Artificial Motor Control For Electrically Stimulated Upper Limbs Of Plegic Or Paretic People

Functional Electrical Stimulation (FES) is a technique used in the restoration and generation of movements performed by subjects with neuromuscular disorders such as spinal cord injury (SCI). The purpose of this article is to outline the state of the art and perspectives of the use of FES in artificial motor control of the upper limbs in paretic or plegic people. Methods: The databases used in papers selection were Google Scholar and Capes’ Portals as well as proceedings of the Annual Conference of the International Functional Electrical Stimulation Society (IFESS). Results: Approximately 85% of the reviewed studies showed FES profile with pulse duration ranging from 1 to 300 μs and modulating (burst) frequency between 10 and 40 Hz. Regarding the type of electrodes, 88% of the studies employed transcutaneous electrodes. Conclusion: We concluded that FES with closed-loop feedback and feedforward are the most used and most viable systems for upper limbs motor control, because they perform self-corrections slowing neuromuscular adaptation, allowing different planes and more range of movement and sensory-motor integration. One of the difficulties found in neuroprosthesis systems are electrical wires attached to the user, becoming uninteresting in relation to aesthetics and break. The future perspectives lead to a trend to miniaturization of the stimulation equipment and the availability of wireless networks, which allow the attachment of modules to other components without physical contact, and will become more attractive for daily use. © 2016, Sociedade Brasileira de Engenharia Biomedica. All rights reserved.32219921

Muscle fatigue assessment by mechanomyography during application of NMES protocol

Background: Neuromuscular electrical stimulation (NMES) is a widely used technique for rehabilitation in physical therapy, however it causes muscle fatigue more rapidly than does voluntary contraction. In clinical practice, it becomes necessary to monitor muscle fatigue during NMES protocols to adjust the parameters of electrical current stimulation and, thus, increase stimulation time. Objectives: The aim of this study is to use mechanomyography (MMG) as a means of evaluating peripheral muscle fatigue during the execution of an NMES protocol. Methods: An MMG signal acquisition system and an experimental protocol were developed. During in vivo tests, 10 participants performed maximal voluntary contractions (MVCs) for knee extension. A maximization phase was conducted with dynamic contractions generated by NMES at 10% of MVC (100 Hz, 400 mu s) on the quadriceps muscle, and the main NMES protocol occurred at 30%, of MVC (50 Hz, 400 mu s). Simultaneously, MMG(RMS) (amplitude) and MMG(MPF) (frequency) signals of the rectus femoris and the knee extension torque were acquired. Results: The tendency line of the MMGRMS was descendant, indicating that MMGRMS correlates with torque amplitude. However, MMGMPF did not show a significant correlation with torque for the present NMES protocol. Conclusions: MMG is a technique that can be simultaneously applied to NMES because there is no electrical interference and it can be used during functional movements in the NMES-generated muscle contraction. Article registered in the Australian New Zealand Clinical Trials Registry (ANZCTR) under the number ACTRN12609000866202.13542242

A solution for linearity, stability and frequency bandwidth in PAM electrocutaneous stimulators' isolation interface

This paper introduces a novel method to isolate low-level from high-voltage circuits and/or channels of PAM electrocutaneous stimulators in neuromuscular electrical stimulation (NMES). The method avoids problems of linearity and polarization stability of optocouplers and narrow bandwidth of isolation amplifiers. Its main parameters are: carrier frequency of rectangular pulses up to 1 MHz and maximum modulating signal (elliptical or triangular envelopes) of 50 kHz. The circuit has low drift, high-voltage isolation, low-power consumption, requires few components, is battery-operated and ideal for microcomputer interface-based applications. Copyright (C) 1996 Elsevier Science for IPEMB.18869269

Method for automatic detection of wheezing in lung sounds

The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data