Algorithm for evaluating tissue circulation based on spectral changes in wearable photoplethysmography device

Abstract

Tissue circulation monitoring is an effective method to detect compromised circulation in time after tissue transplantation. Use of flexible photoplethysmography (PPG) devices for tissue circulation monitoring allows the continuous measurement of signals at multiple positions on the tissue. An algorithm of tissue circulation evaluation that considers motion artifacts is also necessary for such devices, although conventional motion evaluation algorithms cannot be used with weak PPG signals during compromised circulation. In this study, we developed an algorithm that discriminates between three states – normal circulation, compromised circulation, and artifacts. We measured the signals from different attachment positions on eight healthy volunteers for investigating the variation of signals between these positions. We then applied the algorithm to evaluate normal and compromised circulations during a resting position and with motion events. The efficiency of the algorithm was evaluated based on the data usage and specificity calculated from one-week continuous measurements. The results show that, for all volunteers, the algorithm correctly identified normal and compromised circulation signals even when the signal was partially corrupted due to motion artifacts. Seriously corrupted data were identified as artifacts. Data usage and specificity during one-week monitoring on volunteers were 89.7 ± 3.0% and 99.3 ± 0.6%, respectively. The results indicate that our device achieves effective one-week monitoring on tissues and our algorithm correctly evaluates tissue circulation with wearable PPG devices. Our device and algorithm have the potential to assist medical staff during post-operative observation of transplanted tissues.