Effective electromyographic (EMG) signal characterization is critical in the diagnosis of
neuromuscular disorders. Machine-learning based pattern classification algorithms are …

In this work, an attempt has been made to differentiate surface electromyography (sEMG)
signals under muscle fatigue and non-fatigue conditions with multiple time window (MTW) …

In this paper, we propose a muscle gesture-computer interface (MGCI) system for a five-
fingered robotic hand control employing a commercial wearable MYO gesture armband …

Abstract Analysis of neuromuscular fatigue finds various applications ranging from clinical
studies to biomechanics. Surface electromyography (sEMG) signals are widely used for …

Purpose In this work, an attempt has been made to analyze surface electromyography
(sEMG) signals in dynamic contractions using bispectrum features. Methods Signals are …

Surface electromyography (sEMG) signals are stochastic, multicomponent and non‐
stationary, and therefore their interpretation is challenging. In this study, an attempt has been …

In this paper, a new CNN architecture is introduced for classification of six different hand
gestures using surface electromyography (EMG) data collected from the forearm. At first, two …

Biomedical signals represent the variation in electric potential due to physiological
processes and are recorded through certain types of sensors or electrodes. In practice, the …

This book gathers selected high-quality research papers presented at International
Conference on Advanced Computing and Intelligent Technologies (ICACIT 2021) held at …

Fatigue is a phenomena associated with reduction of maximum force in muscles while
performing functional activities. Assessment of fatigue is important in the field of clinical …