Table 4. Classification results of three classifiers using the acceleration sensor placed on the chest.

	KNN (K = 3)			Rotation Forest			Neural Network
Activity	Precision	Recall	F-measure	Precision	Recall	F-measure	Precision	Recall	F-measure
A1	0.988	0.930	0.958	0.985	0.977	0.981	0.976	0.938	0.956
A2	0.873	0.802	0.836	0.917	0.893	0.905	0.699	0.791	0.742
A3	0.839	0.758	0.796	0.838	0.930	0.882	0.729	0.665	0.696
A4	0.916	0.476	0.626	0.952	0.966	0.959	0.855	0.913	0.883
A5	0.221	0.968	0.359	0.996	0.957	0.976	0.974	0.957	0.965
A6	0.981	0.860	0.916	0.958	0.972	0.965	0.979	0.871	0.922
A7	0.979	0.658	0.787	0.974	0.925	0.949	0.886	0.807	0.845
A8	0.943	0.883	0.912	0.942	0.927	0.935	0.829	0.874	0.851
A9	0.985	0.833	0.903	0.976	0.883	0.927	0.950	0.845	0.895
A10	0.893	0.822	0.856	0.928	0.923	0.925	0.858	0.900	0.878
A11	0.881	0.798	0.838	0.902	0.938	0.920	0.824	0.904	0.862
A12	1.000	0.613	0.760	0.993	0.944	0.968	0.977	0.894	0.934
Average	0.891	0.771	0.805	0.940	0.938	0.939	0.864	0.860	0.861