@inproceedings{116c86523493406ebfa929c286a88997,
title = "Remote photoplethysmography system for unsupervised monitoring regional anesthesia effectiveness",
abstract = "Determining the level of regional anesthesia (RA) is vitally important to both an anesthesiologist and surgeon, also knowing the RA level can protect the patient and reduce the time of surgery. Normally to detect the level of RA, usually a simple subjective (sensitivity test) and complicated quantitative methods (thermography, neuromyography, etc.) are used, but there is not yet a standardized method for objective RA detection and evaluation. In this study, the advanced remote photoplethysmography imaging (rPPG) system for unsupervised monitoring of human palm RA is demonstrated. The rPPG system comprises compact video camera with green optical filter, surgical lamp as a light source and a computer with custom-developed software. The algorithm implemented in Matlab software recognizes the palm and two dermatomes (Medial and Ulnar innervation), calculates the perfusion map and perfusion changes in real-time to detect effect of RA. Seven patients (aged 18-80 years) undergoing hand surgery received peripheral nerve brachial plexus blocks during the measurements. Clinical experiments showed that our rPPG system is able to perform unsupervised monitoring of RA.",
keywords = "Dermatomes, Palm detection, Perfusion, Photoplethysmography imaging, Regional anesthesia, Remote photoplethysmography, Skin microcirculation, Unsupervised monitoring",
author = "U. Rubins and A. Miscuks and Z. Marcinkevics and M. Lange",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; 2nd International Conference on Biophotonics-Riga 2017, BPR 2017 ; Conference date: 27-08-2017 Through 29-08-2017",
year = "2017",
doi = "10.1117/12.2297158",
language = "English",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Janis Spigulis",
booktitle = "Biophotonics - Riga 2017",
address = "United States",
}