The aim of the diploma thesis is the design and implementation of methods for detecting fatigue in electromyogram (EMG). At first is done a literature review on the topic of fatigue detection in electromyography (EMG). Measurement of fatigue-induced changes in the EMG signal is performed on ten subjects using the Biopac ©. Next is in the thesis solved the selection of the optimal methods of evaluating the fatigue-induced changes in EMG recording using statistical testing. In the final part of the thesis is discussion on the results of statistical testing, creation a user interface in Matlab © and comprehensive instructions for laboratory focused on the topic of fatigue in the EMG signal.

The task of this thesis was focused on influence of physical load on electrical activity of muscle. There are basic principals and terms from the problematic of measuring electric activity of muscle. Author suggested measuring protocol, got data from group of people, made an application and used this application to analyse measured signals. At the end of this work it was suggested statistical processing and evaluation of results.

This project treats of using electromyograph as a control standard for prosthetic replacement of human arm. The work is mainly focused on surface signals. Reader is briefed by creation and transmission of the signal. The work takes account of the transmission of the signal for surface electrodes and the differences between the ideal and the real connection. Another point of the thesis is the design of basic system model for simulation of the robotic arm movement, which depends on the measured signal. In the practical part there is the realization of the artificial limb movement. It starts with the roboric arm construction and continues with the communication between computer and the robotic arm. First part of practical testing ends with creating of an user interface, which is capable of control all robotic arm movements. The interface is combined with a computer model in Matlab robotic toolbox. The model is able to move in sync with the real robot. The final part is devoted to practical measurement with Biopac instruments. The obtained signal is modified to be used as controller for the robotic arm. Author's aim is to adjust this movement to be most similar to real movement.

The Master´s thesis summarizes the knowledge about controlling of myoelectric prostheses. The Introduction part of this work provides an overview of the anatomy of muscles and their contraction. In case of restricted function of hand, it is necessary to compensate this deficiency by using prosthetic limbs. Among one of the most technically difficult is robotic prosthesis. In this semestral work is myoelectric prosthesis replaced by a robotic arm. Arm is controlled by the electromyographic signals. The signals are recorded by Biopac acquision unit, then processed in LabVIEW and robotic system is controlled by the Arduino platform.

The master´s thesis deals with fatigue evaluation in electrooculography records (EOG). The theoretical part focuses on electrooculography itself, fatigue and methods used for fatigue detection from EOG. The practical part includes a plan of optimal methodology for fatigue evaluation using EOG. The EOG signals are recorded during the volunteers are watching prepared scenes. Those scenes are desribed here. There is also definition of signal processing methods with relevant block diagrams. Laboratory protocol describing EOG signals recording using Biopac data acquisition system is included. Ten volunteers were measured according to this protocol and the signal database was created. In brief questionnaire volunteers were supposed to evaluate fatigue and discomfort of the measurment. Recorded signals were processed and acquired parameters were statistically evaluated. Then the parameters were discussed in terms of fatigue detection ability. On the basis of that software application was created. This application detects fatigue in selected signal. The thesis includes detailed laboratory manual for students.

