Table 6.

Comparison between this work and recent published references.

Methods	Sensor and Data		technique		System specification
	Sensor type	Data type	Preprocessing techniques	Recognitionalgorithm	Evaluation measures	Accuracy	R&A simultaneously
Proposed method	barometric sensor	air pressure	Threshold Filtering + Neighborhood filtering	SMR + AdaBoost-SVM	Accuracy F1-score	99.9%	yes
35	Pressure sensitive sheet	pressure image	CNN with Transfer Learning		Accuracy Confusion matrix	91.24%	no
34	FSR sensor	pressure image	HOG + LBP	FFANN	Accuracy Confusion matrix	97%	no
45	FSR sensor	pressure image	No feature extraction	Deep neural network	Accuracy	99.7%	no
44	FSR sensor	pressure image	spatio-temporal median filter	CNN	Accuracy	99.8%	no
46	FSR sensor	pressure image	Fuzzy representation	CNN	precision, recall, F1-score and accuracy	98.2%	NO
39	FSR sensor	pressure data	No feature extraction	Neural Network Bayesian Network	accuracy	97.1%	NO