Interactive assistant tool for the evaluation of kinematic patterns and EMG signals in patients with a forearm injury

Subjective feelings feedbacks are commonly employed by a patient during forearm rehabilitation therapy without real-time data, leading to suboptimal recovery results in some patients. Technological innovations in the field of assisted rehabilitation have enabled the evolution of real-time monitoring systems. In this paper, interactive assistant development is presented as the interface to define the relationship between the kinematics patterns and the electromyographic signals during the forearm rehabilitation routine. Leap Motion (LM) and Shimmer3 EMG sensors read the routine behavior by following the movements that appear on the software. Real-time targets are programmed to lead the necessary forearm movements that the therapist sets to determine the recovery progress. The integration of software and hardware shows a dataset basis on interaction variables such as arm velocity, arm position, performance rate, and electrical muscle pulse. The results obtained from tests show that the system works effectively within a range of movement of 9 to 88 degrees in rotation about the axes, and velocities under 190 mm/s show stable movement representation on software. Finally, the outcomes ranges show an alternative tool to evaluate patients with a forearm injury.

Changes in muscle coactivation during running: a comparison between two techniques, forefoot vs rearfoot

Introduction: According to the literature, eccentric exercise has been considered a precursor of neuromuscular changes generated by post-exercise damage, mainly causing an alteration in the muscle cell membrane. Muscle fiber conduction velocity (MFCV) has been one of the physiological variables that have allowed to quantify this alteration. Some investigations have shown a decrease in the MFCV after eccentric exercise protocols; however, few studies have confirmed these findings. This review aimed to describe the recent scientific evidence that reports changes in the MFCV after eccentric exercise protocols. Material and method: From 265 articles, 6 articles were selected from EBSCO and MEDLINE platforms with a temporal filter of 10 years (between 2010 and April 2020), using inclusion/exclusion criteria predetermined. Firstly, the information from eccentric exercise effect on MFCV, and exercise protocols were described. Secondly, the techniques used to record electromyographic signals and some criteria to determine the MFCV were reported. Results: Modifications of MFCV can be observed after eccentric exercise in almost all selected articles. At the same time, a decrease of this variable was observed in four studies, associated with the biceps brachii and two portions of the quadriceps muscles. However, one article describes an increase of the MFCV in the vastus lateralis quadriceps. Conclusion: The articles suggest that eccentric contractions could modify the MFCV behavior of some muscles. However, evidence is still lacking to describe the real cause of these changes.

Acupuncture E_cacy Study Using Electromyographic Signals

Acupuncture is a centuries-old therapeutic technique. However, because of the large number of complicating circumstances, it has been difficult to clearly prove the treatment's therapeutic effectiveness.As a result, acupuncture has failed to acquire acceptance in the mainstream clinical sector. An electromyography (EMG) sensor was built and used to test the efficacy of acupuncture in alleviating muscular stiffness in this study. Electrodes, differential and inverting amplifiers, filters, and a full-wave rectifier made up the EMG circuit. The output of the circuit was sent to a microcontroller for analog-to-digital transformation in order to perform data acquisition. Acupuncture was used to treat four participants who had muscular dysfunction in various regions of their bodies in our case study. Before and after the therapy, EMG signals at the damaged regions were recorded. The findings revealed that the therapy had no immediate conceivable impact on the patients, since the levels of muscular contraction before and after the treatment were comparable. When the EMG signals were measured 30 minutes after the therapy, signs of muscular alleviation were found. This shows that acupuncture does supply patients with beneficial medicine, although slowly. The act of placing the highly conducting needles into the acupuncture sites, we believe, is similar to connecting a parallel wire to a circuit, resulting in a short-circuited route at the meridian. It permits the meridian's polarized in- ner energy, or qi, to pass through. The equilibrium in qi regulation can therefore be restored by unclogging the ow of qi.The repair process is relatively slow, and the treatment impact may not be immediately apparent, because the consti- tutive qualities at the acupuncture points where the needles are pricked may not alter quickly.

A Perspective on Muscle Synergies and Different Theories Related to Their Adaptation

The human motor system is a complex neuro-musculo sensory system that needs further investigations of neuro-muscular commands and sensory-motor coupling to decode movement execution. Some researchers suggest that the central nervous system (CNS) activates a small set of modules termed muscle synergies to simplify motor control. Further, these modules form functional building blocks of movement as they can explain the neurophysiological characteristics of movements. We can identify and extract these muscle synergies from electromyographic signals (EMG) recorded in the laboratory by using linear decomposition algorithms, such as principal component analysis (PCA) and non-Negative Matrix Factorization Algorithm (NNMF). For the past three decades, the hypothesis of muscle synergies has received considerable attention as we attempt to understand and apply the concept of muscle synergies in clinical settings and rehabilitation. In this article, we first explore the concept of muscle synergies. We then present different strategies of adaptation in these synergies that the CNS employs to accomplish a movement goal.

