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Interpretation and Analysis of Neural and Muscle Signals- Dozentinnen/Dozenten
- Prof. Dr. Alessandro Del Vecchio, Prof. Dr. Seung Hee Yang
- Angaben
- Seminar
Präsenz
2 SWS, ECTS-Studium, ECTS-Credits: 5, Sprache Englisch
Zeit und Ort: Di 14:45 - 16:15, Hörsaal ZMPT
- ECTS-Informationen:
- Title:
- Interpretation and Analysis of Neural and Muscle Signals
- Credits: 5
- Prerequisites
- Compulsory prerequisites: No compulsory prerequisites
Recommended: Basic biology and neurophysiology, Computer programming (Matlab and/or Python), Biosignal processing
- Contents
- Lecture: Fundamentals of speech signals, electrocardiogram, and electromyography.
Lecture: Principles of neural signals
Generation of an action potential; Recording electrophysiological data in humans; examples of EMG, EEG, intracortical data, and audio signals. Lecture: Speech signals and processing Lecture: ECG signal and processing Lecture: EMG signal and processing
Association between EMG and voluntary force; Interpretation of multi-channel EMG signals; Neuronal encoding of behaviour; motor unit physiology in humans; motoneuron properties, longitudinal assessment of neuronal function; voice biomarkers for diagnosis and treatment of neurological disease; automatic speech recognition; speech pathology. Lecture: MATLAB / Python practical coursework
Biosignal processing; data with high temporal resolution, identification of individual neurons, associations between neuronal discharge times and behaviour; control of prosthetic devices from neural signals.
Extraction of neural information from speech and ECG signals, electrophysiological signals, and data mining and neural network model training on these signals.
Practical work: literature overview on these signals and a critical analysis on how to merge these signals for an artificial intelligent system that can detect and prevent neural and/or muscular pathologies.
- Literature
- -Principles of Neuroscience from Eric R. Kandel, MD
-Motor unit from Heckman and Enoka, DOI: 10.1002/cphy.c100087
-Neural Engineering, Edited by Bin He
-Tutorial: Analysis of motor unit discharge characteristics from high-density surface EMG signals, Del Vecchio et al. https://doi.org/10.1016/j.jelekin.2020.102426
-Restoring sensorimotor function through intracortical interfaces: progress and looming challenges, Bensmaia and Miller
https://www.nature.com/articles/nrn3724
-Speech and Language Processing, 2nd Edition by Daniel Jurafsky and James Martin. Prentice Hall (2008).
-Automatic Speech Recognition: A Deep Learning Approach (Signals and Communication Technology). 2015th Edition by Li Deng
-Alday, Erick A. Perez, et al. "Classification of 12-lead ecgs: the physionet/computing in cardiology challenge 2020." Physiological measurement 41.12 (2020): 124003.
https://iopscience.iop.org/article/10.1088/1361-6579/abc960/meta
-Orozco-Arroyave, Juan Rafael, et al. "Apkinson: the smartphone application for telemonitoring Parkinson’s patients through speech, gait and hands movement." Neurodegenerative Disease Management 10.3 (2020): 137-157.
https://www.futuremedicine.com/doi/full/10.2217/nmt-2019-0037?casa_token=FLKpZKgV3WcAAAAA%3ApZ7cX9gMQL50cO0Z_sosJPfVQ_KlVjsvRWoaMlTqRgXYkyP8N3KBBmQotGSyK-PiYnOnj843qs7CWQ
- Zusätzliche Informationen
- Schlagwörter: Neurophysiology, Neural signals
Für diese Lehrveranstaltung ist eine Anmeldung erforderlich.
Die Anmeldung erfolgt über: StudOn
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2022/2023:
- Interpretation and Analysis of Neural and Muscle Signals (BioSignalIS)
- Institution: Juniorprofessor für Neuromuscular Physiology and Neural Interfacing
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