Real-time acquisition and analysis ofElectro-oculography signals
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Electro-oculography signals are corneo-retinal potentials that carry informationpertaining to eye movements. This information can be used to estimate drowsinesslevel of the subject which could provide interesting insights into research of acci-dent prevention. Of all features present, blink duration has been proved to be aneffective measure of drowsiness. The aim of this thesis work is to build a portablesystem to acquire and analyze electro-oculographic (EOG) signals in real-time.The system contains two sub-systems; a hardware sub-system that consists of thefilters, amplifiers, data acquisition card and isolation and the software sub-systemthat contains the program to acquire and analyze the signal and present the resultsto the observer. The filters were designed starting with simulation, implementa-tion on the prototype board, culminating in the design of a printed circuit board(PCB) and packaging. The complete software was written in PythonTMusing sev-eral relevant libraries for data processing. A text-based user interface was createdto enable easy user interaction. The results are graphically displayed in real-time.
Ex-situ tests were done with two volunteers while in-situ test was done onone subject. The data from the in-situ tests showed "good signal quality" in a"noisy" environment concurring with the design specifications. To motivate theimportance of calibration, two calibration paradigms were used during ex-situtests, where one paradigm records only normal blinks while the other records longblinks and the results showed differences in detection and error rates. The obser-vations made from performance tests at various levels gave "satisfactory results"and proved the usefulness of the system for experimental purposes in-situ.
Place, publisher, year, edition, pages
2012. , 82 p.
Electro-oculography, real-time sleep stage classification, accidents, drowsiness, sleepiness, blink characteristics, Python, MATLAB, 5Spice analysis, NI6008
Medical Equipment Engineering
IdentifiersURN: urn:nbn:se:liu:diva-76734ISRN: LiTH-IMT/MASTER-EX--12/011--SEOAI: oai:DiVA.org:liu-76734DiVA: diva2:516518
Statens väg- och transportforskningsinstitut (VTI), Linköping, Sweden
Subject / course
Masterprogram Biomedical Engineering (BME)
2012-01-27, IMT 1, Linköping university, Linköping, Sweden, 14:18 (English)
Ahlström, Christer, Researcher
Salerud, Göran, Professor