Η λειτουργία του εγκεφάλου βασίζεται στο σύνολο της ηλεκτροχημικής δραστηριότητας των νευρώνων, που αποτελούν το δομικό λίθο του νευρικού συστήματος. Η καταγραφή των βιολογικών σημάτων, ή βιοσημάτων, τα οποία προκύπτουν από την ηλεκτρική δραστηριότητα των νευρώνων του εγκεφάλου, αποτελούν το αντικείμενο της Ηλεκτροεγκεφαλογραφίας, η οποία είναι μια μη επεμβατική μέθοδος καταγραφής του παραγόμενου, από τον εγκέφαλο, ηλεκτρικού πεδίου. Η πρώτη επιτυχημένη καταγραφή βιοδυναμικών του ανθρώπινου εγκεφάλου αποδίδεται στο Γερμανό φυσιολόγο Hans Berger, ο οποίος στα τέλη της δεκαετίας του 1930, πραγματοποίησε για πρώτη φορά τη μέτρηση διαφορών δυναμικού από την επιφάνεια του κεφαλιού. Σήμερα, το Ηλεκτροεγκεφαλογράφημα (ΗΕΓ) αποτελεί μια ευρέως διαδεδομένη τεχνική κλινικής εξέτασης που χρησιμοποιείται με κύριο σκοπό τη διάγνωση. Στην παρούσα εργασία περιγράφεται η λειτουργία του νευρικού συστήματος, ενώ παρατίθενται στοιχεία ανατομίας του εγκεφάλου. Ακόμα, αναλύεται η φύση και τα χαρακτηριστικά των βιοσημάτων, που λαμβάνονται από την εξωτερική δερματική επιφάνεια του κεφαλιού, ενώ παρουσιάζονται οι βασικές αρχές της Ηλεκτροεγκεφαλογραφίας, ο τρόπος καταγραφής και τα κυριότερα χαρακτηριστικά του σήματος του ΗΕΓ. Εν συνεχεία, περιγράφεται η καταγραφή Ηλεκτροεγκεφαλογραφήματος, που έγινε με τη χρήση του συστήματος MP150 της Biopac. Ο MP150, σε συνδυασμό με το γραφικό περιβάλλον του Acqknowledge 3.8.2 αποτελεί ένα πλήρες σύγχρονο σύστημα καταγραφής πολλών ειδών βιοδυναμικών από διαφορετικές περιοχές του ανθρώπινου σώματος. Αξιοποιώντας τις δυνατότητες του συστήματος αυτού, καταφέραμε να καταγράψουμε και να παρατηρήσουμε τη ρυθμική δραστηριότητα του εγκεφάλου. Επίσης, γίνεται αναφορά στα σημαντικότερα πακέτα εργαλείων του Matlab, που έχουν σαν αντικείμενο την ανάλυση του Ηλεκτροεγκεφαλογραφήματος, ενώ επιχειρείται η περαιτέρω επεξεργασία του σήματος που καταγράφηκε, με τη χρήση ενός από αυτά (eeglab). Επιπλέον, στην εργασία αυτή παρουσιάζονται τα κυριότερα χαρακτηριστικά κάποιων από τις σημαντικότερες μεθόδους ανάλυσης του σήματος που προκύπτει από το ηλεκτροεγκεφαλογράφημα, ενώ παράλληλα γίνεται μια προσπάθεια σύγκρισης των δυνατοτήτων τους, με σκοπό την εξαγωγή χρήσιμων συμπερασμάτων που μπορούν να αξιοποιηθούν σε επόμενες μελέτες. / The entire function of the human brain is based on the electrochemical activity of the neurons, which form the whole nervous system. The recording of the biological signals resulting from the electrical activity of the brain forms the content of Electroencephalography, which is a non invasive method of recording the electric field produced in the human brain. The first successful recording of human brain’s biodynamics was made by German physiologist Hans Berger, who was the first to measure the electrical potential difference on the human head. Nowadays, Electroencephalography (EEG) is a very common clinical examination technique, which is used for the purpose of diagnosis. One of the objects of the present thesis is the description of the nervous system function, while there are some basic elements of the human brain’s anatomy. There is a brief analysis of the nature and features of the biological signals produced by the brain, as well as a presentation of the basic principles of the Electroencephalography. In addition, there is a description of the recording of the EEG signal, which was made with the use of Biopac MP150 system. MP150 and its graphic interface Acqknowledge 3.8.2 form a complete modern data acquisition system, which offers the possibility to record biodynamics from different parts of the human body. Making use of the Biopac system, we were able to record and analyze the brain rhythmic activity. Moreover, the most common Matlab toolboxes that are used for EEG signal processing are presented, while a further analysis of our EEG signal was attempted through eeglab. Furthermore, in the present thesis, the basic features of some of the most important methods of EEG signal analysis are presented. This quite extended presentation is made in order to be used as information for future study and research on EEG signal analysis. Key words: nervous system, biological signals, Electroencephalography, MP150, Acqknowledge, Matlab toolboxes, eeglab, signal analysis

Master’s thesis deal about electroencefalography, measurement EEG signals and analysis measuermed signals. Project contains two basis practical parts. Firts part contain two PC’s programs that’s are used to fundamental analysis to frequence-domain and visual display of brain mapping created with Matlab. Second chapter of practical parts includes two PC’s programs created with LabView. First of them is the EEG biofeedback making use for advanced analyses and second program is used to detection segment of stacionarity.

The master’s thesis is focused on the possibilities of measuring heart rate of ECG signal and its use in therapeutic game of ECG biofeedback. This thesis describes the way of measuring ECG with acquisition unit Biopac and analyzes signal processing for measurement of heart rate – algorithms of QRS detection, HRV analysis. Realisation of therapeutic is designed for applications in Matlab.

This work deals with the affects of multimedia stimuli on the human body, their processing by senses, the possibility of presentation of the stimuli with emphasis on the possibility of measuring the impact of their effect on biological signals using external measuring station. It describes the design and implementation of the application, allowing presentation of the mentioned stimuli and their synchronization with external measuring system Biopac.

This master’s thesis describes a wireless accelerometer module. The aim of this work was to study the properties and involvement of the accelerometer, wireless module design for data transfering from the accelerometer to the PC and the module implementation. As a wireless device is used bluetooth module that enables communication between the product and the computer. The wireless module used rechargable lithium ion battery that helps keep module alive without adapter or net cable.