Stroke is the second largest cause of death worldwide and one of the most common causes of disability. However, several approaches have been proposed to deal with stroke patient rehabilitation like robotic devices and virtual reality systems, researchers have found that the brain-computer interfaces (BCI) approaches can provide better results. In this study, the electroencephalography (EEG) dataset from post-stroke patients were investigated to identify the effects of the motor imagery (MI)-based BCI therapy by investigating sensorimotor areas using frequency and time-domain features and to select particular methods that help in enhancing the MI-based BCI systems for stroke patients using EEG signal processing. Therefore, to detect

The electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI)

  Foot and ankle movements are essential in various activities like walking, running, and balance, where the mechanics of these movements are affected by the muscles around the ankle joint [1,2]. In this study, the correlations between isometric ankle torque and muscle activity of the tibialis anterior (TA) and gastrocnemius (GAS) in the course of dorsiflexion and plantarflexion was investigated. Eight healthy participants were enrolled for the study, where the ankle torque and surface Electromyography (sEMG) of the main flexors were measured and analyzed. The results showed that ankle torque is higher in plantarflexion than dorsiflexion. In addition, the TA has greater muscle activity during dorsiflexion, while the GAS presents higher ac

Recording an Electromyogram (EMG) signal is essential for diagnostic procedures like muscle health assessment and motor neurons control. The EMG signals have been used as a source of control for powered prosthetics to support people to accomplish their activities of daily living (ADLs). This work deals with studying different types of hand grips and finding their relationship with EMG activity. Five subjects carried out four functional movements (fine pinch, tripod grip and grip with the middle and thumb finger, as well as the power grip). Hand dynamometer has been used to record the EMG activity from three muscles namely; Flexor Carpi Radialis (FCR), Flexor Digitorum Superficialis (FDS), and Abductor Pollicis Brevis (ABP) with different le

Reverse shoulder arthroplasty is an increasingly common surgical intervention. However there are concerns and known limitations in relation to such joint replacement, while novel designs of reverse shoulder prostheses continue to appear on the market. Many claim to offer improvements over older designs but such assertions are difficult to validate when there is no consensus as to how such implants should be tested in vitro or even if such testing is necessary. In order to permit appropriate in vitro testing of reverse shoulder prostheses a unique, multi-station test rig was designed which was capable of applying motion in three axes to test prostheses. The shoulder simulator can apply up to 110° of motion in the flexion–extension and abd

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.