Coaching with audiovisual technology in acute-care hospital settings: systematic review

Feasibility of Wearable Sensors to Assess Cognitive Load During Clinical Performance: Lessons Learned and Blueprint for Success

INTRODUCTION

Cognitive load (CogL) is increasingly recognized as an important resource underlying operative performance. Current innovations in surgery aim to develop objective performance metrics via physiological monitoring from wearable digital sensors. Surgeons have access to consumer technology that could measure CogL but need guidance regarding device selection and implementation. To realize the benefits of surgical performance improvement these methods must be feasible, incorporating human factors usability and design principles. This paper aims to evaluate the feasibility of using wearable sensors to assess CogL, identify the benefits and challenges of implementing devices, and develop guidance for surgeons planning to implement wearable devices in their research or practice.

METHODS

We examined the feasibility of wearable sensors from a series of empirical studies that measured aspects of clinical performance relating to CogL. Across four studies, 84 participants and five sensors were involved in the following clinical settings: (i) real intraoperative surgery; (ii) simulated laparoscopic surgery; and (iii) medical team performance outside the hospital.

RESULTS

Wearable devices worn on the wrist and chest were found to be comfortable. After a learning curve, electrodermal activity data were easily and reliably collected. Devices using photoplethysmography to determine heart rate variability were significantly limited by movement artifact. There was variable success with electroencephalography devices regarding connectivity, comfort, and usability.

CONCLUSIONS

It is feasible to use wearable sensors across various clinical settings, including surgery. There are some limitations, and their implementation is context and device dependent. To scale sensor use in clinical research, surgeons must embrace human factors principles to optimize wearability, usability, reliability, and data security.

Enhancing surgical performance in cardiothoracic surgery with innovations from computer vision and artificial intelligence: a narrative review

When technical requirements are high, and patient outcomes are critical, opportunities for monitoring and improving surgical skills via objective motion analysis feedback may be particularly beneficial. This narrative review synthesises work on technical and non-technical surgical skills, collaborative task performance, and pose estimation to illustrate new opportunities to advance cardiothoracic surgical performance with innovations from computer vision and artificial intelligence. These technological innovations are critically evaluated in terms of the benefits they could offer the cardiothoracic surgical community, and any barriers to the uptake of the technology are elaborated upon. Like some other specialities, cardiothoracic surgery has relatively few opportunities to benefit from tools with data capture technology embedded within them (as is possible with robotic-assisted laparoscopic surgery, for example). In such cases, pose estimation techniques that allow for movement tracking across a conventional operating field without using specialist equipment or markers offer considerable potential. With video data from either simulated or real surgical procedures, these tools can (1) provide insight into the development of expertise and surgical performance over a surgeon's career, (2) provide feedback to trainee surgeons regarding areas for improvement, (3) provide the opportunity to investigate what aspects of skill may be linked to patient outcomes which can (4) inform the aspects of surgical skill which should be focused on within training or mentoring programmes. Classifier or assessment algorithms that use artificial intelligence to 'learn' what expertise is from expert surgical evaluators could further assist educators in determining if trainees meet competency thresholds. With collaborative efforts between surgical teams, medical institutions, computer scientists and researchers to ensure this technology is developed with usability and ethics in mind, the developed feedback tools could improve cardiothoracic surgical practice in a data-driven way.