Design of a complex virtual reality simulation to train finger motion for persons with hemiparesis: a proof of concept study

Abstract

Background: Current neuroscience has identified rehabilitation approaches with the potential to stimulate adaptive changes in the brains of persons with hemiparesis. These approaches include, intensive task-oriented training, bimanual activities and balancing proximal and distal upper extremity interventions to reduce competition between these segments for neural territory.

Methods: This paper describes the design and feasibility testing of a robotic/virtual environment system designed to train the hand and arm of persons with hemiparesis. The system employs a simulated piano that presents visual, auditory and tactile feedback comparable to an actual piano. Arm tracking allows patients to train both the arm and hand as a coordinated unit, emphasizing the integration of both transport and manipulation phases. The piano trainer includes songs and scales that can be performed with one or both hands. Adaptable haptic assistance is available for more involved subjects. An algorithm adjusts task difficulty in proportion to subject performance. A proof of concept study was performed on four subjects with upper extremity hemiparesis secondary to chronic stroke to establish: a) the safety and feasibility of this system and b) the concurrent validity of robotically measured kinematic and performance measures to behavioral measures of upper extremity function.

Results: None of the subjects experienced adverse events or responses during or after training. As a group, the subjects improved in both performance time and key press accuracy. Three of the four subjects demonstrated improvements in fractionation, the ability to move each finger individually. Two subjects improved their aggregate time on the Jebsen Test of Hand Function and three of the four subjects improved in Wolf Motor Function Test aggregate time.

Conclusion: The system designed in this paper has proven to be safe and feasible for the training of hand function for persons with hemiparesis. It features a flexible design that allows for the use and further study of adjustments in point of view, bilateral and unimanual treatment modes, adaptive training algorithms and haptically rendered collisions in the context of rehabilitation of the hemiparetic hand.

Figure 1

Virtual Piano trainer. A. CyberGrasp haptic device worn over a CyberGlove instrumented glove. B. Depiction of Virtual Key Press C. Piano Trainer Simulation; hands shown in a first person perspective.

Figure 2

Independent Finger Flexion. Left Panel: Depiction of independent finger flexion preceding a virtual piano trainer intervention. Fingers are flexed as the subjects moves his hand to the cued key (first 1.5 seconds), then all four fingers flex as the subject attempts to press a piano key with his index finger. Right Panel: After nine days of training then, fingers are flexed initially during transport (first. 0.5 seconds) then the subject extends all four fingers (0.5 to 1.1 seconds) finally the non-cued fingers maintain flexion and the cued index finger flexes independently.

Figure 3

Demonstration of Adaptive Algorithms A and B. Left Panel: The blue line depicts target fractionation. The red line indicates the fractionation angles achieved by the subject during the attempted key presses. The green line indicates the timing of successful key presses. While training using Algorithm A, target fractionation decreases steadily until actual fractionation exceeds target fractionation. Key presses are unsuccessful because the actual fractionation (red line) does not meet the target fractionation (blue line) The green line indicates the timing of successful key presses. Right Panel: When training using Algorithm B diminution of target fractionation was delayed for six seconds, forcing the subject to attain a higher fractionation score to affect a successful key press.

Figure 4

Improvements in Accuracy and Task Duration. Percent change in the time required to achieve successful key press (Duration, upper panel) and number of correct key presses (Accuracy, lower panel) are shown for each of the four subjects from the feasibility study following unilateral and bilateral piano training.

Figure 5

Daily Average Fractionation Scores During Training. Upper Panel: Fractionation Average daily fractionation for Subjects S1, S2 and S3 during 90 minute sessions using the Virtual Piano Trainer. Patterns of change vary. S1 increases average fractionation from 16 to 76 degrees. S2 improved from -15 to 63 degrees and S3 from 27 to 34 degrees. Lower Panel: Average daily fractionation for Subject S4, who used the CyberGrasp during training. His fractionations score improved over the first four days of training, with the CyberGrasp providing 10 Newtons of assistive force. On day five and six the assistive force was reduced to 6 Newtons. Fractionation diminishes initially but then improves. On training days seven and eight the force was further reduced to 4 Newtons of assistance. Fractionation diminishes again but then makes a small improvement.

Figure 6

Target and actual fractionation changes during training in subject S5. The solid line depicts target fractionation and the dashed line depicts actual fractionation changes over two weeks of training for each of the four fingers for subject S5. The vertical line separates training with Algorithm A on the left and Algorithm B on the right (see Fig. 3). Minimal changes in fractionation were accomplished by this subject.

Figure 7

Target and actual fractionation changes during training in subject S6. This subject did not make gains when using algorithm A (on the left of the vertical line) but demonstrated dramatic improvements in his ability to isolate individual finger motion in three of his four fingers when using algorithm B (on the right of the vertical line). Subject demonstrated an increase in peak fractionation of 48 degrees for index finger, 165 degrees for middle finger and 72 degrees for pinky).