Assessment strategy of human upper forearm inter-relation and muscle fatigue

Surface electromyography (EMG) signals classification is currently applied in various prostheses and arm controls using various classification methods. The limited robustness in practical EMG control applications has become an important matter of research consideration. The precision of EMG signal features and parameters proportionally vary with muscle fatigue (MF). The major challenge for the study is to identify the MF manifestation in the EMG signal, so that the control performance is improved. This can be done by the improvement of data collection practicality, features extraction and classification. Hence, fundamental study is performed by investigating the signals acquired from the human upper forearm (UFA) to determine muscle characteristics and to establish the inter-relationship between both muscles of the forearm and upper arm. The aim of the present study is to investigate the applicability of human UFA muscles and MF indices at various force levels of maximum voluntary contraction (MVC). EMG signals are recorded from nine (9) normally limbed subjects. The frequency domain power spectrum density (PSD) is computed in order to derive the useful characteristics of the signal. The results show that only few muscles contributes for the movement. Further analysis show that flexor digitorum superficialis (FDS), flexor carpi radialis (FCR), extensor carpi radialis longus (ECRL), extensor digitorum communis (EDC) and biceps/triceps brachii show interesting results

Effect of two adjacent muscles of flexor and extensor on finger pinch and hand grip force

Hand grip force and motion pattern classification using bio signal such as Electromyogram (EMG) has been very important in current studies. EMG based pattern classification has gain the utmost consideration especially in the commercial prostheses. Developing an intuitive hand control with fast response both in time and space are the major challenges. These challenges are due to the lack of information gathered from adjacent muscles. The study of adjacent muscles is crucially needed as it will allow to provide optimised hand grip and motion pattern classification without redundancy in the use of muscle information. The main aim of this paper is to investigate the effect of two adjacent flexor muscles; flexor digitorum superficial (FDS) and flexor carpi radialis (FCR), two adjacent extensor muscles: extensor carpi radialis longus (ECRL) and extensor digitorum communis (EDC) providing the perspective view of individual muscle performance compared to their adjacent muscle with respect to finger pinch and hand grip force. Practical classification results prove the significance of the study, both adjacent muscles perform almost similar with approximately 95% of similarities across different subjects. The results achieved lead to the conclusion, that the use of adjacent muscles can be reduced to only single muscle channel providing an optimised data for pattern recognition or classification