MARS-RERC Machines Assisting Recovery from Stroke Rehabiliation Engineering Research Center on...

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Page 1: MARS-RERC Machines Assisting Recovery from Stroke Rehabiliation Engineering Research Center on Rehabilitation Robotics & Telemanipulation Funded by:Hosted.
Page 2: MARS-RERC Machines Assisting Recovery from Stroke Rehabiliation Engineering Research Center on Rehabilitation Robotics & Telemanipulation Funded by:Hosted.

MARS-RERCMARS-RERC Machines Assisting Recovery from Stroke

Rehabiliation Engineering Research Center onRehabilitation Robotics & Telemanipulation

Funded by:

Hosted at:

R1: Evaluating Error Augmentation For Neurorehabilitation

James Patton, Robert Kenyon, Derek Kamper, Sarah Housman, Ian Sharp, Mark Kovic, Ross Bogey, Borko Jovanovic

Page 3: MARS-RERC Machines Assisting Recovery from Stroke Rehabiliation Engineering Research Center on Rehabilitation Robotics & Telemanipulation Funded by:Hosted.

R1: Evaluating Error Augmentation For Neurorehabilitation

• Aim 1: Therapist-Driven Trajectories– Therapist specifies the trajectory in real-time– Allows therapist to customize approach,

focusing on what is critical for a particular patient’s recovery

• Aim 2: Patient-Driven Trajectories– Allow subject to provide own desired trajectory– Sensor mounted on healthy limb (bimanual

training)

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Models of learning• Hebbian,

reinforc-ment, supervised

• Post-movement adaptation

• Feedback error learning

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A. Unperturbed

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B. Training forces E. Final

Patton, J. L., M. E. Phillips-Stoykov, et al. (2006). "Evaluation of robotic training forces that either enhance or reduce error in chronic hemiparetic stroke survivors." Experimental Brain Research 168(3): 368-383.

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Patton, J. L., M. E. Phillips-Stoykov, et al. (2006). "Evaluation

of robotic training forces that either enhance or reduce error in

chronic hemiparetic stroke survivors." Experimental Brain

Research 168(3): 368-383.

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• EA works in stroke & healthy• We have the tools for big study• Light forces are all that’s needed• For EA, we need to know the

“desired” or “intended” location• What if the therapist or the

patient themselves provide the cue?

• Visual or force EA?• Coupling between hands

Background & Motivation

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• Integrate several systems:– Robot– Wrist Clamp– WREX– Hand opening device

• Software– H3D environment

• Assessment– Inclusion and exclusion criteria– Clinical tests– Exist questionnaire software

Development

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Experiment 1.1• Therapist-Driven Trajectories

– Therapist specifies the trajectory in real-time– Allows therapist to customize approach, focusing on what is critical for

a particular patient’s recovery

• 18 subjects, random order of 2 groups :1. EA therapy2. Non-EA therapy

• 4 weeks of treatment• Each treatment Lasts 2 weeks• Each visit is ~45 min• 4 groups

• EA with visual distortion• EA with haptic forces• EA with visual distortion and haptics• No EA

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AIM 2 ExperimentsAll Patient-Driven Trajectories

• Experiment 2.1: Same as Experiment 1, except – Patient-Driven

• Experiment 2.2: – 3 groups

• Reach simultaneously-bimanually• Reach sequentially• Control (Free reaching without cues from healthy limb)

• Experiment 2.3– 3 groups

• Reach in parallel• Reach in mirror• Control (Free reaching without cues from healthy limb)

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• Blinded Rater• Assessments pre and post each tx.

– “Reach and retrieve” (rag on a stick)– Functional workspace when reaching

towards 9 targets on periphery– Wolf Motor Function Test– Box and Blocks– Fugl-Meyer

Assessments

Figure 3: Schematic example of the directions and layers of the functional workspace determined in the workspace parts of the experiment.

x

y

Theoretical workspace boundary

Targets

Exten of

reaching to targets at

different levels

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EA haptic forces

Figure 11: The double exponential function governing the error-augmentation (dashed line defined in Equation 1.

Force F

Error

Fsat

sat

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Secondary assessments:

• How much time (tx vs. setup)?

• how long did it take to achieve therapeutically meaningful effect?

• Which treatment engaged / frustrated patient

• Therapist opinion

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Inclusion Criteria

• Chronic Stroke (8+ mos post) (Changed to 6+ mos in NW IRB)

• Available medical records/radiographic info • Ischemic infarct in MCA (not included in NW

IRB)• Primary Motor Cortex Involvement (not

included in NW IRB)• Some degree of shoulder and elbow mvmt.• AMFM 40-50 (Changed to 25-50 in NW IRB)

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Exclusion Criteria• Bilateral paresis• Severe sensory deficits• Severe spasticity (MAS = 4) • Severe contracture (added to NW IRB)• Aphasia, cognitive impairment or affective dysfunction that would

influence the ability to perform experiment• Severe concurrent medical problems• Diffuse/multiple lesion sites or multiple stroke events• Hemispatial neglect/inattention or field cut that would influence the

ability to perform experiment • Ataxia (added in NW IRB)• Significant pain (greater than 5/10) in UE (added in NW IRB)• Botox injection in previous 3 months (added in NW IRB)• Participation in other UE research projects (added in NW IRB)

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Statistics• Randomized Mixed effects model

– Trend affecting the hypothesis on treatment type?

– Period-by treatment interaction– Carry over effect– Patient-by-treatment interaction

• Bayesian?– Early results– Alternative to testing

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Electronic Electronic Visualization Visualization Lab at UICLab at UIC

Northwestern Northwestern UniversityUniversity

Rehabilitation Rehabilitation Institute of Institute of ChicagoChicago

Sensory Motor Sensory Motor Performance Performance Program (SMPP)Program (SMPP)

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