Reprint

Biomedical Sensors for Functional Mapping: Techniques, Methods, Experimental and Medical Applications

Edited by
December 2023
254 pages
  • ISBN978-3-0365-9823-9 (Hardback)
  • ISBN978-3-0365-9824-6 (PDF)

This book is a reprint of the Special Issue Biomedical Sensors for Functional Mapping: Techniques, Methods, Experimental and Medical Applications that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary

Biomedical sensors stand at the forefront of modern medical technologies, serving as indispensable components in diverse instruments and equipment. These sensors unravel the intricacies of biological processes and medical interventions. The recent surge in high-density sensor systems, characterized by arrangements in matrix arrays and other configurations, has ushered in a new era of functional evaluation. This spans electrophysiological activity, the metabolic responses of organs and tissues, and motor control analysis, all enriched with crucial spatial information. Functional mapping, a burgeoning approach in various biomedical techniques such as EEG, EMG, ECG, NIRS, and MEG, is proving to be transformative. Its integration enhances our comprehension of complex biological behaviors, where the precise spatial localization of sensing methodologies becomes paramount. The applications of functional mapping using biomedical sensors extend across multiple fields, including neuroscience, neuromuscular physiology, rehabilitation, and cardiology. Its utility ranges from diagnostic purposes to assessing the effectiveness of therapeutic interventions. The primary objective of this reprint was to collect papers that delineate the forefront of techniques, methods, and applications in the realm of biomedical sensors. Additionally, the focus extends to specific algorithms for data processing, ensuring a robust understanding of functional information intricately associated with spatial localization.  

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
EMG; EEG; rehabilitation; neuromotor; evaluation; assessment; review; machine learning; EMG; biofeedback; transfer learning; random forest classifier; COVID-19; intubation; tracheoesophageal fistula; tracheal lesions; acute respiratory distress syndrome; modeling; intensive care unit; muscle synergies; whole body FES; neurological patients; photodynamic therapy; fluorescence; laser; fluorophores; enamel; EEG; effective connectivity; kurtosis; resting-state connectivity; stationarity; sleep monitoring; pressure bed sensor (PBS); unobtrusive measure; multi-scale analysis; sleep apnea–hypopnea syndrome (SAHS); shift-working; optically detected magnetic resonance; quantum magnetometer; magnetoencephalography; time domain; functional near infrared spectroscopy; diffuse optics; brain; hemodynamics; resting-state brain oscillation; mental workload; EEG; signal processing; reliability; cognitive performance; Simon task; emotion detection; valence; arousal; wearable sensors; regression; classification; machine learning; technology acceptance model; rehabilitation exoskeletons; therapists; neuro-rehabilitation; multiple linear regression; Pearson’s correlation; integrated sensor systems; hand function; hand osteoarthritis; electromyography; diagnosis; discriminant analysis; photoplethysmogram; microcirculation; deep learning; convolutional neural network; modelling; classification; n/a