Effect of Sensory Loss on Improvements of Upper-Limb Paralysis Through Robot-Assisted Training: A Preliminary Case Series Study

Kinematic analysis of movement patterns during a reach-and-grasp task in stroke patients

Background

This study aimed to evaluate the kinematic movement patterns during a reach-and-grasp task in post-stroke patients according to the upper extremity impairment severity.

Methods

Subacute stroke patients (n = 46) and healthy controls (n = 20) were enrolled in this study. Spatiotemporal and kinematic data were obtained through 3D motion analysis during the reach-and-grasp task. Stroke patients were grouped using the Fugl-Meyer Assessment (FMA) scale, and a comparison of the groups was performed.

Results

The severe group showed a significantly longer movement time, lower peak velocity, and higher number of movement units than the mild group during the reach-and-grasp task (p < 0.05). Characteristic compensatory movement patterns, such as shoulder abduction, thoracic posterior tilting, and upward and external rotation were significantly greater during the forward transporting phase in the severe group than in the mild group (p < 0.05). The FMA score was significantly associated with the movement time during the forward transporting phase, number of movement units during the reaching phase, range of shoulder abduction-adduction and wrist flexion-extension movements during the reaching phase, and range of thoracic internal-external rotation during the backward transporting phase (p < 0.05).

Conclusion

Post-stroke patients have unique spatiotemporal and kinematic movement patterns during a reach-and grasp-task according to the impairment severity.

Current Topics in Technology-Enabled Stroke Rehabilitation and Reintegration: A Scoping Review and Content Analysis

BACKGROUND

There is a worldwide health crisis stemming from the rising incidence of various debilitating chronic diseases, with stroke as a leading contributor. Chronic stroke management encompasses rehabilitation and reintegration, and can require decades of personalized medicine and care. Information technology (IT) tools have the potential to support individuals managing chronic stroke symptoms.

OBJECTIVES

This scoping review identifies prevalent topics and concepts in research literature on IT technology for stroke rehabilitation and reintegration, utilizing content analysis, based on topic modelling techniques from natural language processing to identify gaps in this literature.

ELIGIBILITY CRITERIA

Our methodological search initially identified over 14,000 publications of the last two decades in the Web of Science and Scopus databases, which we filter, using keywords and a qualitative review, to a core corpus of 1062 documents.

RESULTS

We generate a 3-topic, 4-topic and 5-topic model and interpret the resulting topics as four distinct thematics in the literature, which we label as Robotics, Software, Functional and Cognitive. We analyze the prevalence and distinctiveness of each thematic and identify some areas relatively neglected by the field. These are mainly in the Cognitive thematic, especially for systems and devices for sensory loss rehabilitation, tasks of daily living performance and social participation.

CONCLUSION

The results indicate that IT-enabled stroke literature has focused on Functional outcomes and Robotic technologies, with lesser emphasis on Cognitive outcomes and combined interventions. We hope this review broadens awareness, usage and mainstream acceptance of novel technologies in rehabilitation and reintegration among clinicians, carers and patients.

Posterior parietal cortex contributions to cross-modal brain plasticity upon sensory loss

Sensory loss causes compensatory behavior, like echolocation upon vision loss or improved visual motion detection upon deafness. This is enabled by recruitment of the deprived cortical area by the intact senses. Such cross-modal plasticity can however hamper rehabilitation via sensory substitution devices. To steer rehabilitation towards the desired outcome for the patient, having control over the cross-modal take-over is essential. Evidence accumulates to support a role for the posterior parietal cortex (PPC) in multimodal plasticity. This area shows increased activity after sensory loss, keeping similar functions but driven by other senses. Patient-specific factors like stress, social situation, age and attention, have a significant influence on the PPC and on cross-modal plasticity. We propose that understanding the response of the PPC to sensory loss and context is extremely important for determining the best possible implant-based therapies, and that mouse research holds potential to help unraveling the underlying anatomical, cellular and neuromodulatory mechanisms.