Comparison of Bagging and Boosting Ensemble Machine Learning Methods for Automated EMG Signal Classification

Table 5

Comparison of the classification accuracies achieved by different studies using different datasets.

The study reference	Feature extraction method	Classifier	Classification accuracy (%)
[4]	AR + DWT	ANFIS	95
[5]	DWT	PSO-SVM	97.41
[13]	MUSIC	Combined neural network (CNN)	94
[11]	DWT	FSVM	97.67
[10]	DWT	Evolutionary SVM	97
[15]	AR	WNN	90.7
[21]	DWT	Bagging ensemble with SVM	99
[34]	Fuzzy k-means	SVM	86.14.
[35]	Peaks of MUAPs.	SVM	95.90
[36]	Time domain features	Adaptive fuzzy k-NN	93.5
[39]	CWT	Convolutional neural network	96.80
Proposed method	WPD	AdaBoost with RF	99.08