Wearable biosensors and mobile healthcare (mHealth) technologies are revolutionizing modern healthcare delivery by providing access to pragmatic, medical-grade services that are scalable outside of the hospital setting. Electrodermal activity (EDA) is a physiological signal of particular importance within the mHealth community because it is a useful marker for the physiological arousal of the sympathetic nervous system used in studies of depression, anxiety disorders, stress management, and many more. EDA refers to electrical variations in skin conductance and capacitance occurring at the surface of the skin due to changes in sweat secretion. Modern EDA biosensors often require significant analog and digital resources to acquire and record high-quality EDA signals due to the wide range and variability of skin conductivity across populations. There are significant challenges in maintaining a balance between high-performance sensing capabilities of a biosensor and its ability to be small in size, unobtrusive, and long-lasting. The work within this thesis addresses the research question of how low-resource digital design can be used to improve the size, power efficiency, and utility of wearable EDA sensors while maintaining high-quality physiological sensing capabilities. An ultra-low resource system for EDA measurement is presented that implements a quasi-digital EDA sensor topology for measuring both the
conductive and capacitive components of the EDA signal and requires no analog-to-digital converters or in-phase and quadrature demodulation. Additionally, we apply on-board compression and storage of the EDA signal within a 16-bit microcontroller to improve sensor size and power efficiency by removing the external data storage and transmission requirements for long-term EDA monitoring. The accuracy, precision, dynamic range, and power efficiency of the developed system is characterized and the devices are evaluated in a pilot study.
|Advisor:||Halter, Ryan J|
|Commitee:||Odame, Kofi M, Hansen, Eric W, Ertin, Emre|
|School Location:||United States -- New Hampshire|
|Source:||DAI-B 81/2(E), Dissertation Abstracts International|
|Subjects:||Biomedical engineering, Electrical engineering|
|Keywords:||Compression, Electrodermal activity, Wearable biosensors, Microcontrollers|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be