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Gait Adaptation and Biofeedback for Cerebral Palsy

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University of Washington

Status

Enrolling

Conditions

Cerebral Palsy

Treatments

Device: Audiovisual Biofeedback
Procedure: Multilevel Orthopedic Surgery
Device: Biomotum Spark: Robotic ankle resistance

Study type

Interventional

Funder types

Other
NIH

Identifiers

NCT05899153
STUDY00015348
R01NS091056 (U.S. NIH Grant/Contract)

Details and patient eligibility

About

This research aims to evaluate walking function in children with cerebral palsy (CP). The researchers want to understand how children with CP adapt and learn new ways of moving. They have previously found that measuring how a person controls their muscles is important for assessing walking ability and response to interventions. In these studies, they will adjust the treadmill belt speeds and/or provide real-time feedback to evaluate how a child can alter their movement. The feedback will include a wearable exoskeleton that provides resistance to the ankle and audio and visual cues based on sensors that record muscle activity. This research will investigate three goals: first, to measure how children with CP adapt their walking; second, to see if either repeated training or orthopedic surgery can improve adaptation rates; and third, to determine if individual differences in adaptation relate to improvements in walking function after treatment. This research will help develop better treatments to enhance walking capacity and performance for children with CP.

Full description

Prior research has shown that children with cerebral palsy (CP) use simplified motor control strategies compared to nondisabled (ND) peers, and that these differences in motor control are associated with walking function. While we can quantify motor control during activities like walking, the processes by which a child with CP adapts and learns new movement patterns are poorly understood.

This research will use two paradigms to evaluate adaptation and motor learning in children with CP: walking on a split-belt treadmill and responding to multimodal biofeedback. Walking on a split-belt treadmill, which has two belts set at different speeds to induce asymmetry during walking, has been commonly used to evaluate adaptation in other clinical populations. Responding to multimodal feedback can also be used to evaluate an individual's capacity to adapt their walking pattern. This research will use a real-time multimodal feedback system that targets plantarflexor activity, a key muscle group that is often impaired in CP. Sensorimotor feedback will be provided using a lightweight, body-worn robotic device that provides adaptive ankle resistance and step-by-step audiovisual feedback will be provided based on muscle activity from the plantarflexors using a visual display and audible tone. This research will quantify adaptation rate (e.g., change in soleus activity or step length symmetry) in response to these perturbations, and observe the impact of repeated practice or orthopedic surgery on walking function (e.g., change in walking speed). The specific aims are to:

Aim-1: Quantify adaptation rates in children with CP. We will quantify adaptation rate in response to three perturbation experiments: split-belt treadmill walking, sensorimotor feedback, and audiovisual feedback. The primary hypotheses are that children with CP will exhibit reduced adaptation rates compared to ND peers, and that adaptation rates will be associated with function (Gross Motor Function Measure, GMFM-66).

Aim-2: Determine whether adaptation rates change in response to repeated multimodal feedback training. We will evaluate children with CP who undergo six weeks of multimodal biofeedback training (20-min, 2x/week) or orthopedic surgery. The primary hypothesis is that multimodal feedback training will produce greater changes in adaptation rates than orthopedic surgery.

Aim-3: Determine whether changes in gait after treatment are associated with adaptation rates. Gait analysis will be performed to determine whether baseline adaptation rates are associated with changes in gait after treatment. The primary hypotheses are that baseline adaptation rates will be associated with changes in muscle, joint, and whole-body performance.

Enrollment

36 estimated patients

Sex

All

Ages

7 to 18 years old

Volunteers

Accepts Healthy Volunteers

Inclusion and exclusion criteria

Inclusion Criteria:

  • Diagnosis of bilateral cerebral palsy that impacts both legs
  • Gross Motor Functional Classification System Level II
  • No surgery or lower-extremity injuries 12 months prior to enrollment
  • No botulinum toxin injections in prior 3 months
  • No prior selective dorsal rhizotomy surgery
  • No history of seizures or cardiac conditions that would preclude walking on a treadmill for 20 minutes
  • No current pain that hinders walking

Trial design

Primary purpose

Basic Science

Allocation

Non-Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

36 participants in 2 patient groups

Orthopedic Surgery
Experimental group
Description:
Participants who have been scheduled for lower-extremity, multilevel orthopedic surgery will be assessed before and 9-18 months after surgery to evaluate changes in gait and adaptation rates.
Treatment:
Procedure: Multilevel Orthopedic Surgery
Audiovisual + Sensorimotor Biofeedback
Experimental group
Description:
Participants will complete 12 sessions (20 minutes of walking on a treadmill) over a 6-8 week period while receiving both audiovisual and sensorimotor biofeedback. Sensorimotor biofeedback will be provided with an ankle exoskeleton that provides resistance to ankle plantarflexion during the stance phase of gait. The visual feedback will be provided on a screen with a bar showing real-time muscle activity and the audio feedback will be a sound played when they reach the target level of muscle activity from the plantarflexors.
Treatment:
Device: Biomotum Spark: Robotic ankle resistance
Device: Audiovisual Biofeedback

Trial contacts and locations

1

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Central trial contact

Katherine M Steele, PhD; Alyssa Spomer, PhD

Data sourced from clinicaltrials.gov

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