Towards bioelectric signal-enabled human healthcare monitoring: state-of-the-art, design strategies, challenge, and future

This project focuses on the design and evaluation of front-end circuits for bioelectric signal acquisition, drawing insights from contemporary research in human healthcare monitoring. Bioelectric signals, such as electroencephalogram (EEG), electrocardiogram (ECG), electrooculogram (EOG), and electromyogram (EMG), are critical for diagnostic and monitoring applications. The methodology involves a comprehensive analysis of state-of-the-art design strategies and challenges associated with acquiring these signals, including considerations for noise reduction, power efficiency, common-mode rejection, and miniaturization. The project aims to develop a simulation model for a multi-channel bioelectric signal acquisition system, incorporating advanced circuit topologies for amplification, filtering, and analog-to-digital conversion. Furthermore, it will explore the integration of commercial biosensors and components, evaluating their

performance characteristics against established benchmarks and identifying potential improvements. This research will contribute to understanding the practical implementation of high-fidelity bioelectric signal acquisition systems, addressing key design considerations for next-generation wearable and implantable healthcare devices, and informing future developments in biosensor circuit design.

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