LSGDM with Biogeography-Based Optimization (BBO) Model for Healthcare Applications

Table 1

Result analysis of MR-LSDGM technique under different runs.

No. of runs	Methods	Sensitivity	Specificity	Precision	Accuracy	F-score
Run-1	Walk	0.994	1.000	1.000	0.999	0.997
	Up	0.985	0.997	0.985	0.995	0.985
	Down	0.988	0.998	0.986	0.996	0.987
	Sit	0.910	0.989	0.943	0.976	0.926
	Std	0.951	0.981	0.918	0.976	0.934
	Lay	1.000	1.000	1.000	1.000	1.000
	Average	0.971	0.994	0.972	0.990	0.972
Run-2	Walk	0.998	1.000	1.000	1.000	0.999
	Up	0.989	0.998	0.992	0.997	0.990
	Down	0.991	0.998	0.991	0.997	0.991
	Sit	0.919	0.991	0.952	0.979	0.935
	Std	0.959	0.983	0.926	0.979	0.942
	Lay	1.000	1.000	1.000	1.000	1.000
	Average	0.976	0.995	0.977	0.992	0.976
Run-3	Walk	0.998	1.000	1.000	1.000	0.999
	Up	0.983	0.998	0.991	0.996	0.987
	Down	0.991	0.998	0.986	0.997	0.988
	Sit	0.915	0.989	0.943	0.977	0.929
	Std	0.953	0.981	0.919	0.976	0.935
	Lay	0.996	1.000	1.000	0.999	0.998
	Average	0.973	0.994	0.973	0.991	0.973
Run-4	Walk	0.998	1.000	1.000	1.000	0.999
	Up	0.985	0.998	0.992	0.996	0.988
	Down	0.991	0.998	0.988	0.997	0.989
	Sit	0.917	0.989	0.945	0.977	0.931
	Std	0.955	0.982	0.922	0.977	0.938
	Lay	0.998	1.000	1.000	1.000	0.999
	Average	0.974	0.995	0.975	0.991	0.974
Run-5	Walk	0.998	1.000	1.000	1.000	0.999
	Up	0.985	0.998	0.989	0.996	0.987
	Down	0.988	0.998	0.988	0.997	0.988
	Sit	0.923	0.989	0.942	0.978	0.932
	Std	0.951	0.983	0.923	0.977	0.937
	Lay	0.994	1.000	1.000	0.999	0.997
	Average	0.973	0.995	0.974	0.991	0.973