CHARACTERIZATION OF TEXTILE ELECTRODES FOR EMG MEASUREMENTS

Textile electrodes are an alternative to conventional silver-chloride electrodes in wearable systems. Their easy integration in garments and comfort provided to the user make them an interesting development of textile engineering. The potential of such electrodes to allow more unobtrusive data collection in health and sports context may enable the development of biosensing garments to be used in biomechanics. However, proper validation of the recorded signals is paramount, and few studies have yet presented consistent methodologies for textile-based electromyographic recordings. This study presents the validation of the electrical and morphological properties of electromyographic signals recorded with textile electrode, in comparison to conventional silver-chloride electrodes. Results indicate that both sets of electrodes have identical signal-to-noise ratios, but with distinct impedance frequency responses. Electromyographic envelope morphologies are also identical, although textile electrodes usually have lower amplitudes.

DEVELOPMENT OF AN ALGORITHM FOR IDENTIFICATION OF TERRAIN IN A LOWER LIMB PROSTHESIS CONTROL SYSTEM

Статья посвящена разработке алгоритма определения типа местности, по которой перемещается пользователь протезом нижней конечности. Идентификация местности, по которой происходит движение, является важной задачей при управлении протезами нижних конечностей, так как на разных типах местности протез должен совершать разные модели движений. В данном исследовании высказано предположение о возможности определения типа местности с помощью электромиографических датчиков, которые записывают сигналы от определенных мышц пользователя протезом. Чтобы подтвердить это утверждение, было проведено исследование. Испытуемые выполняли несколько типов движений: движение прямо, подъем и спуск по лестнице, подъем и спуск по наклонной поверхности. Электромиографические сигналы регистрировались от разных мышц нижних конечностей испытуемых. После первичной обработки из сигналов были выделены параметры биоэлектрического сигнала, чаще всего используемые в управлении протезами. Результаты исследования показали, что существует статистическая разница в некоторых параметрах сигнала в зависимости от канала регистрации сигнала и типа местности, на которой происходит движение. Исследование доказало возможность определения типа местности по четырем комбинациям параметр сигнала - мышца. На основании полученных результатов предложен алгоритм идентификации местности The article is devoted to the development of an algorithm for determining the type of terrain along which the user moves with a lower limb prosthesis. Identification of the terrain along which the movement takes place is when controlling the prostheses of the lower extremities, since on different types of terrain the prosthesis must perform different models of movements. In this study, it is assumed that it is possible to determine the location using electromyographic sensors that record signals from the muscles of the wearer with a prosthesis. Research has been done to confirm this claim. The subjects performed several types of movements: straight movement, climbing and descending stairs, ascending and descending an inclined surface. Electromyographic signals were recorded from different muscles of the lower end objects. After primary processing, the parameters of the bioelectric signal were extracted from the signals. The research results show that there is a statistical difference in some signal parameters depending on the signal registration channel and the type of terrain on which the movement takes place. The study proved the possibility of determining the type of terrain by four combinations of signal parameter - muscle. Based on the results obtained, an algorithm for identifying the area is proposed

Effect of BoNT/A in the Surface Electromyographic Characteristics of the Pelvic Floor Muscles for the Treatment of Chronic Pelvic Pain

Chronic pelvic pain (CPP) is a complex condition with a high economic and social burden. Although it is usually treated with botulinum neurotoxin type A (BoNT/A) injected into the pelvic floor muscles (PFM), its effect on their electrophysiological condition is unknown. In this study, 24 CPP patients were treated with BoNT/A. Surface electromyographic signals (sEMG) were recorded at Weeks 0 (infiltration), 8, 12 and 24 from the infiltrated, non-infiltrated, upper and lower PFM. The sEMG of 24 healthy women was also recorded for comparison. Four parameters were computed: root mean square (RMS), median frequency (MDF), Dimitrov’s index (DI) and sample entropy (SampEn). An index of pelvic electrophysiological impairment (IPEI) was also defined with respect to the healthy condition. Before treatment, the CPP and healthy parameters of almost all PFM sides were significantly different. Post-treatment, there was a significant reduction in power (<RMS), a shift towards higher frequencies (>MDF), lower fatigue index (<DI) and increased information complexity (>SampEn) in all sites in patients, mainly during PFM contractions, which brought their electrophysiological condition closer to that of healthy women (<IPEI). sEMG can be used to assess the PFM electrophysiological condition of CPP patients and the effects of therapies such as BoNT/A infiltration.

Assist-As-Needed Exoskeleton for Hand Joint Rehabilitation Based on Muscle Effort Detection

Robotic-assisted systems have gained significant traction in post-stroke therapies to support rehabilitation, since these systems can provide high-intensity and high-frequency treatment while allowing accurate motion-control over the patient’s progress. In this paper, we tackle how to provide active support through a robotic-assisted exoskeleton by developing a novel closed-loop architecture that continually measures electromyographic signals (EMG), in order to adjust the assistance given by the exoskeleton. We used EMG signals acquired from four patients with post-stroke hand impairments for training machine learning models used to characterize muscle effort by classifying three muscular condition levels based on contraction strength, co-activation, and muscular activation measurements. The proposed closed-loop system takes into account the EMG muscle effort to modulate the exoskeleton velocity during the rehabilitation therapy. Experimental results indicate the maximum variation on velocity was 0.7 mm/s, while the proposed control system effectively modulated the movements of the exoskeleton based on the EMG readings, keeping a reference tracking error <5%.