This paper presents a technique to synthesize speech from SEMG signals using a frame-byframe basis. SEMG signals are firstly enframed and classified into a number of phonetic classes by a neural network, then the produced sequences of phonetic indices are translated to acoustic signals by concatenating their corresponding pre-recored speech segments. A significant advantage of the proposed synt...

We present a multiclass fuzzy relevance vector machine (FRVM) learning mechanism and evaluate its performance to classify multiple hand motions using surface electromyographic (sEMG) signals. The relevance vector machine (RVM) is a sparse Bayesian kernel method which avoids some limitations of the support vector machine (SVM). However, RVM still suffers the difficulty of possible unclassifiable...

To date, most studies use surface electromyographic (sEMG) signals as the control source on active rehabilitation robots, and unilateral data are collected based on the gait symmetry hypothesis, which has caused much controversy. The purpose of this study is to quantitatively evaluate the sEMG activity asymmetry of bilateral muscles in lower extremities during functional tasks. Nine participant...

Electromyography (EMG) and ultrasonography have been widely used for skeletal muscle assessment. Recently, it has been demonstrated that the muscle thickness change collected by ultrasound during contraction, namely sonomyography (SMG), can also be used for assessment of muscles and has the potential for prosthetic control. In this study, the performances of one-dimensional sonomyography (1D SM...

The surface electromyographic (sEMG) signal that originates in the muscle is inevitably contaminated by various noise signals or artifacts that originate at the skin-electrode interface, in the electronics that amplifies the signals, and in external sources. Modern technology is substantially immune to some of these noises, but not to the baseline noise and the movement artifact noise. These no...

Low back pain (LBP) is a major public health problem and the leading disabling musculoskeletal disorder globally. A number of biomechanical methods using kinematic, kinetic and/or neuromuscular approaches have been used to study LBP. In this narrative review, we report recent developments in two biomechanical methods: estimation of lower back loads and large-array surface electromyography (LA-S...

Motion predictions for limbs can be performed using commonly called Hill-based muscle models. For this type of models, a surface electromyogram (sEMG) the serves as an input signal activation model. However, Hill model needs additional information about mechanical system state (current length, velocity, etc.) reliable prediction force generation and, hence, joint motion. One feature that contai...

This article reviews the current techniques of surface electromyography (SEMG) assessment. Discussed are static, dynamic, and combination assessment techniques and the rational for their use.

Most practitioners would agree that the main cause of urinary incontinence after RP is sphincter or neurological damage or urethral shortening due to the surgery. The external striated sphincter is tubular and has broad attachments over the fascia of the prostate near the apex. Its innervations arise from the pudendal nerves and the autonomic nerves in the pelvic plexus. Urinary continence reco...

Convolutional neural network (CNN) has been widely exploited for simultaneous and proportional myoelectric control due to its capability of deriving informative, representative, transferable features from surface electromyography (sEMG). However, muscle contractions have strong temporal dependencies, but conventional CNN can only exploit spatial correlations. Considering that the long short-ter...