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Vorlesung: Physiological Computing and Neuroergonomics

  • Dozent: Dr. Lewis Chuang
  • Kontakt: pcn@um.ifi.lmu.de
  • Semesterwochenstunden: 2 + 3
  • ECTS-Credits: 6
  • Modul: Vertiefende Themen für Master Medieninformatik, Master Informatik und Master Mensch-Computer-Interaktion
  • Sprache: Englisch

News

  • Es wird gebeten, die erste Veranstaltung am 29.04.19 zu besuchen um die Organisation des Kurs zu besprechen
  • Der Kurs fällt am 06.05.19 und 10.06.19 (Pfingstmontag) aus

Anmeldung via Uniworx

  • https://uniworx.ifi.lmu.de/?action=uniworxCourseWelcome&id=1133

Klausur/Nachholklausur

  • Es sind keine Hilfsmittel erlaubt.
  • Zum Bestehen müssen min. 50% der Punkte erreicht werden.

Termine und Ort

  • Vorlesung: Montag, 10 Uhr bis 11:45 Uhr c.t., erster Termin 29.04.19
  • Übung: Montag, 12 Uhr - 14:45 c.t., erster Termin 29.04.19
  • Ort: Theresienstraße 39, 80337 München, Raum B139

Inhalt

Our bodies are supported by numerous functions and mechanisms that allow us to respond to the requirements of our environment as well as to support our intentions. Our hearts beat faster and our pupils dilate, in anticipation of physical exertion; neurons fire from the skeletomuscular system to the peripheral and central nervous system and back. Many of these functions are physically measurable. While large and expensive biomedical devices were previously necessary to acquire such data, the last decade has witnessed a growth in the miniaturization and cost-effectiveness of consumer-grade wearable sensors. This creates a potential for computing systems that are responsive to changes in their users’ physiological state.
This course is designed to provide students with a basic knowledge of the human physiological system as well as train students to acquire, analyze, and interpret data. The goal is to provide students with a fundamental understanding of the physiological activity to the extent that it can be meaningfully submitted to a computing systems. This course could complement but is NOT a suitable substitute for fundamental courses in human physiology (e.g., Neurophysiology, Dept. Physiological Genomics). The following topics will be covered:

  • Optical and electrical data acquisition for physiological activity
  • Time-series analysis for physiological activity
  • The peripheral nervous system
  • Electrodermal activity
  • Pupil tracking
  • The skeletomuscular system
  • Electromyography
  • Electrical muscle stimulation)
  • The central nervous system
  • Electroencephalography
  • Event-related potentials
  • Physiological computing systems

Aufbau und Zeitplan (vorläufig)

Datum Vorlesung (in UniWorX verfügbar) Übung
29.04.20 Organisation, Einführung in die Signalverarbeitung Foundations, Basic Electricity, Neuroanatomy and Neurophysiology, Introduction to SciPy, Panda, Domains, FFT, Features
06.05.20 Keine Vorlesung Keine Übung
13.05.2019 The nervous system and measurement of its activity Data quality check, Detecting Saccade, Fixation, Blink (comparison of algorithms) AOI analysis (Dwell, etc.), Heatmap
20.05.20 The Electroencephalogram (EEG) EEG Measre, Importance of preperation, Impedance, Detecting Artefacts (Blink, Chewing, 50Hz), Different Channels / Regions, Explain live signals
27.05.19 EEG and Behavior: Motor and Mental Activities Data Preprocessing (Filtring, Removing Artefacts), Time (entropy, fractal dimension) and Frequency Domain (spectogram, wavelets), Different waves, Power analysis, (De)Synchronisation
03.06.19 EEG and Behavior: Sensation, Attention, Conditioning, and Sleep Classification, EMS, Studentproject to build an EMS inerface, e.g. Handshake, People connection with EMG, Safety introduction, Individual differences, Accuracy,
10.06.19 No lecture Keine Übung
17.06.19 Brain Computer Interfaces (Prof. Fabien Lotte, Inria, CH) active vs passive Interfaces, Student projects
24.06.19 Event-Related Brain Potentials & Behavior ERP dataset
01.07.19 Muscle Activity & Behavior Principle, Individual differences, Live signal comparison
08.07.19 Neuroprostheses (Dr. Ricardo Chavarriaga, EPFL, CH) Data Preprocessing (filtering, motion artefacts), RMS, Phase, Signal decomposition (segmentation, wavelet transform, PCA, and clustering), AI (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1455479/), Fatigue detection
15.07.19 Electrodermal Activity (EDA) & Behavior: Arousal EDA
22.07.19 Heart Activity & Behavior: Stress, Emotions, Motivation Heartreat (consumer product, einfluss)
29.07.19 Applied Psychophysiological Computing: Biofeedback Keine Übung