| Summary: | 碩士 === 國立交通大學 === 電機資訊國際學位學程 === 100 === In the recent decade, the accelerated emergence of an aged population alongside increased medical costs has been recognized as a worldwide problem. Whereas a shortage in medical personnel will leave the healthcare system unable to meet the requirements of a growing number of elderly patients, even more will be deprived of access to quality healthcare due to the high costs of diagnosis and treatment. As a result, in recent years, the field of biomedical engineering has emerged as a top priority research and development topic.
In response to the needs of healthcare monitoring applications in particular emergency care, long-term observation and cognitive science, we propose the development of an integrated brain-heart monitoring system and provide a demonstration platform as a proof of concept for future works and development along this topic. The motivation of this work is threefold; first is to improve patient experience by means of a portable biomedical device; second, to reduce overall system costs associated with the equipment, operations, logistics and management in both hospital and home care settings; and third, to pave the way for new research directions relating to brain-heart monitoring applications.
In this thesis, we present the development of a biomedical signal multiprocessor comprising a novel diffuse optical tomography (DOT) processor for brain imaging, an independent component analysis (ICA) processor for removing electroencephalogram (EEG) signal artifacts, and a heart rate variability (HRV) analysis processor for monitoring electrocardiogram (ECG) signals. Furthermore, in order to reduce power consumption and prolong operating time, a lossless data compressor is employed to reduce bandwidth requirements during wireless transmission of biomedical data. The multiprocessor design is implemented both as an AHB-compatible IP for ARM-based SOCs on a Xilinx FPGA and as an IC fabricated using UMC 65nm CMOS technology.
To demonstrate the functionality and real-time application of the developed multiprocessor design, a complete, end-to-end brain-heart monitoring system platform employing the SoC-based implementation is presented. EEG, ECG and/or functional near infrared (fNIR) signals acquired by an analog front-end IC are processed or bypassed by the biomedical multiprocessor depending on configuration commands sent wirelessly from a remote science station. Processed or raw biomedical data optionally compressed by a lossless data compressor are packaged according to a fixed output data format and finally sent back to the remote science station for real-time LCD display, data storage, or further off-line processing and analysis.
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