Mechanomyographic response during FES in healthy and paraplegic subjects

Analysis of Skin Deformation Differences on the Upper Arm Between Active and Passive Movements During Elbow Flexion and Extension

The motion ability of patients in the acute phase of stroke is difficult to define with existing indexes such as the Brunnstrom stage. Hence, for designing a novel evaluation index for stroke rehabilitation in the acute phase, we focused on the differences between the skin deformations in active and passive movements. Skin deformation reflects the activities of body tissues that are related to motion ability. We measured skin deformations on the upper arm in active and passive movements during elbow flexion and extension and extracted features from these deformations. For practical rehabilitation applications, we developed a novel flexible distance sensor array to reduce the time needed for attaching sensors to patients. Using principal component analysis (PCA), the skin deformation could be decomposed into joint movements and activeness of movements as the first two components (PC1 and PC2). The joint angle and PC1 exhibited a high correlation, and the standard deviation (SD) of PC2 indicated a significant difference in the types of movements. From the above results, we concluded that the SD ratio between PC2 and PC1 may be used to evaluate motion ability considering the inherent biomechanical characteristics.

Interfaces with the peripheral nervous system for the control of a neuroprosthetic limb: a review

The field of prosthetics has been evolving and advancing over the past decade, as patients with missing extremities are expecting to control their prostheses in as normal a way as possible. Scientists have attempted to satisfy this expectation by designing a connection between the nervous system of the patient and the prosthetic limb, creating the field of neuroprosthetics. In this paper, we broadly review the techniques used to bridge the patient's peripheral nervous system to a prosthetic limb. First, we describe the electrical methods including myoelectric systems, surgical innovations and the role of nerve electrodes. We then describe non-electrical methods used alone or in combination with electrical methods. Design concerns from an engineering point of view are explored, and novel improvements to obtain a more stable interface are described. Finally, a critique of the methods with respect to their long-term impacts is provided. In this review, nerve electrodes are found to be one of the most promising interfaces in the future for intuitive user control. Clinical trials with larger patient populations, and for longer periods of time for certain interfaces, will help to evaluate the clinical application of nerve electrodes.

Correlation between mechanomyography features and passive movements in healthy and paraplegic subjects

Mechanomyography (MMG) measures both muscular contraction and stretching activities and can be used as feedback in the control of neuroprostheses with Functional Electrical Stimulation (FES). In this study we evaluated the correlation between MMG features and passive knee angular movement of rectus femoris and vastus lateralis muscles acquired from healthy volunteers (HV) and spinal cord injured volunteers (SCIV). Twelve HV and thirteen SCIV were submitted to passive and FES elicited knee extensions and in each extension, eleven windows of analysis with 0.5s length were inspected. Temporal (RMS and INT) and frequency (MF and μ3) features were extracted. Spearman correlation coefficients (p) were computed in order to check correlations between the features obtained from both MMG sensors. The correlation between MMG(MF) and MMG temporal analysis (RMS and INT) to HV was classified as positive, moderate (p from 0.635 to 0.681) and high (p from 0.859 to 0.870), and weak (positive e negative) to SCIV. These results differ from those obtained in voluntary contraction or artificially evoked by functional electrical stimulation and may be relevant in applications with closed loop control systems.