Table 3. Classification accuracy results for classifiers: Random Forest (RF), Linear Support Vector (LSV) and Logistic Regression (LR).

Markers	Upper limb type (three classes)	Participants group (two classes)
FN	RF = 65%	RF = 88%
	LSV = 65%	LSV = 77%
	LR = 60%	LR = 88%
LEP	RF = 61%	RF = 89%
	LSV = 54%	LSV = 85%
	LR = 61%	LR = 85%
MPH	RF = 67%	RF = 96%
	LSV = 62.5%	LSV = 79%
	LR = 67%	LR = 83%
ACR	RF = 62.5%	RF = 80%
	LSV = 67%	LSV = 80%
	LR = 62.5%	LR = 84%
LEP, MPH	RF = 71%	RF = 99%
	LSV = 71%	LSV = 83%
	LR = 71%	LR = 92%
FN, LEP, MPH	RF = 60%	RF = 92%
	LSV = 60%	LSV = 84%
	LR = 60%	LR = 84%
LEP, MPH, ACR	RF = 68%	RF = 74%
	LSV = 77%	LSV = 83%
	LR = 73%	LR = 83%
FN, LEP, MPH, ACR	RF = 68%	RF = 91%
	LSV = 77%	LSV = 78%
	LR = 86%	LR = 87%