Graduate, Undergraduate Category: Engineering, Health ...
Graduate, Undergraduate Category: Engineering, Health, Rehabilitation Degree Level: PhD,MSc Abstract ID# 430
Assessment of Ankle’s Motor Control Using Virtually Interfaced Rehabilitation Robotic System Mohsen
1 Nabian ,
,2 Farjadian ,
3 Hartman ,
Amir B. Amber John Constantinos Mavroidis1, 2, Maureen K. Holden2, 3
3 Corsino ,
Department of Mechanical and Industrial Engineering1, Bioengineering2, Department of Physical Therapy3, Northeastern University
3
1 2
• • • • • • • •
Millions of individuals are affected by neurological diseases and injuries that impact physical function Dysfunction of muscles around the ankle is a common residual impairment that affects balance and gait There is no robotic device on the market that reduces rehabilitation costs vi-RABT is a robotic device for retraining motor control at the ankle (Fig. 1) vi-RABT has 2 degree of freedom (DOF) actuation with angle and torque measurement mechanisms The robotic device is interfaced with a series of virtual reality (VR) games for retraining ankle function (Fig. 2) VR games performed with either force- or motioncontrol (Fig. 3) 5 healthy subjects recruited for pilot study to examine performance between 2 control mechanisms Early results indicate participants have better performance with motion-control than force-control in tasks with 2-DOF
• • • •
Subjects’ maximal force production was assessed for PF/DF (plantarflexion/dorsiflexion, IV/EV (inversion/eversion)(Table 1). Single-axis ROM was assessed for PF/DF, IV/EV (Table 1). Assessment findings were used to set parameters within the games; for example, the user may have to perform 80% of maximal dorsiflexion to reach a target. Subjects participated in 2 blocks of 30 trials each, for each of 3 VR games, under two conditions: Force-control and Positioncontrol: The first 2 games were the ‘Board’ game (Fig. 3 – left) played in single-DOF mode, then in 2-DOF mode. The 3rd game, ‘Maze” game (Fig. 3- Right), was played with 2-DOF only. For the Maze game, errors (wall collisions) were also counted.
150
Time (Sec)
•
• Early results from the first five subjects are reported here. We compared time to acquire 30 targets using force vs. motion control in different game settings. • Subjects demonstrated a significantly better performance for motion control vs. strength control when performing in the two axis mode (Fig. 4 – Right). Error scores had a similar pattern. • Subjects did not show a significant difference for motion control vs. strength control when performing in the single axis mode (Fig. 4 – Left )
Strength Motion
4
100
50
0
B-DFPF B-INEV
B
M
[1] V. L. Roger, et. al., “Executive summary: heart disease and stroke statistics--2012 update: a report from the American Heart Association,” Circulation, vol. 125, no. 1, pp. 188–197, Jan. 2012. [2] B. R. Waterman, B. D. Owens, S. Davey, M. A. Zacchilli, and P. J. Belmont Jr, “The epidemiology of ankle sprains in the United States,” J Bone Joint Surg Am, vol. 92, no. 13, pp. 2279–2284, Oct. 2010. [3] Y. Ding, M. Sivak, B. Weinberg, C. Mavroidis, and M. K. Holden, “NUVABAT: Northeastern university virtual ankle and balance trainer,” in Proc. of the 2010 IEEE Haptics Symposium, pp. 509–514, 2010.
Assessment of Ankle’s Motor Control Using Virtually Interfaced Rehabilitation Robotic System Mohsen
1 Nabian ,
,2 Farjadian ,
3 Hartman ,
Amir B. Amber John Constantinos Mavroidis1, 2, Maureen K. Holden2, 3
3 Corsino ,
Department of Mechanical and Industrial Engineering1, Bioengineering2, Department of Physical Therapy3, Northeastern University
3
1 2
• • • • • • • •
Millions of individuals are affected by neurological diseases and injuries that impact physical function Dysfunction of muscles around the ankle is a common residual impairment that affects balance and gait There is no robotic device on the market that reduces rehabilitation costs vi-RABT is a robotic device for retraining motor control at the ankle (Fig. 1) vi-RABT has 2 degree of freedom (DOF) actuation with angle and torque measurement mechanisms The robotic device is interfaced with a series of virtual reality (VR) games for retraining ankle function (Fig. 2) VR games performed with either force- or motioncontrol (Fig. 3) 5 healthy subjects recruited for pilot study to examine performance between 2 control mechanisms Early results indicate participants have better performance with motion-control than force-control in tasks with 2-DOF
• • • •
Subjects’ maximal force production was assessed for PF/DF (plantarflexion/dorsiflexion, IV/EV (inversion/eversion)(Table 1). Single-axis ROM was assessed for PF/DF, IV/EV (Table 1). Assessment findings were used to set parameters within the games; for example, the user may have to perform 80% of maximal dorsiflexion to reach a target. Subjects participated in 2 blocks of 30 trials each, for each of 3 VR games, under two conditions: Force-control and Positioncontrol: The first 2 games were the ‘Board’ game (Fig. 3 – left) played in single-DOF mode, then in 2-DOF mode. The 3rd game, ‘Maze” game (Fig. 3- Right), was played with 2-DOF only. For the Maze game, errors (wall collisions) were also counted.
150
Time (Sec)
•
• Early results from the first five subjects are reported here. We compared time to acquire 30 targets using force vs. motion control in different game settings. • Subjects demonstrated a significantly better performance for motion control vs. strength control when performing in the two axis mode (Fig. 4 – Right). Error scores had a similar pattern. • Subjects did not show a significant difference for motion control vs. strength control when performing in the single axis mode (Fig. 4 – Left )
Strength Motion
4
100
50
0
B-DFPF B-INEV
B
M
[1] V. L. Roger, et. al., “Executive summary: heart disease and stroke statistics--2012 update: a report from the American Heart Association,” Circulation, vol. 125, no. 1, pp. 188–197, Jan. 2012. [2] B. R. Waterman, B. D. Owens, S. Davey, M. A. Zacchilli, and P. J. Belmont Jr, “The epidemiology of ankle sprains in the United States,” J Bone Joint Surg Am, vol. 92, no. 13, pp. 2279–2284, Oct. 2010. [3] Y. Ding, M. Sivak, B. Weinberg, C. Mavroidis, and M. K. Holden, “NUVABAT: Northeastern university virtual ankle and balance trainer,” in Proc. of the 2010 IEEE Haptics Symposium, pp. 509–514, 2010.
