Detection of Human Stress Using Optimized Feature Selection and Classification in ECG Signals

Table 3

Performance and comparison results of the proposed system with conventional works.

References	Methodology	Experimental results in %
		Precision	Recall	Accuracy	F1 score
Proposed		92.78	91.56	92.43	95.86
[7]	FCM clustering	87.65	86.32	87.39	89.39
[8]	Convolutional neural networks	86.23	85.56	90.19	91.50
[9]	Long short-term memory (LSTM) network	85.18	86.49	88.13	89.16
[10]	Frequency analysis	73.98	74.12	75	76.30
[11]	Heart-rate variability (HRV) correlation analysis	87.06	88.10	89	91
[12]	Convolutional neural networks	60.72	62.59	63.97	68.23
[13]	Deep ECGNet	80.35	81.79	82.7	85.26
[14]	SVM and ANN	88.26	88.79	89.21	89.96
[15]	Minimum redundancy maximum relevance (mRMR) selection algorithm	82.52	83.3	84.4	85.23