Altered Corticomuscular Coherence (CMCoh) Pattern in the Upper Limb During Finger Movements After Stroke

Background: Proximal compensation to the distal movements is commonly observed in the affected upper extremity (UE) of patients with chronic stroke. However, the cortical origin of this compensation has not been well-understood. In this study, corticomuscular coherence (CMCoh) and electromyography (EMG) analysis were adopted to investigate the corticomuscular coordinating pattern of proximal UE compensatory activities when conducting distal UE movements in chronic stroke.

Method: Fourteen chronic stroke subjects and 10 age-matched unimpaired controls conducted isometric finger extensions and flexions at 20 and 40% of maximal voluntary contractions. Electroencephalogram (EEG) data were recorded from the sensorimotor area and EMG signals were captured from extensor digitorum (ED), flexor digitorum (FD), triceps brachii (TRI), and biceps brachii (BIC) to investigate the CMCoh peak values in the Beta band. EMG parameters, i.e., the EMG activation level and co-contraction index (CI), were analyzed to evaluate the compensatory muscular patterns in the upper limb.

Result: The peak CMCoh with statistical significance (P < 0.05) was found shifted from the ipsilesional side to the contralesional side in the proximal UE muscles, while to the central regions in the distal UE muscle in chronic strokes. Significant differences (P < 0.05) were observed in both peak ED and FD CMCohs during finger extensions between the two groups. The unimpaired controls exhibited significant intragroup differences between 20 and 40% levels in extensions for peak ED and FD CMCohs (P < 0.05). The stroke subjects showed significant differences in peak TRI and BIC CMCohs (P < 0.01). No significant inter- or intra-group difference was observed in peak CMCoh during finger flexions. EMG parameters showed higher EMG activation levels in TRI and BIC muscles (P < 0.05), and higher CI values in the muscle pairs involving TRI and BIC during all the extension and flexion tasks in the stroke group than those in the control group (P < 0.05).

Conclusion: The post-stroke proximal muscular compensations from the elbow to the finger movements were cortically originated, with the center mainly located in the contralesional hemisphere.

Finger Angle Estimation From Array EMG System Using Linear Regression Model With Independent Component Analysis

Surface ElectroMyoGraphy (EMG) signals from the forearm used in prosthetic hand and finger control systems require precise anatomy data of finger muscles that are small and located deep within the forearm. The main problem of this method is that the signal quality depends on the placement of EMG sensor, which can significantly affects the accuracy and precision to estimate joint angles or forces. Moreover, in case of amputees, the location of finger muscles is unknown and needed to be identified manually for EMG recording. As a result, most modern prosthetic hands utilize limited number of muscles with pattern recognition to control finger according to pre-defined grip which is unable to mimic natural finger motion. To address such issue, we used array EMG sensors to obtain EMG signals from all possible positions on the forearm and applied regression method to produce natural finger motion. The signals were analyzed using independent component analysis (ICA) to find the best-fitted independent component (IC) that matches the anatomical data taken after the experiment. Next, from the IC and EMG signals, finger angles were estimated using linear regression model (LRM). Each finger was assigned EMG and IC component for flexion and extension muscles, to assess the possibility of controlling each finger angle separately. We compared the joint angles of each finger between calculated from IC and EMG by correlation coefficients (CC) for all fingers. The average CC values were higher than 0.7, demonstrating the strength of the linear relationship. The different between IC and EMG methods suggests that the IC method can reduce noise and increase the signal to noise ratio. The performance of ICA method showed higher CC value at around 0.2 ± 0.10. In order to confirm the performance of ICA method, we also tested mathematical musculoskeletal model (MSM). The result from this study showed that not only array EMG sensors with ICA significantly improve the quality of signal detected from forearm but also reduce problems of conventional EMG sensors and consequently improve the performance of regression method to imitate natural finger motion.

Influence of Wrist Position on the Metacarpophalangeal Joint Motion of the Index Through Small Finger

BACKGROUND

The metacarpophalangeal joints exhibit range of motion that is influenced by wrist position. Synergistic motion occurs between the wrist and the metacarpophalangeal joints with different static wrist positions affecting joints' motion capability. The aim of this study was to determine how different wrist positions influence the active range of motion of the index through small finger metacarpophalangeal joints.

