AML-DECODER: Advanced Machine Learning for HD-sEMG Signal Classification-Decoding Lateral Epicondylitis in Forearm Muscles.

Background: Innovative algorithms for wearable devices and garments are critical for diagnosing and monitoring disease (such as lateral epicondylitis (LE)) progression. LE affects individuals across various professions and causes daily problems.

Methods: We analyzed signals from the forearm muscles of 14 healthy controls and 14 LE patients using high-density surface electromyography.

Repetitive active and passive cognitive stimulations induce EEG changes in patients with Rett syndrome.

Background: Despite being considered a rare disease, Rett syndrome is a leading cause of profound cognitive impairment in females. This study explores game-based cognitive stimulation to enhance attention during learning tasks, offering an alternative treatment perspective.

Methods: Fifteen diagnosed Rett syndrome girls participated in four 24-minute sessions, including a 5-minute initial resting state recording.

EEG connectivity patterns in response to gaming and learning-based cognitive stimulations in Rett syndrome.

Background: Functional connectivity is scarcely studied in Rett syndrome (RTT). Explorations revealed associations between RTT's clinical, genetic profiles, and coherence measures, highlighting an unexplored frontier in understanding RTT's neural mechanisms and cognitive processes.

Aims: To evaluate the effects of diverse cognitive stimulations-learning-focused versus gaming-oriented-on electroencephalography brain connectivity in RTT.

An integrated mathematical model of the cardiovascular and respiratory response to exercise: model-building and comparison with reported models.

The use of physiological models in medicine allows the evaluation of new hypotheses, development of diagnosis and clinical treatment applications, and development of training and medical education tools, as well as medical device design. Although several mathematical models of physiological systems have been presented in the literature, few of them are able to predict the human cardiorespiratory response under physical exercise stimulus adequately. This paper aims to present the building and comparison of an integrated cardiorespiratory model focused on the prediction of the healthy human response under rest and aerobic exercise.

High-density surface electromyography signals during isometric contractions of elbow muscles of healthy humans.

This paper presents a dataset of high-density surface EMG signals (HD-sEMG) designed to study patterns of sEMG spatial distribution over upper limb muscles during voluntary isometric contractions. Twelve healthy subjects performed four different isometric tasks at different effort levels associated with movements of the forearm. Three 2-D electrode arrays were used for recording the myoelectric activity from five upper limb muscles: biceps brachii, triceps brachii, anconeus, brachioradialis, and pronator teres.