Macquarie University
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Physiological signal acquisition system for wireless communication

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posted on 2022-03-28, 12:50 authored by Zhihao Cui
National Acoustic Laboratory uses HEARLab System to record to record the brain function of hearing loss people. Typically, the principle of the HEARLab System is to detect the hearing loss level of the patient by recording the patient's electroencephalography (EEG). Recently, because of the wired signal transmission method, the patient has to be constrained in a particular space, which causes inconvenience to the experimenter and the subject. Thus, the aim of this project is to use a wireless connection method to replace the traditional physical line connection method and to achieve the Internet of things (IoT). In this thesis, Texas Instruments CC3200 LaunchPad is to be used to make the wireless information transmission. Therefore, based on the Wi-Fi environment the new HEARLab System can wirelessly transmit information between the PC and the CC3200 LaunchPad by using User Datagram Protocol (UDP). The UDP is written in Java and discussed in detail in the thesis. Further work aims to process the received EEG signals. Typically, regarding the signal processing principle, the received EEG signals are stored in digital format on the computer. On this occasion Java digital signal processing is going to be introduced in the thesis. All the related code or tools will be attached in Dropbox.


Table of Contents

Introduction -- Background -- Communication between the CC3200 LaunchPad and the computer -- DSP, signal display and GUI -- Wireless HEARLab System prototype -- Real-time wireless HEARLab System prototype demonstration -- Result -- Conclusion -- Abbreviations -- Bibliography -- Appendices.


Empirical thesis. Bibliography: pages 67-69

Awarding Institution

Macquarie University

Degree Type

Thesis bachelor honours


BSc (Hons), Macquarie University, Faculty of Science and Engineering, School of Engineering

Department, Centre or School

School of Engineering

Year of Award


Principal Supervisor

Oya Sevimli

Additional Supervisor 1

Loi Teck

Additional Supervisor 2

Cong-van Nguyen


Copyright Zhihao Cui 2016. Copyright disclaimer:




1 online resource (vii, 77 pages colour illustrations)

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