Design and implementation of wearable monitoring system for mental health management

Abstract

With an increasing demand for wearable healthcare system, more complex analysis with physiological signals is required for many applications. The bulky instruments are developed in a small size of portable devices and recently some of them are also implemented as small as it is attached on the body or clothes. The semiconductor system shrinks all the functions on a small chip. In addition, the wearable systems require more and more complex operations for diverse applications such as sleep monitoring, emotion detection and mental health monitoring. Three kinds of integrated circuit (IC) solutions for wearable monitoring system for mental health are dealt with.

The first solution is the monitoring system using both brain and cardiac signals. The chaos-processor treats both electroencephalogram (EEG) and heart rate variability (HRV). An independent component analysis (ICA) accelerator decreases the error of HRV extraction from 5.94% to 1.84% in the preprocessing step. Largest Lyapunov exponent (LLE), as well as conventional features such as mean and standard variation, is calculated with NCA acceleration. The chaos-processor fabricated in $0.13 \mu m$ CMOS technology consumes only $259.6 \mu W$.

The second solution is the cardiac monitoring system which is made in the shape of chest patch. The cardiac monitoring SoC extracts several features from HRV. There are, for example, nonlinear features such as LLE, SampEn and ApEn, frequency-domain features such as LFHF, peakLF and peakHF, and time-domain features such as mean HR, SDNN and pNN50. With those features, the mental stress is estimated using support vector machine (SVM). The chip is fabricated in $0.13 \mu m$ CMOS process with $4 \times 2mm^2$ of dimension. It operates in 1.2V of supply voltage and 1MHz of operating frequency.

The third solution deals with more complex analysis of EEG and add the feedback path. A neuro-feedback stimulation (NFS) chip is proposed and integrated into the mental h...