Abstract

We present a wireless, wearable device to measure transcutaneous partial oxygen pressure (tcpO2) non-invasively. The device, tuned to physiological range pO2, detects changes in phosphorescence lifetime and intensity of ultra-bright metalloporphyrins embedded within breathable films. We have implemented machine learning algorithms to improve the accuracy of the measurements against changes in temperature, photobleaching, inter-device/film variations, etc. Our first in human measurements reveal the devices are able to detect quick and subtle changes in tcpO2 due to local and systemic changes in blood flow of skin or deeper muscle tissue. Models to extract tissue oxygenation and oxygen consumption rate are explored.

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