Shoes	Physilog Gait Up
2015	[120]	Inertial Sensor	95	k-NN	Wrist, Ankle, Trunk	ReSense
2020	[35]	ACC	95	RF	Hip	ActiGraph
2020	[38]	ACC	93	DL	—	Smart Phone
2020	[37]	ACC	89	SVM	Hip and Thigh	GT3X+ and GT9X
2020	[36]	ACC, BVP, HR	92	RF	Hip and Wrist	Microsoft Band, ADXL335
—	Proposed Method	ACC, HR, ST, GSR, BVP	95	LSTM-DL	Wrist	Empatica E4
—	Proposed Method	ACC (Using only ACC)	90	LSTM-DL	Wrist	Empatica E4
Comparison of EE Estimation Results
Year	Reference	Used Sensors	MAE (MET)	MAPE (%)	RMSE (MET)	Device
2015	[50]	ACC, HR, NB	0.52	23.2	—	Zephyr, Shimmer2, BodyMedia Fit
2014	[51]	ACC, ECG	0.70	25.7	—	ADXL330 and five ECG Necklace
2015	[52]	ACC, HR, ST	0.87	32.8	—	BodyMedia FIT
2015	[53]	ACC, HR, RR	0.61	27.5	—	BodyMedia Fit, Zephyr, Shimmer
2015	[54]	ACC	0.31	—	—	LIS3L02AQ3 Sensor Data
2014	[55]	ACC, HR	—	—	1.0	ActiGraph GT3X+, Polar RS400
2020	[56]	HR	—	—	0.71	Suunto Smart Belt
2020	[57]	HR	—	16.8	—	Misfit Shine 2
—	Proposed Method	ACC, HR, ST, GSR, BVP	0.25	12.1	0.51	Empatica E4
—	Proposed Method	ACC (Using only ACC)	0.59	22.0	0.79	Empatica E4