Authors: Ali Keshavarz Panahi; Sohyung Cho; Michael M. Awad
Addresses: Industrial and Manufacturing Engineering, Southern Illinois University, Edwardsville, IL 62026, USA ' Industrial and Manufacturing Engineering, Southern Illinois University, Edwardsville, IL 62026, USA ' School of Medicine, Washington University in Saint Louis, Saint Louis, MO 63110, USA
Abstract: The goal of this study is to detect muscle fatigue and time-to-fatigue in vulnerable muscle groups, before determining whether the former has any effect on surgical performance. In the experiment, surface electromyography (sEMG) was deployed to record the muscle activations of 12 subjects while performing fundamentals of laparoscopic surgery (FLS) tasks for a total of three hours. In all, 16 muscle groups were tested. The resultant data were then reconstructed using recurrence quantification analysis (RQA). In addition, a subjective fatigue assessment was conducted to draw comparisons with the RQA results. The subjects' performance was also investigated via a FLS task performance analysis, the results demonstrating that RQA can detect muscle fatigue in 12 muscle groups as well as their time-to-fatigue. The results also indicated that RQA and subjective fatigue assessment are very closely correlated (p-value < 0.05). However, the performance analysis results showed that the subjects' performance improved over time.
Keywords: minimally invasive surgery; MIS; fatigue analysis; recurrence quantification analysis; RQA; FLS task performance analysis; subjective fatigue assessment.
International Journal of Biomedical Engineering and Technology, 2020 Vol.34 No.3, pp.234 - 248
Received: 26 Jun 2017
Accepted: 20 Nov 2017
Published online: 25 Nov 2020 *