Identifying Successful Motor Task Completion via Motion-Based Performance Metrics

Objective assessment of skill is important in understanding the human performance of precision motor control tasks; however, outcome-based performance measures are most commonly used to provide feedback after the task is completed. In this paper, we propose the use of motion-based performance metrics in order to determine successful task completion strategies for a complex and unconstrained dynamic task. We developed a novel motor control task in a virtual environment and identified two motion-based metrics (mean absolute jerk and average frequency) that correlate with the successful performance of the task measured as a function of completion time and acquired targets. Our methodologies provide insight into the movement strategies used during successful trials of the motor control task, and could be used to provide specific feedback and coaching aimed at altering the task completion strategy and boosting the participants' performance.

[1]  Ali Israr,et al.  Expertise-Based Performance Measures in a Virtual Training Environment , 2009, PRESENCE: Teleoperators and Virtual Environments.

[2]  T. Judkins,et al.  Objective evaluation of expert and novice performance during robotic surgical training tasks , 2009, Surgical Endoscopy.

[3]  Thomas S. Lendvay,et al.  Initial validation of a virtual-reality robotic simulator , 2008, Journal of robotic surgery.

[4]  R. Brent Gillespie,et al.  Haptic feedback and human performance in a dynamic task , 2002, Proceedings 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. HAPTICS 2002.

[5]  Blake Hannaford,et al.  Virtual Training for a Manual Assembly Task , 2001 .

[6]  Michael D. Byrne,et al.  Motor Skill Acquisition in a Virtual Gaming Environment , 2011 .

[7]  D. Bavelier,et al.  Exercising your brain: a review of human brain plasticity and training-induced learning. , 2008, Psychology and aging.

[8]  Dagmar Sternad,et al.  Energy margins in dynamic object manipulation. , 2012, Journal of neurophysiology.

[9]  D. Gentile,et al.  The impact of video games on training surgeons in the 21st century. , 2007, Archives of surgery.

[10]  S. Schaal,et al.  Bouncing a ball: tuning into dynamic stability. , 2001, Journal of experimental psychology. Human perception and performance.

[11]  Stefan Schaal,et al.  http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained , 2007 .

[12]  G. Maddern,et al.  Surgical Simulation: A Systematic Review , 2006, Annals of surgery.

[13]  A. Moinzadeh,et al.  Face, content, and construct validity of dV-trainer, a novel virtual reality simulator for robotic surgery. , 2009, Urology.

[14]  Gregory D. Hager,et al.  Towards integrating task information in skills assessment for dexterous tasks in surgery and simulation , 2011, 2011 IEEE International Conference on Robotics and Automation.

[15]  S. Schaal,et al.  One-Handed Juggling: A Dynamical Approach to a Rhythmic Movement Task. , 1996, Journal of motor behavior.

[16]  Y. Fery,et al.  Enhancing the control of force in putting by video game training , 2001, Ergonomics.

[17]  Amod Jog,et al.  Assessing system operation skills in robotic surgery trainees , 2012, The international journal of medical robotics + computer assisted surgery : MRCAS.

[18]  D Sternad,et al.  Dynamics of a bouncing ball in human performance. , 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.