Reaching in Stroke 3rd Phase

Purpose:

For stroke survivors, the use of compensatory movements can lead to a reduction of range of motion, pain, and a pattern of "learned non-use". A common compensatory movement present during upper limb reaching is trunk displacement. Although this motion has been identified as an important one to be reduced, few strategies for addressing this problem have been considered. The existing strategies require physical restraint of the person to the back of a chair, making them undesirable for use in unsupervised therapy. As a result, there is a current need for alternate methods that promote the use of correct movement patterns both in the clinic and in the home. In this sense, technology can act as an enabler to create new ways of reducing trunk compensation. Still, there is a gap in the literature as trunk compensation has only been investigated as a secondary theme in robotic and computer-aided rehabilitation.

Consequently, in this project the investigators will look into the reduction of trunk compensation using robotic devices and commercially available technology, to enable a focus on the quality of the movements in unsupervised therapy. The potential results from this project could later be applied and generalized to other modes of compensation in stroke and other neurological disabled populations.

Objective:

The objective is to demonstrate that feedback cues and rewards (game scores) could be used to reduce trunk compensatory movements in unsupervised therapy.

Research Questions:

Will the use of visual+force feedback and the use of visual+force+game scores feedback reduce trunk compensation?

Will one of these feedback modalities (visual+force vs. visual+force+game scores) be more effective in reducing trunk compensation?

Equipment:

• 1 Kinect (Microsoft, Inc.) markerless motion capture system.
• 2 Kinova Jaco assistive robotic arms. These devices are used to assist disabled people on daily tasks. The arms are designed for safe interaction (low forces) with the user.
• 1 Desktop computer and a monitor to deliver the visual feedback.

Method:

The investigators will implement the force feedback cues using two Kinova Jaco robotic devices to deliver them. The force feedback cues will be provided as resistance to move the robots' handles. These cues will be applied when the user moves outside a certain error band, based on a "normal" reaching pattern. In addition, the magnitude of the cue will be proportional to the magnitude of trunk compensation. The visual cues will be implemented using a monitor to display two cursors (empty circles) that will represent the participant's hands, and the circles will fill with red ink as the user starts to compensate. As the magnitude of compensation increases, the amount of red ink will gradually increase to indicate the level at which the user is compensating. For the game scores, the participant will be rewarded with more points when less compensation is exhibited, or with less points when an increased level of compensation is measured. .

In the study, the investigators will compare the combination of visual+force feedback vs. visual+force+game scores feedback.

The goal of this approach is to investigate whether using compensatory motions to affect the outcome of the game scores would lead to a further reduction of these movements when compared to only receiving feedback about the movement pattern without attaching a reward to it. This approach will follow an operant conditioning strategy to attempt to change the subject's behaviour when performing unrestrained bimanual exercises.

Summary of Procedures:

(Total Time: 2-2.5 hours):

1. Participants will be recruited.
2. Introduce the study and equipment. Participants will be asked to inform the investigator if they feel uncomfortable or fatigued at any point during the experiment, and will be given as many breaks as needed.
3. Ask participants to fill out consent forms, or if their unable to provide consent due to their health condition, their caregivers/guardians will provide consent and the subject will provide assent.
4. Participant will fill out a background questionnaire and a registered physical therapist will conduct a clinical assessment based on recognized impairment scales (Fugl-Meyer Upper Extremity Assessment and Reaching Performance Scale) to use the scores as a baseline for the comparisons that will be performed in the statistical analyses at the end of this phase. The Reaching performance Scale requires the use of video recording of the assessment for scoring. If the participant wants to know their clinical assessment results, at the end of the session, the therapist will provide a photocopy of the results, and will give the participant and explanation of these results and answer any questions that the participant may have about these scales. In the case of the Reaching Performance Scale as the scoring is done after the study, the participant could receive their scores at a later date via a telephone call.
5. All the study sessions will be conducted at the University of British Columbia (UBC) Point Grey Campus. During the test, the participants will be asked to interact with a computer through the use of the following input technologies: 2 Jaco Kinova robotic arms and a Microsoft Kinect. Using these technologies, the participants will perform bimanual symmetric movements with their arms/ hands to control a simple cursor/target videogame. The Kinect will measure the participant's movement as data points for every joint, no video will be recorded. The robotic devices will be used to record the hands' movements and will increase their resistance to be moved based on the level of trunk compensation of the participant. The monitor will be used to provide visual feedback about the participant's trunk compensation and to display the target game and game scores.
6. Ask participants to sit in a chair and adjust footrest to have their feet fully supported, their knees at a 90 degree angle, and their back against the chair.
7. Ask participants to hold on to the handles of the two robotic devices.
8. In case participants are not able to hold the handle due to hand weakness, an adjustable fabric and elastic strap will be fitted around their palm to hold the hand on top of the handle.
9. The maximum force that the user can produce to push the robots will be measured by reading the robot's sensors.
10. Ask the participant to perform a series of unimanual reaches to calibrate the system based on the participant's arm's length.
11. Ask participant to perform 5 practice bimanual reaches to become familiar with the system and the motion mapping.
12. Ask participant to perform 15 baseline (no feedback) bimanual reaches to measure their trunk compensation. The investigators will use the value of average trunk compensation to set the error bands for the visual and force feedback.
13. Ask participant to perform 5 practice bimanual reaches to become familiar with either the visual+force feedback, or the visual+force+game scores (depending on the randomization of subjects).
14. Ask the participant to perform 60 trials of bimanual reaches to 1 target at knee height with arms fully extended. Participants will receive visual feedback about their compensation and their accumulated game scores through the computer's monitor, and as increased resistance to move of the robots.
15. The participant will be able to rest between targets if requested. In addition there will be 1 minute rests after every 15 targets.
16. The participant will perform 15 reaches without any feedback (Post measurement)
17. The participants will have 5 minutes of break before starting the second feedback condition.
18. Repeat steps 14, 15 and 16, but with the other type of feedback (visual+force, or visual+force+game scores).
19. A note taker will record the occurrence of obstacles encountered by the participants during the study.
20. The motion tracking data and assessment videos will be saved on a computer file, backed up on a UBC-based file server and on optical media.
21. At the end of the session the participant will answer a usability questionnaire.
22. The data from the note taker, motion logs, assessment videos and questionnaires will be used to conduct a quantitative and qualitative analysis to gain further insight into how augmented feedback can reduce compensatory trunk movements, and the ease of use and functionality of the system. All the data will be identified using participants' numbers.
23. The video recordings will be erased/destroyed 5 years after publication of results.

Study Design:

The investigators will follow a within-subjects crossover design with the independent variable being the feedback type and the levels will be: visual+force feedback and visual+force+game scores. The primary dependent variable will be the measure of trunk compensation.

The investigators will follow a counterbalanced strategy to reduce the carryover effects from performing the two conditions in a certain order. Data collection will include motion log files, scores from the game, discussions with participants and exit surveys.