BACKGROUND: The loss of haptic information that results from the reduced-access conditions present in minimally invasive surgery (MIS) may compromise the safety of the procedures. This limitation must be overcome through training. However, current methods for determining the skill level of trainees do not measure critical elements of skill attainment. This study aimed to evaluate the usefulness of force information for the assessment of skill during MIS. METHODS: To achieve the study goal, experiments were performed using a set of sensorized instruments capable of measuring instrument position and tissue interaction forces. Several force-based metrics were developed as well as metrics that combine force and position information. RESULTS: The results show that experience level has a strong correlation with the new force-based metrics presented in this article. In particular, the integral and the derivative of the forces or the metrics that combine force and position provide the strongest correlations. CONCLUSIONS: This study showed that force-based metrics are better indications of performance than metrics based on task completion time or position information alone. The proposed metrics can be automatically computed, are completely objective, and measure important aspects of performance.
BACKGROUND: The loss of haptic information that results from the reduced-access conditions present in minimally invasive surgery (MIS) may compromise the safety of the procedures. This limitation must be overcome through training. However, current methods for determining the skill level of trainees do not measure critical elements of skill attainment. This study aimed to evaluate the usefulness of force information for the assessment of skill during MIS. METHODS: To achieve the study goal, experiments were performed using a set of sensorized instruments capable of measuring instrument position and tissue interaction forces. Several force-based metrics were developed as well as metrics that combine force and position information. RESULTS: The results show that experience level has a strong correlation with the new force-based metrics presented in this article. In particular, the integral and the derivative of the forces or the metrics that combine force and position provide the strongest correlations. CONCLUSIONS: This study showed that force-based metrics are better indications of performance than metrics based on task completion time or position information alone. The proposed metrics can be automatically computed, are completely objective, and measure important aspects of performance.
Authors: Dimitrios Stefanidis; William W Hope; James R Korndorffer; Sarah Markley; Daniel J Scott Journal: J Am Coll Surg Date: 2010-04 Impact factor: 6.113
Authors: Barbara Goff; Lynn Mandel; Gretchen Lentz; Amy Vanblaricom; Anne-Marie Amies Oelschlager; David Lee; Andrew Galakatos; Matthew Davies; Peter Nielsen Journal: Am J Obstet Gynecol Date: 2005-04 Impact factor: 8.661
Authors: Brandon Rohrer; Susan Fasoli; Hermano Igo Krebs; Richard Hughes; Bruce Volpe; Walter R Frontera; Joel Stein; Neville Hogan Journal: J Neurosci Date: 2002-09-15 Impact factor: 6.167
Authors: Behnaz Poursartip; Marie-Eve LeBel; Laura C McCracken; Abelardo Escoto; Rajni V Patel; Michael D Naish; Ana Luisa Trejos Journal: Sensors (Basel) Date: 2017-08-05 Impact factor: 3.576