Incorporating Haptic Effects Into Three-Dimensional Virtual Environments to Train the Hemiparetic Upper Extremity

Looks like it works, then write up a proposed protocol on this and distribute it to all the stroke hospitals. 

Incorporating Haptic Effects Into Three-Dimensional Virtual Environments to Train the Hemiparetic Upper Extremity

Qinyin Qiu
2009, Ieee Transactions on Neural Systems and Rehabilitation Engineering a Publication of the Ieee Engineering in Medicine and Biology Society

Robotics,
Biomedical Engineering,
Biomechanics,
Skill Acquisition,
Neurophysiology
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Sergei Adamovich
,
Gerard G. Fluet
,
Alma S. Merians
,
Abraham Mathai
, and
Qinyin Qiu

Abstract

Current neuroscience has identified several constructs to increase the effectiveness of upper extremity rehabilitation. One is the use of progressive, skill acquisition-oriented training. Another approach emphasizes the use of bilateral activities. Building on these principles, this paper describes the design and feasibility testing of a robotic / virtual environment system designed to train the arm of persons who have had strokes. The system provides a variety of assistance modes, scalable work spaces and hand-robot interfaces allowing persons with strokes to train multiple joints in three dimensions. The simulations utilize assistance algorithms that adjust task difficulty both online and offline in relation to subject performance. Several distinctive haptic effects have been incorporated into the simulations.An adaptive master-slave relationship between the unimpaired and impaired arm encourages active movement of the subject's hemiparetic arm during a bimanual task. Adaptive anti-gravity support and damping stabilize the arm during virtual reaching and placement tasks. An adaptive virtual spring provides assistance to complete the movement if the subject is unable to complete the task in time.Finally, haptically rendered virtual objects help to shape the movement trajectory during a virtual placement task. A proof of concept study demonstrated this system to be safe, feasible and worthy of further study.
Keywords
Cerebrovascular Accident; Neuroplasticity; Robotics; Upper Extremity; Virtual Reality
INTRODUCTION
A significant proportion of the persons surviving cerebrovascular accidents (CVA) suffer from residual sensory and motor impairments that affect their upper extremity function and can severely limit the functional independence of a person after a CVA [1], [2]. Newer studies show that robotically-facilitated repetitive movement training might be an effective stimulus for normalizing upper extremity motor control in persons with moderate to severe impairments who have difficulty performing unassisted movements [3], [4]. Hogan and colleagues designed a suite of robots starting with the MIT-MANUS a 2 DOF robot that trained the shoulder and elbow in a horizontal plane [4]. Subsequent additions to their suite include a 1 DOF robot that can train shoulder movements in vertical or diagonal planes [5],and a third that trains the wrist in three DOF [6]. Participants interact with the end effector of these robots at the hand and their arms are supported by external structures as needed.Trajectories of the participant may be shaped utilizing a haptic channel that limits negative trajectories and movement that deviates from a predetermined positive trajectory [7]. The PARIS system was designed to work in larger three dimensional work spaces and to either train or study the effects of adjusting actual task parameters and distortion of tasks or feedback and their effect on motor learning and control [8]. The NeReBot and the MariBot are two wirebased robot systems designed to provide passive range of motion treatments to the shoulderand arm of patients with minimal active movement [9].