Functional MRI Assessment of Brain Activity During Hand Rehabilitation with an MR-Compatible Soft Glove in Chronic Stroke Patients: A Preliminary Study.

Brain plasticity plays a significant role in functional recovery after stroke, but the specific benefits of hand rehabilitation robot therapy remain unclear. Evaluating the specific effects of hand rehabilitation robot therapy is crucial in understanding how it impacts brain activity and its relationship to rehabilitation outcomes. This study aimed to investigate the brain activity pattern during hand rehabilitation exercise using functional magnetic resonance imaging (fMRI), and to compare it before and after 3-week hand rehabilitation robot training. To evaluate it, an fMRI experimental environment was constructed to facilitate the same hand posture used in rehabilitation robot therapy. Two stroke survivors participated and the conjunction analysis results from fMRI scans showed that patient 1 exhibited a significant improvement in activation profile after hand rehabilitation robot training, indicative of improved motor function in the bilateral motor cortex. However, activation profile of patient 2 exhibited a slight decrease, potentially due to habituation to the rehabilitation task. Clinical results supported these findings, with patient 1 experiencing a greater increase in FMA score than patient 2. These results suggest that hand rehabilitation robot therapy can induce different brain activity patterns in stroke survivors, which may be linked to patient-specific training outcomes. Further studies with larger sample sizes are necessary to confirm these findings.

EEG-EMG hybrid real-time classification of hand grasp and release movements intention in chronic stroke patients.

Rehabilitation of the hand motor function is essential for stroke patients to resume activities of daily living. Recent studies have shown that wearable robot systems, like a multi degree-of-freedom soft glove, have the potential to improve hand motor impairment. The rehabilitation system, which is intuitively controlled according to the user's intention, is expected to induce active participation of the user and further promote brain plasticity. However, due to the patient-specific nature of stroke patients, extracting the intention from stroke patients is still challenging. In this study, we implemented a classifier that combines EEG and EMG to detect chronic stroke patients' four types of intention: rest, grasp, hold, and release. Three chronic stroke patients participated in the experiment and performed rest, grasp, hold, and release actions. The rest vs. grasp binary classifier and release vs. hold binary classifier showed 76.9% and 86.6% classification accuracy in real-time, respectively. In addition, patient-specific accuracy comparisons showed that the hybrid approach was robust to upper limb impairment level compared to other approaches. We believe that these results could pave the way for the development of BCI-based robotic hand rehabilitation therapy.

Biomimetic finger extension mechanism for soft wearable hand rehabilitation devices.

For the rehabilitation and assistance of the hand functions, wearable devices have been developed, and the interest in tendon driven mechanisms have especially increased since it allows light weight and compact design. The tendon driven hand rehabilitation devices provides grasping force via exo-tendons routed on the dorsal and palmar sides of the hand pulled by remotely located actuators. However, most of the devices were not able to provide natural joint extension sequence of the finger and showed hyperextension of finger joints because the tendons for extension were fixed at the fingertip, concentrating the torque at the distal interphalangeal joint. In this study, a ring-type biomimetic finger extension mechanism was developed, which mimics the origin, structure, and orientation of the extensor tendon. The biomimetic mechanism was evaluated by comparing the motion with voluntary finger extension and the motion made by other conventional tendon driven finger extension mechanisms. The biomimetic extension mechanism provided the same joint extension sequence with voluntary finger extension, and the fully extended posture was most close to the voluntary finger extension among the tendon-driven mechanisms used in the experiments. The joint angle differences between the proposed tendon mechanism and the voluntary finger extension was -1.2 °±3.4 °, -2.9°±2.0°, and -3.1°±8.0° for distal phalangeal, proximal phalangeal, and metacarpo-phalangeal joint, respectively.