UC San Diego

The importance of health sensing continues to grow in light of an aging global population, the prevalence of chronic illness, a dramatic rise in mental health disorders, and a healthcare system with gaps in equal coverage for everyone. Wearable sensing technologies have greatly expanded health monitoring and human-computer interface applications, bridging the gaps between traditional clinical instrumentation and urgent need for remote, daily healthcare. Noninvasive electrophysiology tools in particular seek to measure signals from the brain and body at conventional sensing locations such as the scalp, but require bulky instrumentation and cumbersome setup procedures, limiting prolonged use in real-world settings. As an appealing alternative, electrophysiological sensing within the ear provides continuous physiological and cognitive state monitoring in an unobtrusive form factor. The proximity of the ear to the central nervous system and the high density of exocrine glands in the ear canal motivate the integration of multiple sensing modalities including electroencephalography (EEG), electrodermal activity (EDA), and metabolite detection into a single in-ear device. The work in this dissertation extends the capabilities and amplifies the impact of in-ear sensing systems addressing several of their limitations including electrode performance, manufacturing scalability, and low-power acquisition hardware. A primary aim of this work is to enhance in-ear sensors to support higher electrode count, offering reliable, long-term wearability, user comfort, and straightforward fabrication methods to benefit investigation of physiological signals in a broader subject pool. Another primary aim of this work is to provide high-performance data acquisition hardware to meet the needs of mobile health monitoring from multimodal sensor arrays. First, new methods for the development of in-ear sensors are presented which deliver user-generic dry-contact electrodes made from standard printed circuit boards (PCBs). Electrodes are characterized using electrochemical impedance spectroscopy (EIS) and a series of in-vivo electrophysiological studies. The second part presents a complete and versatile wireless electrophysiology data acquisition system (weDAQ) that is demonstrated for in-ear EEG and on-body electrophysiology as an open-source resource for the biomedical community. Subsequently, a neural interface system-on-chip (NISoC) integrated circuit (IC) is presented which substantially lowers the power and improves signal integrity through a new correlated double sampling (CDS) technique. Finally, the sensing system is evaluated for use with subjects for auditory steady-state response (ASSR), electrodermal activity (EDA), and attention state classification (vigilance), demonstrating its utility as a versatile, mobile health monitoring platform.