Development of a Physics-Based Target Shooting Game to Train Amputee Users of Multijoint Upper Limb Prostheses

Abstract

For upper limb amputees, learning the control of myoelectric prostheses is difficult and challenging. Introduction of newer prostheses with multiple degrees of freedom controlled by various neural commands will make such training even more difficult. To produce smooth and human-like movements, the user must learn to produce multiple neural commands with precise amplitude and timing. To aid in training of the amputee users, we have developed a realistic and motivating virtual environment (VE) consisting of a physics-based target shooting game. The users' neural commands such as EMG, cortical neural activity, or voluntary movements of the residual limbs can be used to control the movement of a simulated prosthesis to point and shoot at virtual targets. In addition to the visual, sound, and performance feedback of the resulting movement, the game provides reaction forces in contact points that can be used to drive haptic displays. The timing measurements show that the physics-based simulation and rendering can be executed in real time in readily available PC systems. The target shooting game was developed in musculoskeletal modeling software (MSMS) that has been developed in our laboratory and is freely available for development of similar virtual training applications.

Learning an EMG Controlled Game: Task-Specific Adaptations and Transfer

“…So far, myogame research has not shown much empirical evidence for their benefit (see e.g. [ 1 , 3 , 4 , 6 – 10 ], but see [ 12 ]). The current designs therefore do not yet warrant testing for motor learning effects on patient groups.…”

“…using a myogame). Many studies so far limit their research to the development of the myogame, and do not include an evaluation of training effects after using the game [ 3 , 4 ]. Studies that did include the training of the myogame often did not provide statistical support for apparent improvement in performance and, with the exception of one study [ 5 ], none have used a control group [ 6 – 11 ].…”

“…Finally, the consensus in motor learning literature is that training is task-specific–that is, in order to transfer a skill between tasks, the goal of these tasks should be as similar as possible [ 13 – 16 ]. So far however, myogames deliberately deviate from real ADL tasks in order to remain entertaining and motivating [ 1 , 3 – 10 ].…”

Comparing the Exteroceptive Feedback of Normal Stress, Skin Stretch, and Vibrotactile Stimulation for Restitution of Static Events

“…They either apply too much pressure and break the shell or apply too little pressure and have it slip from their grasp. Healthy humans, by contrast, do not need to pay constant visual attention (Davoodi and Loeb, 2012) during such tasks because the tactile sensors (mechanoreceptors) in their skin allow them to easily regulate the grasping force level (Ferrington et al, 1977;Dargahi and Najarian, 2004). The central nervous system (CNS) transmits proprioceptive and exteroceptive information whenever one comes into contact with an external stimulus; over time, these experiences are used to inform one's reaction to present events (Hager-Ross et al, 1996;Augurelle et al, 2003).…”

Real-Time Control of an Interactive Impulsive Virtual Prosthesis

“…The system designed by Hargrove et al is meant to simulate an interactive task but does not actually include contact dynamics [6]. Applications of the Davoodi and Loeb environment which incorporate some form of contact dynamics have been described but user control of these has not been demonstrated [19], [20]. The interactive trans-humeral virtual prosthesis developed by Lambrecht et al [11] had four control-classes (Elbow flexion/extension, forearm supination, and hand open) under synchronous EMG control and was controllable by able-bodied subjects.…”