Christopher D'Ambrosia, Estella Y. Huang, Nicole H. Goldhaber, Henrik Christensen, Ryan C. Broderick, Lawrence G. Appelbaum
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Physiological Detection of Intraoperative Errors During Robot-Assisted Surgery
Background
This study tested the measurement of operator physiology during performance on robot-assisted surgery simulations to determine if these signals can identify errors and classify high and low performers.
Methods
57 participants performed digital simulations on da Vinci Xi system. Simulation videos, electrocardiogram (EKG), and electroencephalography (EEG) were analysed using linear mixed effects models.
Results
Relative to non-error intervals, errors elicited significant differences in EKG and EEG measures, including high-frequency power, interbeat interval and ratio of theta-to-alpha EEG power. High and low performers differed significantly in several of these measures, while classification models were accurate for the detection of errors (85.7%) and performance groups (96.3%), and using physiological signals leading up to errors, could accurately predict upcoming errors (85.7%).
Conclusions
Noninvasive recording of physiology can differentiate error from non-error intervals and performance groups, leading to the possibility that online physiology can develop into training or early warning systems.
期刊介绍：
The International Journal of Medical Robotics and Computer Assisted Surgery provides a cross-disciplinary platform for presenting the latest developments in robotics and computer assisted technologies for medical applications. The journal publishes cutting-edge papers and expert reviews, complemented by commentaries, correspondence and conference highlights that stimulate discussion and exchange of ideas. Areas of interest include robotic surgery aids and systems, operative planning tools, medical imaging and visualisation, simulation and navigation, virtual reality, intuitive command and control systems, haptics and sensor technologies. In addition to research and surgical planning studies, the journal welcomes papers detailing clinical trials and applications of computer-assisted workflows and robotic systems in neurosurgery, urology, paediatric, orthopaedic, craniofacial, cardiovascular, thoraco-abdominal, musculoskeletal and visceral surgery. Articles providing critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies, commenting on ease of use, or addressing surgical education and training issues are also encouraged. The journal aims to foster a community that encompasses medical practitioners, researchers, and engineers and computer scientists developing robotic systems and computational tools in academic and commercial environments, with the intention of promoting and developing these exciting areas of medical technology.
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