Roland W Partridge1, Fraser S Brown2, Paul M Brennan3, Iain A M Hennessey4, Mark A Hughes3. 1. Royal Hospital for Sick Children, Edinburgh, UK RolandPartridge@nhs.net. 2. University of Edinburgh Medical School, Edinburgh, UK. 3. Western General Hospital, Edinburgh, UK. 4. Alder Hey Children's Hospital, Liverpool, UK.
Abstract
AIM: To assess the potential of the LEAP™ infrared motion tracking device to map laparoscopic instrument movement in a simulated environment. Simulator training is optimized when augmented by objective performance feedback. We explore the potential LEAP has to provide this in a way compatible with affordable take-home simulators. METHOD: LEAP and the previously validated InsTrac visual tracking tool mapped expert and novice performances of a standardized simulated laparoscopic task. Ability to distinguish between the 2 groups (construct validity) and correlation between techniques (concurrent validity) were the primary outcome measures. RESULTS: Forty-three expert and 38 novice performances demonstrated significant differences in LEAP-derived metrics for instrument path distance (P < .001), speed (P = .002), acceleration (P < .001), motion smoothness (P < .001), and distance between the instruments (P = .019). Only instrument path distance demonstrated a correlation between LEAP and InsTrac tracking methods (novices: r = .663, P < .001; experts: r = .536, P < .001). Consistency of LEAP tracking was poor (average % time hands not tracked: 31.9%). CONCLUSION: The LEAP motion device is able to track the movement of hands using instruments in a laparoscopic box simulator. Construct validity is demonstrated by its ability to distinguish novice from expert performances. Only time and instrument path distance demonstrated concurrent validity with an existing tracking method however. A number of limitations to the tracking method used by LEAP have been identified. These need to be addressed before it can be considered an alternative to visual tracking for the delivery of objective performance metrics in take-home laparoscopic simulators.
AIM: To assess the potential of the LEAP™ infrared motion tracking device to map laparoscopic instrument movement in a simulated environment. Simulator training is optimized when augmented by objective performance feedback. We explore the potential LEAP has to provide this in a way compatible with affordable take-home simulators. METHOD: LEAP and the previously validated InsTrac visual tracking tool mapped expert and novice performances of a standardized simulated laparoscopic task. Ability to distinguish between the 2 groups (construct validity) and correlation between techniques (concurrent validity) were the primary outcome measures. RESULTS: Forty-three expert and 38 novice performances demonstrated significant differences in LEAP-derived metrics for instrument path distance (P < .001), speed (P = .002), acceleration (P < .001), motion smoothness (P < .001), and distance between the instruments (P = .019). Only instrument path distance demonstrated a correlation between LEAP and InsTrac tracking methods (novices: r = .663, P < .001; experts: r = .536, P < .001). Consistency of LEAP tracking was poor (average % time hands not tracked: 31.9%). CONCLUSION: The LEAP motion device is able to track the movement of hands using instruments in a laparoscopic box simulator. Construct validity is demonstrated by its ability to distinguish novice from expert performances. Only time and instrument path distance demonstrated concurrent validity with an existing tracking method however. A number of limitations to the tracking method used by LEAP have been identified. These need to be addressed before it can be considered an alternative to visual tracking for the delivery of objective performance metrics in take-home laparoscopic simulators.