Table 2.

Sampling of recent work in the detection of patient intent for robotic upper-limb stroke rehabilitation

Paper	Device	Intent Detection					Movement type			Subject testing
		Signal Type	Triggered	Continuous move/rest	Continuous proportional velocity	Point- to- point	Continuous	Unconstrained	Validation with healthy subjects	Validation with impaired subjects	Validation in simulation
[19]	MIT-Manus (2D planar endpoint manipulator)	Velocity or EMG	*			*					*
[38]	Gentle/G (3-dof grasp robot)	Force	*			*
[75]	ARM Guide (1-dof linear reaching)	Velocity	*			*				1
[49]	ARM Guide (1-dof linear reaching)	Displacement	*			*				19
[76•]	ARMin III (7-dof arm exoskeleton)	Gaze duration and velocity	*			*			*
[77]	NEUROExos (1-dof elbow exoskeleton)	EMG			*		*		10
[78•]	1-dof wrist flexion/ extension	EMG			*	*				16
[79]	1-dof elbow exoskeleton	EMG	*					*	1
[80]	1-dof elbow exoskeleton	EMG			*			*		8
[28••]	AssistOn-Mobile (2D planar arm motions)	EEG			*		*		1
[81]	MIT-Manus (2D planar endpoint manipulator)	EEG	*			*				8
[82•]	L-Exos (4-dof arm exoskeleton) and EEG	Eye tracking and EEG		*		*			3	4
[83]	MIT-Manus (2D planar endpoint manipulator)	EEG	*			*				25
[84]	Barrett WAM (7-dof robot arm) for endpoint control	EEG		*		*			6	3
[85•]	MAHI Exo-II (4-dof elbow/wrist exoskeleton)	EEG	*			*			3	1

In the subject testing columns, numbers indicate number of subjects tested, if known