Surface-Based Electromyography Gesture Profiling of Laparoscopic Tools Using a Wearable Sensor
This study explores surface-based electromyography (sEMG) to evaluate the effects of tool handling and fatigue on the muscle activation of laparoscopy surgeons. Specifically, the Myo Armband is used because it is a wearable, unobtrusive, and wireless sensor. Collected EMG signatures showed that more complex gestures have more active muscle groups. For the fatigued state, analysis of the signatures using the RMS feature showed that for more complex gestures, RMS increased because of muscle compensation due to fatigue. Accuracy exercise findings showed that there is a decrease in %accuracy when using an endoscope compared to when looking directly and there is a slight decrease in %accuracy once fatigue is induced. 100% accuracy cannot be reached due to awkward tool handling. Through various experiments, this study presented possible methods to evaluate the effects of tool handling and fatigue on the muscle activation of surgeons through use of sEMG. Analysis of these signatures may lead to better understanding on how specific tool design affects muscle activity and muscle fatigue, and to utilize this as a basis for a more ergonomic laparoscopic set-up and tool design.
Salud, I., Bolingot, H. J., Macaraig, L. C., Libatique, N., & Tangonan, G. (2021). Surface-based electromyography gesture profiling of laparoscopic tools using a wearable sensor. In Y. Shiraishi, I. Sakuma, K. Naruse, & A. Ueno (Eds.), 11th Asian-Pacific Conference on Medical and Biological Engineering (pp. 31–37). Springer International Publishing. https://doi.org/10.1007/978-3-030-66169-4_5