Learning Kinematic Constraints in Laparoscopic Surgery

Negating the fulcrum effect in manual laparoscopic surgery: Investigating skill acquisition with a haptic simulator

BACKGROUND

Manual laparoscopic surgery requires extensive training and familiarization. It has been suggested that motion inversion caused by the 'fulcrum effect' is key to motor challenges. We investigate the potential of a conceptual semi-robotic handheld tool that negates natural inversion.

METHODS

A custom laparoscopic simulator with haptic feedback was developed to allow interactive evaluation of the conceptual tool via virtual prototyping, prior to fabricating a physical prototype. Two groups of eight participants each used either the conceptual or a regular virtual tool over a ten week study to complete two abstract tasks of motor control and force regulation.

RESULTS

Statistically significant higher rates of skill improvement were demonstrated with the conceptual tool for motion efficiency, task completion time and error reduction. Force regulation increased for both groups but without significant differences.

CONCLUSIONS

The results indicate potential for fulcrum-negating hand tools in reducing the time needed to acquire motor skills.

Data sample size needed for prediction of movement distributions

Human movement ability should be described not only by its typical behavior, but also by the wide variation in capabilities. This would mean that subjects that are encouraged to move throughout their workspace but otherwise free to move any way they like might reveal their unique movement tendencies. In this study, we investigate how much information (data) is needed to reliably construct a movement distribution that predicts an individual's movement tendencies. We analyzed the distributions of position, velocity and acceleration data derived during self-directed motor exploration by stroke survivors (n=10 from a previous study) and healthy individuals (n=5). We examined whether these simple kinematic variables differed in terms of the amount of data required. We found a trend of decreasing time needed for characterization with the order of kinematic variable, for position, velocity, and acceleration, respectively. In addition, we investigated whether data requirements differ between stroke survivors and healthy. Our results suggest that healthy individuals may require more data samples (time for characterization), though the trend was only significant for position data. Our results provide an important step towards using statistical distributions to describe movement tendencies. Our findings could serve as more comprehensive tools to track recovery in or design more focused training intervention in neurorehabiliation applications.

Effective part-task training as evidence of distinct adaptive processes with different time scales

For some types of visuo-motor transformations like large visuo-motor rotations or the complex transformation of a sliding first-order lever, distinct adaptive processes have been hypothesized that produce a rapid, discrete approximation of the transformation and a slow, graded fine tuning, respectively. Here we investigate whether part-task training of only the second of these processes, namely the fine tuning, transfers to the subsequent performance in a condition with the full transformation of the sliding first-order lever. Therefore, we compared performance of three groups with different practice conditions during transfer to the full transformation. While two groups only practiced the fine tuning without the right-left inversion of the lever prior to transfer, a third group practiced the full lever transformation. Our results show a positive, but less than perfect transfer of the isolated practice of the fine tuning on performance with the full transformation. For the fine tuning itself, transfer was not reliably different from being perfect. The observation that the fine tuning can be acquired separately and added to the later adaptation to the left-right inversion of the lever supports the notion that these slow and fast processes progress rather independently. The additional finding that the preceding acquisition of the fine tuning also facilitates the subsequent rapid process could be due to generalized learning-to-learn or to a more precise assignment of movement errors to the process from which they originate.