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Design and preliminary evaluation of the FINGER rehabilitation robot: controlling challenge and quantifying finger individuation during musical computer game play.

Taheri H, Rowe JB, Gardner D, Chan V, Gray K, Bower C, Reinkensmeyer DJ, Wolbrecht ET - J Neuroeng Rehabil (2014)

Bottom Line: The resulting robotic device was built to accommodate multiple finger sizes and finger-to-finger widths.We also used FINGER to measure subjects' effort and finger individuation while playing the game.Test results demonstrate the ability of FINGER to motivate subjects with an engaging game environment that challenges individuated control of the fingers, automatically control assistance levels, and quantify finger individuation after stroke.

View Article: PubMed Central - HTML - PubMed

Affiliation: Mechanical Engineering Department, University of Idaho, Moscow, ID, USA. htaheri@uidaho.edu.

ABSTRACT

Background: This paper describes the design and preliminary testing of FINGER (Finger Individuating Grasp Exercise Robot), a device for assisting in finger rehabilitation after neurologic injury. We developed FINGER to assist stroke patients in moving their fingers individually in a naturalistic curling motion while playing a game similar to Guitar Hero. The goal was to make FINGER capable of assisting with motions where precise timing is important.

Methods: FINGER consists of a pair of stacked single degree-of-freedom 8-bar mechanisms, one for the index and one for the middle finger. Each 8-bar mechanism was designed to control the angle and position of the proximal phalanx and the position of the middle phalanx. Target positions for the mechanism optimization were determined from trajectory data collected from 7 healthy subjects using color-based motion capture. The resulting robotic device was built to accommodate multiple finger sizes and finger-to-finger widths. For initial evaluation, we asked individuals with a stroke (n = 16) and without impairment (n = 4) to play a game similar to Guitar Hero while connected to FINGER.

Results: Precision design, low friction bearings, and separate high speed linear actuators allowed FINGER to individually actuate the fingers with a high bandwidth of control (-3 dB at approximately 8 Hz). During the tests, we were able to modulate the subject's success rate at the game by automatically adjusting the controller gains of FINGER. We also used FINGER to measure subjects' effort and finger individuation while playing the game.

Conclusions: Test results demonstrate the ability of FINGER to motivate subjects with an engaging game environment that challenges individuated control of the fingers, automatically control assistance levels, and quantify finger individuation after stroke.

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Related in: MedlinePlus

Block diagram of the control system.
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Figure 11: Block diagram of the control system.

Mentions: Minimizing friction was a top priority during the design and manufacturing of FINGER. This goal guided the mechanism design, manufacturing process, and the selection of bearings and actuators. Figure 10 shows the static friction force for one of the 8-bar mechanisms as a function of actuator stroke. These static friction forces were determined experimentally as the force required by the actuator to move the mechanism from a rest position. Because the position dependency in the static friction is minimal, the average static friction force (0.0137 ± 0.0015 N SD) was used to construct a feedforward friction compensator. Assuming a simple Coulomb friction model, the compensator adds this average friction force along the direction of the estimated velocity. To prevent chattering, the compensator only applied the static force after a minimum velocity magnitude is achieved (see the dotted box in Figure 11).


Design and preliminary evaluation of the FINGER rehabilitation robot: controlling challenge and quantifying finger individuation during musical computer game play.

Taheri H, Rowe JB, Gardner D, Chan V, Gray K, Bower C, Reinkensmeyer DJ, Wolbrecht ET - J Neuroeng Rehabil (2014)

Block diagram of the control system.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3928667&req=5

Figure 11: Block diagram of the control system.
Mentions: Minimizing friction was a top priority during the design and manufacturing of FINGER. This goal guided the mechanism design, manufacturing process, and the selection of bearings and actuators. Figure 10 shows the static friction force for one of the 8-bar mechanisms as a function of actuator stroke. These static friction forces were determined experimentally as the force required by the actuator to move the mechanism from a rest position. Because the position dependency in the static friction is minimal, the average static friction force (0.0137 ± 0.0015 N SD) was used to construct a feedforward friction compensator. Assuming a simple Coulomb friction model, the compensator adds this average friction force along the direction of the estimated velocity. To prevent chattering, the compensator only applied the static force after a minimum velocity magnitude is achieved (see the dotted box in Figure 11).

Bottom Line: The resulting robotic device was built to accommodate multiple finger sizes and finger-to-finger widths.We also used FINGER to measure subjects' effort and finger individuation while playing the game.Test results demonstrate the ability of FINGER to motivate subjects with an engaging game environment that challenges individuated control of the fingers, automatically control assistance levels, and quantify finger individuation after stroke.

View Article: PubMed Central - HTML - PubMed

Affiliation: Mechanical Engineering Department, University of Idaho, Moscow, ID, USA. htaheri@uidaho.edu.

ABSTRACT

Background: This paper describes the design and preliminary testing of FINGER (Finger Individuating Grasp Exercise Robot), a device for assisting in finger rehabilitation after neurologic injury. We developed FINGER to assist stroke patients in moving their fingers individually in a naturalistic curling motion while playing a game similar to Guitar Hero. The goal was to make FINGER capable of assisting with motions where precise timing is important.

Methods: FINGER consists of a pair of stacked single degree-of-freedom 8-bar mechanisms, one for the index and one for the middle finger. Each 8-bar mechanism was designed to control the angle and position of the proximal phalanx and the position of the middle phalanx. Target positions for the mechanism optimization were determined from trajectory data collected from 7 healthy subjects using color-based motion capture. The resulting robotic device was built to accommodate multiple finger sizes and finger-to-finger widths. For initial evaluation, we asked individuals with a stroke (n = 16) and without impairment (n = 4) to play a game similar to Guitar Hero while connected to FINGER.

Results: Precision design, low friction bearings, and separate high speed linear actuators allowed FINGER to individually actuate the fingers with a high bandwidth of control (-3 dB at approximately 8 Hz). During the tests, we were able to modulate the subject's success rate at the game by automatically adjusting the controller gains of FINGER. We also used FINGER to measure subjects' effort and finger individuation while playing the game.

Conclusions: Test results demonstrate the ability of FINGER to motivate subjects with an engaging game environment that challenges individuated control of the fingers, automatically control assistance levels, and quantify finger individuation after stroke.

Show MeSH
Related in: MedlinePlus