METHODS

The active range of motion of the index through small finger metacarpophalangeal joints of 31 healthy subjects was measured in flexion/extension and radial/ulnar deviation in 5 different flexion/extension wrist positions, using biaxial electrogoniometers.

RESULTS

There was a difference in range of motion of all fingers depending on the wrist position. The minimum metacarpophalangeal joint range of motion was found in 80° wrist extension, the maximum in neutral wrist position. For the index finger, flexion/extension was 84.7° (±8.6°) to 25.9° (±10.2°) and radial/ulnar deviation was 32.1° (±11.3°) to 22.6° (±12.8°). For the middle finger, flexion/extension was 84.8° (±8.5°) to 25.9° (±10.1°) and radial/ulnar deviation 28.8° (±11.1°) to 22.1° (±8.9). The fourth finger showed a range of motion for flexion/extension of 87.2° (±11.5°) to 22.8° (±11.6°) and radial/ulnar deviation of 8.1° (±5.8°) to 32.3° (±12.4°). The highest range of motion was measured at the fifth finger with flexion/extension of 84.0° (±8.6°) to 32.1°(±16.8°) and radial/ulnar deviation of 15.1° (±12.9°) up to 54.6° (±18.7°).

CONCLUSIONS

The range of motion of the index through small finger metacarpophalangeal joints was significantly influenced by wrist position. The highest metacarpophalangeal joint range of motion of all fingers was conducted in neutral wrist positions. Apart from ergonomic implications, we conclude that metacarpophalangeal joint motion should be assessed under standardized wrist positions.

Median nerve movement in the carpal tunnel before and after carpal tunnel release using transverse ultrasound

PURPOSE

We aimed to compare the movement of the median nerve within the carpal tunnel during wrist and finger motions between before and after carpal tunnel release (CTR) using transverse ultrasound in carpal tunnel syndrome (CTS) patients and to evaluate the biomechanical efficacy of CTR for CTS.

METHODS

Twenty-four patients with CTS were examined by transverse ultrasound. The location of the median nerve within the carpal tunnel was examined quantitatively as a coordinate at varied wrist positions with finger extension and flexion, respectively, before and after CTR.

RESULTS

We found that the median nerve moved statistically significantly more palmarly after CTR than before at all wrist positions during finger motion. The average median nerve displacement toward the palmar side at the palmar flexion position in finger flexion was the greatest among all positions. Additionally, the displacement amounts of the median nerve during finger motion at all wrist positions were statistically significantly smaller after CTR than before.

CONCLUSIONS

The current study demonstrated the movement patterns of the median nerve in the carpal tunnel during wrist and finger motions compared before and after CTR using transverse ultrasound in CTS patients. The findings suggested that as the median nerve shifted greatly palmarly away from the tendons after CTR, the nerve avoids compression or shearing stress from the tendons. This ultrasound information could offer further understanding of the pathomechanics of CTS and provide a more accurate diagnosis of CTS and better treatment by CTR.

Biomechanical evaluation of wrist-driven flexor hinge orthosis in persons with spinal cord injury

The wrist-driven flexor hinge orthosis (WDFHO) is a device used to restore hand function in persons with tetraplegic spinal cord injury by furnishing three-point prehension. We assessed the effectiveness and biomechanical properties of the WDFHO in 24 persons with cervical 6 or 7 tetraplegia who have severely impaired hand function. This study introduces a mechanical operating model to assess the efficiency of the WDFHO. Experimental results showed that pinch force increased significantly (p < 0.001) after using the WDFHO and was found to positively correlate with the strength of wrist extensor muscles (r = 0.41, p < 0.001). However, when the strength of the wrist extensors acting on the WDFHO was greater, the reciprocal wrist and finger motion that generates three-point prehension was less effective (r = 0.79, p < 0.001). Reliable and valid biomechanical evaluation of the WDFHO could improve our understanding of its biomechanics.