Low-power system-on-chip (SOC) implementation for self-sufficient wireless respiratory data and energy harvesting system

Abstract

Recent studies and systems have made it possible to measure respiratory rate comfortably and non-invasively; however, these methods do not particularly focus on their convenience. Specifically, either patient mobility is decreased because they are confined within the respiratory sensor's effective range or the wireless apparatus attached to them necessitates battery replacements every few days. A solution to this problem is to utilize the attachment solution, but remove the battery component. The overall project of this thesis proposes that this can be done by using the respiratory effort itself to power the apparatus. However, with current portable harvesting technology, respiratory effort does not yield more than a couple milliwatts of power at best, thus the apparatus must be optimized for minimum power consumption. Beyond low-power hardware selection, lies the need for low-power software implementation of the respiratory signal's digital processing. This thesis investigates a handful of algorithms and their suitability for this power-restricted environment, and ultimately demonstrates the feasibility of measuring respiratory rate with less than 100 μW of average power by utilizing a low-power system-on-chip. Rather than utilizing the chip's analog-to-digital converter, as is normal convention, a simple comparator approach was adopted. Although rather simplistic and atypical, the minimalistic attitude towards signal processing presented in this thesis is necessary for the development of systems tailored to incredibly low-power environments.