학술논문

Methods and Measures for Mental Stress Assessment in Surgery: A Systematic Review of 20 Years of Literature
Document Type
Periodical
Source
IEEE Journal of Biomedical and Health Informatics IEEE J. Biomed. Health Inform. Biomedical and Health Informatics, IEEE Journal of. 26(9):4436-4449 Sep, 2022
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Signal Processing and Analysis
Human factors
Surgery
Stress measurement
Systematics
Biomedical monitoring
Task analysis
Biomedical measurement
mental stress
intraoperative stress
workload
cognitive monitoring
physiological monitoring
surgical data science
robot-assisted surgery
microsurgery
operating room
wearable sensors
multi-modal acquisition
data analytics
machine learning
heart-rate variability
eye-tracking
electroencephalography
Language
ISSN
2168-2194
2168-2208
Abstract
Real-time mental stress monitoring from surgeons and surgical staff in operating rooms may reduce surgical injuries, improve performance and quality of medical care, and accelerate implementation of stress-management strategies. Motivated by the increase in usage of objective and subjective metrics for cognitive monitoring and by the gap in reviews of experimental design setups and data analytics, a systematic review of 71 studies on mental stress and workload measurement in surgical settings, published in 2001–2020, is presented. Almost 61% of selected papers used both objective and subjective measures, followed by 25% that only administered subjective tools - mostly consisting of validated instruments and customized surveys. An overall increase in the total number of publications on intraoperative stress assessment was observed from mid-2010 s along with a momentum in the use of both subjective and real-time objective measures. Cardiac activity, including heart-rate variability metrics, stress hormones, and eye-tracking metrics were the most frequently and electroencephalography (EEG) was the least frequently used objective measures. Around 40% of selected papers collected at least two objective measures, 41% used wearable devices, 23% performed synchronization and annotation, and 76% conducted baseline or multi-point data acquisition. Furthermore, 93% used a variety of statistical techniques, 14% applied regression models, and only one study released a public, anonymized dataset. This review of data modalities, experimental setups, and analysis techniques for intraoperative stress monitoring highlights the initiatives of surgical data science and motivates research on computational techniques for mental and surgical skills assessment and cognition-guided surgery.