Combining Time-Dependent Force Perturbations in Robot-Assisted Surgery Training

Teleoperated robot-assisted minimally-invasive surgery (RAMIS) offers many advantages over open surgery. However, there are still no guidelines for training skills in RAMIS. Motor learning theories have the potential to improve the design of RAMIS training but they are based on simple movements that do not resemble the complex movements required in surgery. To fill this gap, we designed an experiment to investigate the effect of time-dependent force perturbations on the learning of a pattern-cutting surgical task. Thirty participants took part in the experiment: (1) a control group that trained without perturbations, and (2) a 1Hz group that trained with 1Hz periodic force perturbations that pushed each participant's hand inwards and outwards in the radial direction. We monitored their learning using four objective metrics and found that participants in the 1Hz group learned how to overcome the perturbations and improved their performances during training without impairing their performances after the perturbations were removed. Our results present an important step toward understanding the effect of adding perturbations to RAMIS training protocols and improving RAMIS training for the benefit of surgeons and patients.

What Can Spatiotemporal Characteristics of Movements in RAMIS Tell Us?

Quantitative characterization of surgical movements can improve the quality of patient care by informing the development of new training protocols for surgeons, and the design and control of surgical robots. Here, we present a novel characterization of open and teleoperated suturing movements that is based on principles from computational motor control. We focus on the extensively-studied relationship between the speed of movement and its geometry. In three-dimensional movements, this relationship is defined by the one-sixth power law that relates between the speed, the curvature, and the torsion of movement trajectories. We fitted the parameters of the one-sixth power law to suturing movements of participants with different levels of surgical experience in open (using sensorized forceps) and teleoperated (using the da Vinci Research Kit / da Vinci Surgical System) conditions from two different datasets. We found that teleoperation significantly affected the parameters of the power law, and that there were large differences between different stages of movement. These results open a new avenue for studying the effect of teleoperation on the spatiotemporal characteristics of the movements of surgeons, and lay the foundation for the development of new algorithms for automatic segmentation of surgical tasks.

Instrument Orientation-Based Metrics for Surgical Skill Evaluation in Robot-Assisted and Open Needle Driving

The technical skill of surgeons directly impacts patient outcomes. Advanced tracking systems enable the development of objective motion-based metrics for skill evaluation, but these metrics are not sufficient to evaluate the performance in complex surgical tasks. In this study, we developed metrics for surgical skill evaluation that are based on the orientation of the surgical instruments. Experienced robotic surgeons and novice users performed teleoperated (using the da Vinci Research Kit) and open needle-driving. Task time and the rate of orientation change successfully distinguished between experienced surgeons and novice users. Path length and the normalized angular displacement allowed for a good separation only in part of the experiment. Our new promising metrics for surgical skill evaluation captured technical aspects that are taught during surgeons' training. They provide complementing evaluation to those of classical metrics. Orientation-based metrics add value to skill assessment and may be an adjunct to classic objective metrics providing more granular discrimination of skills.