In this paper our objective is to analyze the cortico-muscular coupling for hand finger motion and its possible use in the control of an exoskeleton based neurorehabilitation system for stroke sufferers. Cortical activity alone is often not sufficient to reliably control a device such as an exoskeleton and hence, our focus is to ascertain and analyze the connectivity between the motor cortex and forearm muscles, controlling the fingers, in terms of coherence between electroencephalogram (EEG) and electromyogram (EMG) signals. We have analyzed the signals separately for three different kinds of exercises consisting of passive motion of fingers using exoskeleton, active motion without any assistance, and motor imagery of the same movements. Four out of six healthy subjects who participated in the experiments have shown significant (p<;0.01) coherence for active finger motion which is well distinguished from the rest state. The EEG analysis resulted in average accuracy of 69.17% for passive finger motion with exoskeleton, 71.25% for active finger motion, and 67.92% for motor imagery, in detecting the volitional intention of the subjects to move their fingers. These results support that EEG-EMG coherence along with EEG analysis has the potential to make a more effective neurorehabilitation system for finger movement restoration of stroke sufferers.

This paper presents an underactuated design of a robotic hand exoskeleton, and a challenge based neurorehabilitation strategy. The exoskeleton is designed to reproduce natural human fingertip paths during extension and grasping, keeping minimal kinematic complexity. It facilitates an impedance adaptation based trigged assistance control strategy by switching between active non-assist and passive assistance modes. In the active non-assist mode, the exoskeleton motion follows the applied fingertip forces based on an impedance model. If the applied fingertip forces are inadequate, the passive assistance mode is triggered. The impedance parameters are updated at regular intervals based on the user performance, to implement a challenge based rehabilitation strategy. A six-week long hand therapy, conducted on four chronic stroke patients, resulted in significant (p-value<0.05) increase in force generation capacity and decrease (p-value<0.05) in the required assistance. Also, there was a significant (p-value<0.05) increase in the system impedance parameters which adequately challenged the patients. The change in the Action-Research-Arm-Test (ARAT) scores from baseline was also found to be significant (p-value<0.05) and beyond the minimal clinically important difference (MCID) limit. Thus the results prove that the proposed control strategy with has the potential to be a clinically effective solution for personalized rehabilitation of poststroke hand functionality.

People suffering from a variety of upper and lower limb disabilities due to different neuro-muscular diseases or injuries, often find it difficult to perform day-today activities of mobility and grasping (pick and place) objects. This paper presents the feasibility and utility of a newly developed assistive device named EMOHEX, for disabled people to perform some activities of daily living (ADL). EMOHEX is an integrated platform that combines a low cost eye-tracking device with a powered-wheelchair mounted hand-exoskeleton, which can assist disabled people in grasping objects while moving around. A dual control panel based graphical user interface is designed wherein the user's intention to select any command button is detected through eye-tracking. The dual control consists of wheelchair control panel and exoskeleton control panel, which are interchangeable by a switch button common to both the panels. The hand-exoskeleton is capable of assisting grasp, hold, and release action. Experiments conducted on 16 healthy participants revealed that performance metrics were significantly (p<0.01) similar for the same task complexity while for different task complexities the performance metrics were significantly (p<0.01) different across all the participants. These results showed the feasibility and stability of the system, respectively. Moreover, the information transfer rate (ITR) of eye-tracker was found satisfactory at 55.28±1.29 bits/min and 51.02±1.72 bits/min for simple and complex task, respectively. Thus, EMOHEX has the potential as a quality assistive device for disabled people.

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A three-finger exoskeleton is designed and controlled to translate and or rotate a slender object held between the fingertips. Each finger exoskeleton comprises of three serially concatenated planar external four-bar linkages, all on one plane, except for the thumb exoskeleton, for which one linkage is out of plane. Linkages are constrained to be on the dorsal side (sagittal plane) of each finger. To design each linkage, when performing coordinated translation and rotation, trajectories of all phalanges of the index and middle fingers and the thumb are obtained through video capture and post-processing that involves coordinate transformation. Optimal kinematic synthesis for each linkage is then performed via the three accuracy point method coupled with a stochastic search algorithm. Post manufacturing, the exoskeleton is mounted on the dorsal side of the hand using Velcro bands. Fastening is accomplished on each phalanx, palm and forearm via a fixture designed to house all three exoskeletons. Nine micro-servo motors are employed for actuation. To perform coordinated translation and rotation tasks, trajectory following is accomplished using open loop position control, incorporating artificial neural network to convert known finger joint angles into the required driving link angles. Based on experimental tests conducted, the exoskeleton is found to be successful in reproducing the requisite finger motions involved in coordinated object manipulation.