Advanced Signal Processing in Wearable Sensors for Health Monitoring

• Autres auteurs: Abbod, Maysam (Éditeur intellectuel), Shieh, Jiann-Shing (Éditeur intellectuel)
• Format: Électronique Chapitre de livre
• Langue: anglais
• Publié: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Sujets: Technology: general issues; History of engineering & technology; automated dietary monitoring; eating detection; eating timing error analysis; biomedical signal processing; smart eyeglasses; wearable health monitoring; artificial neural network; joint moment prediction; extreme learning machine; Hill muscle model; online input variables; Review; ECG; Signal Processing; Machine Learning; Cardiovascular Disease; Anomaly Detection; photoplethysmography; motion artifact; independent component analysis; multi-wavelength; continuous arterial blood pressure; systolic blood pressure; diastolic blood pressure; deep convolutional autoencoder; genetic algorithm; electrocardiography; vectorcardiography; myocardial infarction; long short-term memory; spline; multilayer perceptron; pain detection; stress detection; wearable sensor; physiological signals; behavioral signals; non-invasive system; hemodynamics; arterial blood pressure; central venous pressure; pulmonary arterial pressure; intracranial pressure; heart rate measurement; remote HR; remote PPG; remote BCG; blind source separation; drowsiness detection; EEG; frequency-domain features; multicriteria optimization; machine learning; n/a
• Accès en ligne: DOAB: download the publication; DOAB: description of the publication

Smart, wearables devices on a miniature scale are becoming increasingly widely available, typically in the form of smart watches and other connected devices. Consequently, devices to assist in measurements such as electroencephalography (EEG), electrocardiogram (ECG), electromyography (EMG), blood p...