Toward Restoration of Normal Mechanics of Functional Hand Tasks Post-Stroke: Subject-Specific Approach to Reinforce Impaired Muscle Function

Bioinspired High-Degrees of Freedom Soft Robotic Glove for Restoring Versatile and Comfortable Manipulation

The human hand is one of the most complex and compact grippers that has arisen as a product of natural genetic engineering; it is highly versatile, as it handles power and precision tasks. Since proper contact points and force directions are required to ensure versatility and secure a stable grip on an object, there must be a large workspace and controllable tip force directions for the digits. Although they are important, many individuals with neuromuscular diseases experience loss of these features. Thus, we propose a high-degree-of-freedom (DOF) soft robotic glove inspired by the anatomical features of human hands. The mechanism for adjusting the position and force direction of each tip is based on the structure of the extrinsic and intrinsic muscle-tendon units. The large thumb workspace was achieved by assisting opposition/reposition and flexion/extension to enable various grasping postures. A bidirectional actuation control mechanism with a cable-actuated agonist and an elastomer antagonist increased the assisted DOF and maintained compactness. The kinematic and kinetic performances of our device were evaluated by performing tests with eight stroke survivors. The thumb workspace increased by 43%, 207%, and 248% in the distal-proximal, dorsal-palmar, and radial-ulnar directions, respectively. The pinching shear force decreased by 54% and 45% for the nonthumb digits and thumb, respectively. These device-assisted improvements allowed objects to be stably grasped and manipulated in various postures. The novel device can assist individuals with impaired hand function to improve their grasping performance. Clinical Research Information Service (CRIS) Registration Number: KCT0004855.

Toward Hand Pattern Recognition in Assistive and Rehabilitation Robotics Using EMG and Kinematics

Wearable hand robots are becoming an attractive means in the facilitating of assistance with daily living and hand rehabilitation exercises for patients after stroke. Pattern recognition is a crucial step toward the development of wearable hand robots. Electromyography (EMG) is a commonly used biological signal for hand pattern recognition. However, the EMG based pattern recognition performance in assistive and rehabilitation robotics post stroke remains unsatisfactory. Moreover, low cost kinematic sensors such as Leap Motion is recently used for pattern recognition in various applications. This study proposes feature fusion and decision fusion method that combines EMG features and kinematic features for hand pattern recognition toward application in upper limb assistive and rehabilitation robotics. Ten normal subjects and five post stroke patients participating in the experiments were tested with eight hand patterns of daily activities while EMG and kinematics were recorded simultaneously. Results showed that average hand pattern recognition accuracy for post stroke patients was 83% for EMG features only, 84.71% for kinematic features only, 96.43% for feature fusion of EMG and kinematics, 91.18% for decision fusion of EMG and kinematics. The feature fusion and decision fusion was robust as three different levels of noise was given to the classifiers resulting in small decrease of classification accuracy. Different channel combination comparisons showed the fusion classifiers would be robust despite failure of specific EMG channels which means that the system has promising potential in the field of assistive and rehabilitation robotics. Future work will be conducted with real-time pattern classification on stroke survivors.

Subject-specific, Impairment-based Robotic Training of Functional Upper Limb Movements

Significant hand and upper-limb impairment is common post-stroke. Robotic training can administer a high-dose of repetitive movement training to stroke survivors, but its efficacy can be further improved by targeting specific impairments of individual patients. In this study, we developed a new robotic training protocol that identifies specific impairment patterns that degrade functional performance of individual patients and provide joint-specific assistance to counteract subject-specific impairments. The target tasks were also adjusted based on their task performance during training. Two chronic stroke survivors participated in a pilot training study to demonstrate the efficacy of the proposed impairment-based robotic training. Upper limb function of the participants was improved by the proposed training as shown in the clinical tests (6.5 ± 4.5 increase in Fugl-Meyer; 10 ± 6.9 increase in Action Research Arm Test), and the laboratory tests also showed improvement in their range of motion (hand) and voluntary reaching distance (arm). The impairment-based robotic training targeted (and improved) specific deficits of individual patients that hampered their task performance, which could have contributed to the observed functional improvement. The proposed training can enhance the rehabilitative outcome of robotic training by emphasizing the key components of effective rehabilitation, i.e., subject-specific, impairment-based training.Clinical Relevance- This study shows that impairment-based, 'subject-specific' robotic trainings can improve upper extremity function of stroke survivors.

Forelimb Cortical Stroke Reduces Precision of Motor Control in Mice

Background and Objective. Rodent models of stroke impairment should capture translatable features of behavioral injury. This study characterized poststroke impairment of motor precision separately from strength in an automated behavioral assay. Methods. We measured skilled distal forelimb reach-and-grasp motions within a target force range requiring moderate-strength. We assessed whether deficits reflected an increase in errors on only one or both sides of the target force range after photothrombotic cortical stroke. Results. Pull accuracy was impaired for 6 weeks after stroke, with errors redistributing to both sides of the target range. No decrease in maximum force was measured. Conclusions. This automated reach task measures sustained loss of motor precision following cortical stroke in mice.

Wireless Sensing of Lower Lip and Thumb-Index Finger 'Ramp-and-Hold' Isometric Force Dynamics in a Small Cohort of Unilateral MCA Stroke: Discussion of Preliminary Findings

Automated wireless sensing of force dynamics during a visuomotor control task was used to rapidly assess residual motor function during finger pinch (right and left hand) and lower lip compression in a cohort of seven adult males with chronic, unilateral middle cerebral artery (MCA) stroke with infarct confirmed by anatomic magnetic resonance imaging (MRI). A matched cohort of 25 neurotypical adult males served as controls. Dependent variables were extracted from digitized records of ‘ramp-and-hold’ isometric contractions to target levels (0.25, 0.5, 1, and 2 Newtons) presented in a randomized block design; and included force reaction time, peak force, and dF/dt_max associated with force recruitment, and end-point accuracy and variability metrics during the contraction hold-phase (mean, SD, criterion percentage ‘on-target’). Maximum voluntary contraction force (MVCF) was also assessed to establish the force operating range. Results based on linear mixed modeling (LMM, adjusted for age and handedness) revealed significant patterns of dissolution in fine force regulation among MCA stroke participants, especially for the contralesional thumb-index finger followed by the ipsilesional digits, and the lower lip. For example, the contralesional thumb-index finger manifest increased reaction time, and greater overshoot in peak force during recruitment compared to controls. Impaired force regulation among MCA stroke participants during the contraction hold-phase was associated with significant increases in force SD, and dramatic reduction in the ability to regulate force output within prescribed target force window (±5% of target). Impaired force regulation during contraction hold-phase was greatest in the contralesional hand muscle group, followed by significant dissolution in ipsilateral digits, with smaller effects found for lower lip. These changes in fine force dynamics were accompanied by large reductions in the MVCF with the LMM marginal means for contralesional and ipsilesional pinch forces at just 34.77% (15.93 N vs. 45.82 N) and 66.45% (27.23 N vs. 40.98 N) of control performance, respectively. Biomechanical measures of fine force and MVCF performance in adult stroke survivors provide valuable information on the profile of residual motor function which can help inform clinical treatment strategies and quantitatively monitor the efficacy of rehabilitation or neuroprotection strategies.