Since the introduction of robot-assisted laparoscopic surgery, efforts have been made to incorporate force sensing technologies to monitor critical components and to provide force feedback. The advanced laparoscopic robotic system (AdLap RS) is a robotic platform that aims to mak
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Since the introduction of robot-assisted laparoscopic surgery, efforts have been made to incorporate force sensing technologies to monitor critical components and to provide force feedback. The advanced laparoscopic robotic system (AdLap RS) is a robotic platform that aims to make robot technology more sustainable through the use of the fully reusable shaft-actuated tip-articulating (SATA) instruments. The SATA instrument driver features electronics and sensors exposed to the sterile environment, which complicate the sterilisation process. The aim of this study was to develop and validate smart sensing in stepper motors using the back electromotive force in a newly developed Smart SATA Driver (SSD), eliminating the need for sensors in the sterile environment. Methods: The stepper drivers were equipped with TMC2209 ICs featuring StallGuard technology to measure back EMF. The tip was actuated up until a set StallGuard threshold value was reached, at which the resulting tip force was measured. This cycle was repeated ten times for a range of threshold levels. A regression analysis with a power series model was used to determine the quality of the fit. Results: The SSD is capable of exerting tip forces between 2.4 and 8.2 N. The back EMF force test demonstrated a strong correlation between obtained StallGuard values and measured tip forces. The regression analysis showed an R-squared of 0.95 and a root Mean squared error of 0.4 N. Discussion: The back EMF force test shows promise for force feedback, but its accuracy limits real-time use due to back EMF fluctuations. Future improvements in motor stability and refining the back EMF model are needed to enable real-time feedback. Conclusion: The strong correlation during the back EMF force test shows its potential as a low-budget method for detecting motor stalls and estimating tool–tissue forces without the need for sensors in laparoscopic instruments.@en