Analog front-end circuits for health monitoring applications

Abstract

According to the World Health Organization (WHO), 60% of all deaths are due to chronic diseases such as heart disease, cancer, diabetes, stroke, etc. Continuous health monitoring of such patients can be an efficient method to evaluate and control the side effects of these diseases. However, traditional health monitoring devices are relatively bulky and power hungry to be used comfortably by the patient for long-term monitoring. The need for frequent battery replacement and/or charging is another inconvenience that can interrupt data acquisition, particularly when medical actions need to be taken based on this data. It is, therefore, highly desirable to develop a small-size, reliable and easy-to-use personal health monitoring system. Such a system with sensing, signal processing, and communications capabilities enable continuous long-term monitoring of patients.

The work done in this dissertation lays the ground work for micro- and nano-power interface integrated circuits capable of adapting to different sensing modalities. The presented circuit techniques can extract high fidelity bio-signals and digitize them using standard silicon technology and ultra-low energy consumption. The reduction in energy needs would allow truly autonomous health monitoring systems that can be powered using available or opportunistic energy harvesting approaches as they continue to be developed. With the miniaturization achieved by the IC, flexible electronics and multi-channel approaches could also be used to reduce the size and weight of the monitoring devices even further to provide the comfort level needed by the patients.

I extend such approaches to acquire other physiological signals beyond ECG, such as Electroencephalogram (EEG), Electromyography (EMG), and blood pressure. We also investigate incorporating digitization in the signal path and using the control signals in the analog-to-digital converter (ADC) to program the bandwidth of the instrumentation amplifier (IA)/filter stage to extract only the biological signal of interest. The filtering approach is based on a switched-R-MOSFET-C (SRMC) technique to achieve ultra-low cut-off frequency. An 8-bit successive approximation register (SAR) ADC, following the filter, quantizes the signal, while the SAR control logic is re-used to accurately program the filter bandwidth from 40 Hz to 320 Hz with a 40 Hz step.

I start by proposing a power-efficient, highly linear AFE integrated circuit (IC) for Electrocardiogram (ECG) acquisition applications. The proposed AFE incorporates hardware sharing approaches for combining filtering and buffering functions in one circuit module to reduce the microchip size and energy consumption.

In any health monitoring system, the analog front-end (AFE) is by far the most critical block since it determines the quality of the signal to be processed. This thesis investigates circuit-level architectures for miniaturized ultra low-power, high-linearity AFE for medical-grade health monitoring devices.

A sensing system for arterial pulse waveform (APW) acquisition is also presented which includes an AFE circuit connected to a packaged silicone-coated resistive-bridge pressure sensor for detecting APW through direct skin contact in a non-invasive manner. An automatic calibration circuit is proposed to compensate for the resistive-bridge offset and can reduce such offset down to 1 mV. Together with ECG, EEG, and EMG sensing system, the IC realizes a multi-signal sensing system for a complete health evaluation.