Literature review of stroke assessment for upper-extremity physical function via EEG, EMG, kinematic, and kinetic measurements and their reliability

Abstract

Background Significant clinician training is required to mitigate the subjective nature and achieve useful reliability between measurement occasions and therapists. Previous research supports that robotic instruments can improve quantitative biomechanical assessments of the upper limb, offering reliable and more sensitive measures. Furthermore, combining kinematic and kinetic measurements with electrophysiological measurements offers new insights to unlock targeted impairment-specific therapy. This review presents common methods for analyzing biomechanical and neuromuscular data by describing their validity and reporting their reliability measures. Methods This paper reviews literature (2000–2021) on sensor-based measures and metrics for upper-limb biomechanical and electrophysiological (neurological) assessment, which have been shown to correlate with clinical test outcomes for motor assessment. The search terms targeted robotic and passive devices developed for movement therapy. Journal and conference papers on stroke assessment metrics were selected using PRISMA guidelines. Intra-class correlation values of some of the metrics are recorded, along with model, type of agreement, and confidence intervals, when reported. Results A total of 60 articles are identified. The sensor-based metrics assess various aspects of movement performance, such as smoothness, spasticity, efficiency, planning, efficacy, accuracy, coordination, range of motion, and strength. Additional metrics assess abnormal activation patterns of cortical activity and interconnections between brain regions and muscle groups; aiming to characterize differences between the population who had a stroke and the healthy population. Conclusion Range of motion, mean speed, mean distance, normal path length, spectral arc length, number of peaks, and task time metrics have all demonstrated good to excellent reliability, as well as provide a finer resolution compared to discrete clinical assessment tests. EEG power features for multiple frequency bands of interest, specifically the bands relating to slow and fast frequencies comparing affected and non-affected hemispheres, demonstrate good to excellent reliability for populations at various stages of stroke recovery. Further investigation is needed to evaluate the metrics missing reliability information. In the few studies combining biomechanical measures with neuroelectric signals, the multi-domain approaches demonstrated agreement with clinical assessments and provide further information during the relearning phase. Combining the reliable sensor-based metrics in the clinical assessment process will provide a more objective approach, relying less on therapist expertise. This paper suggests future work on analyzing the reliability of metrics to prevent biasedness and selecting the appropriate analysis.

Non-Surgical Lower-Limb Rehabilitation Enhances Quadriceps Strength in Inpatients with Hip Fracture: A Study on Force Capacity and Fatigue

“…The use of instrumented multi-domain measurements (such as EMG, force, NIRS, kinematics) might help in understanding the complex process underlying motor recovery in rehabilitation [28]. Multi-domain approaches, in particular, may help in providing a wide spectrum of assessments that might be complementary or provide information of different nature [41,42]. Future works will contextualize the presented data with a broader view also including the acquired TD NIRS data for a complete multi-domain approach aiming at characterizing patients' motor functionality.…”

A review of combined functional neuroimaging and motion capture for motor rehabilitation

“…Traditional motor rehabilitation primarily focuses on continuously analyzing movement biomechanics and providing feedback on the quality. During the initial physical examination, these biomechanical assessments are crucial for selecting the most effective treatment strategy and determining a probable prognosis [ 16 ]. In the subsequent rehabilitation, biomechanical measures assist in building muscle strength and mobility by evaluating functional changes and providing corrective feedback.…”

“…Nevertheless, recent reviews investigated the fusion of functional neuroimaging and electromyography (EMG), as well as biomechanical measurements and EMG. [ 16 , 32 , 33 ]. Combined EMG/EEG measures, such as corticomuscular coherence (CMC) representing corticospinal synchronization, correlate with motor improvement.…”

Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients

“…, clinical/functional, biomechanical, and neurophysiological) to provide a comprehensive description of the response to a specific treatment, 10 and design interventions based on an individual’s needs. Indeed, while several studies investigated neural and biomechanical biomarkers of the recovery, 11 rarely the attention have been focused on the changes of brain responses at different post-stroke phases. Additionally, how the dosage and duration of rehabilitation is entangled with the time from stroke event is still a matter of debate.…”

“… 25 - 27 A richer picture of the patient’s motor status can be drawn by concomitantly assessing clinical, biomechanical and neurophysiological markers, that features from single domains may not be able to capture. 11 For example, a multimodal approach to post-stroke recovery assessment may correctly identify compensatory behavior, whereas single domain features may not. 26 …”