Description
Early detection of symptoms enables early diagnosis and treatment of several life threatening conditions by monitoring vital signs continuously. With advances in technology, many new pervasive monitoring systems offers monitoring physiological signals remotely. Although these products enable pervasive monitoring of certain physiological signals, each of the products available in the market caters to a specific functionality. Research has indicated that combined, collaborative analysis of various physiological signals is needed in the diagnosis of certain diseases. So, there is a need to develop a system that can facilitate the monitoring of multiple physiological signals with reconfigurable architecture to include developing technologies, thereby providing a lab-in-a-box kind of experience. This thesis develops a system with reconfigurable hardware and open architecture, component-based software to enable multisensory physiological signal monitoring. In this study, a physiological data acquisition system has been implemented to record the electroencephalogram (EEG), Electromyography (EMG) and motion data of a subject and transmit the data to a host. This system can record up to 32 channels of EEG data, 16 channels of EMG data, and 9 axis motion data. Recorded Data is transmitted to a host wirelessly via Bluetooth Low Energy or Enhanced Shock Burst protocols. Components in the system are configured for not only monitoring signals but also realizing use cases/applications like BMI/BBMI. The BBMI (Bidirectional Brain Machine Interface) system provides 32 channels of brain activity recording and stimulation electronics, supporting up to 16 channels of high voltage stimulation to the brain or spinal cord. Core of the developed modular BBMI system uses INTAN RHD2216 for Analog to Digital conversion of the brain signals, Nordic Nrf51822 highly flexible multi-protocol SOC with Enhanced Shock Burst protocol is utilized for near field communication, and ultrasonic power transfer module is used for wireless charging. A component based software platform was developed for recording and real time controlling of stimulation. A reconfigurable system with clear distinction between components has been engineered.
