Human-like Robotic Controllers for Enhanced Motor Learning
- Conditions
- StrokeSpinal Cord Injuries
- Interventions
- Behavioral: Behavioral Interaction ConditionsDevice: Haptic Impedance LevelBehavioral: Skill Level of PartnerDevice: Robot Controller Showcase
- Registration Number
- NCT04578665
- Lead Sponsor
- Shirley Ryan AbilityLab
- Brief Summary
The purpose of this study is to develop a new paradigm to understand how humans physically interact with each other at a single and at multiple joints, with multiple contact points, so as to synthesize robot controllers that can exhibit human-like behavior when interacting with humans (e.g., exoskeleton) or other co-robots. The investigators will develop models for a single joint robot (i.e. at the ankle joint) that can vary its haptic behavioral interactions at variable impedances, and replicate in a multi-joint robot (i.e. at the ankle, knee, and hip joints). The investigators will collect data from healthy participants and clinical populations to create a controller based on our models to implement in the robots. Then, the investigators will test our models via the robots to investigate the mechanisms underlying enhanced motor learning during different human-human haptic interaction behaviors (i.e. collaboration, competition, and cooperation. This study will be carried out in healthy participants, participants post-stroke, and participants with spinal cord injury (SCI).
- Detailed Description
The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected by 1) different behavioral interaction conditions (i.e., solo task, collaboration task, competition task, or cooperation task); 2) the haptic impedance or stiffness of the virtual connection between dyadic peers (i.e., hard connection, medium connection, or soft connection); and 3) the skill level of the other partner (i.e., novice or expert). The investigators will be using both an ankle robot (M1 device) and a bilateral lower limb exoskeleton (H3/X2 device), and will collect EMG and EEG data.
For Experiment A , the investigators will recruit healthy volunteers (n = 180) to work in dyadic pairs. With the collected data, the investigators will model how humans adapt force and impedance and share roles/specialize during various dyadic interaction behaviors, and use this knowledge to develop robot controllers that mimic movement error and force adaptation for enhanced motor performance.
For Experiment B , the investigators will recruit healthy volunteers (n = 260), participants post-stroke (n = 88) and participants post-SCI (n = 88) to work in dyadic pairs within each population. The investigators will test the robot controllers following the models for mechanical adaptation and role sharing strategies between peers based on Experiment A. The investigators will also monitor single-joint and multi-joint movement error and force adaptation in regards to enhanced motor performance. The investigators will assess if the robot controllers can pass a "haptic Turing Test", rendering them indistinguishable with respect to human peers. A structural MRI will be obtained to be used for EEG source analysis.
For Experiment C, the investigators will showcase the robot controllers by interfacing with participants post-stroke (n = 4) and participants post-SCI (n = 4) with the single-joint and multi-joint assistive robots to observe motor learning and functional outcomes with 10 training sessions per robot.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 764
Not provided
Not provided
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Arm && Interventions
Group Intervention Description Healthy Participants Ankle Robot (M1) Behavioral Interaction Conditions The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Healthy Participants Bilateral Lower Limb Exoskeleton (H3/X2) Skill Level of Partner The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Healthy Participants Ankle Robot (M1) Haptic Impedance Level The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Healthy Participants Ankle Robot (M1) Skill Level of Partner The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Healthy Participants Bilateral Lower Limb Exoskeleton (H3/X2) Behavioral Interaction Conditions The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Clinical Populations Ankle Robot (M1) Haptic Impedance Level The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Clinical Populations Bilateral Lower Limb Exoskeleton (H3/X2) Skill Level of Partner The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Clinical Populations Bilateral Lower Limb Exoskeleton (H3/X2) Robot Controller Showcase The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Healthy Participants Bilateral Lower Limb Exoskeleton (H3/X2) Haptic Impedance Level The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Clinical Populations Ankle Robot (M1) Behavioral Interaction Conditions The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Clinical Populations Ankle Robot (M1) Skill Level of Partner The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Clinical Populations Bilateral Lower Limb Exoskeleton (H3/X2) Behavioral Interaction Conditions The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Clinical Populations Bilateral Lower Limb Exoskeleton (H3/X2) Haptic Impedance Level The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected. Clinical Populations Ankle Robot (M1) Robot Controller Showcase The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected.
- Primary Outcome Measures
Name Time Method Change in lower limb motor control. Motor control will be measured all 10 sessions through study completion, an average of 12 weeks. Lower limb motor control will be assessed through analysis of tracking movements to a target trajectory. If the tracking error decreases, this corresponds to motor control improvement.
Change in motor output from surface EMG of lower limb muscles Change of motor output at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. For Experiment A and B with M1: the surface EMG activation patterns of the gastrocnemius and tibialis anterior muscles will be collected. For Experiment A and B with H3/X2, the surface EMG of the gluteus maximus, biceps femoris, tensor fasciae latae, rectus femoris, vastus lateralis, gastrocnemius medialis, soleus, and tibialis anterior muscles will be collected.
- Secondary Outcome Measures
Name Time Method Change in functional gait assessment (FGA) Change in score at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Balance while walking will be assessed using the functional gait assessment (FGA). This has a scale of 0 to 30, with the higher score indicating better balance and decreased fall risk.
Change in strength via dynamometer testing. Change in strength at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Change in strength will be assessed via the maximum voluntary contraction for joints with a dynamometer.
Change in stance time. Change in stance time at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Stance time is the amount of time that passes during the stance phase of one extremity in a gait cycle. It includes single support and double support. Equal stance time between limbs is a better outcome.
Change in BERG balance scale (BBS) Change of score at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Static and dynamic sitting and standing balance will be assessed using the BERG balance scale. The scale ranges from 0 to 56, and a higher score indicates better balance and decreased fall risk.
Change in stride variability. Change in stride variability at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Stride variability is the ratio between the standard-deviation and mean of stride time, expressed as percentage. Decreased variability indicates a better outcome.
Change in cadence. Change in number of steps at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Cadence is the total number of steps taken within a given time period; often expressed per minute. Typically a higher number of steps is a better outcome.
Change in 6 minute walking test. Change of ambulation distance at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Physical function test measuring the total distance walked in a span of six minutes will be assessed. A shorter time indicates improvement.
Change in 10 meter walking test. Change of ambulation distance at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Physical function test measuring the walking speed in a span of 10 meters will be assessed. A shorter time indicates improvement in walking speed.
Change in Modified Ashworth Scale. Change in score at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Spasticity of lower extremity muscles will be assessed using the Modified Ashworth Scale. The minimum score of 0 means no increase in spasticity and the maximum score of 4 means the body part is rigid in flexion or extension. A lower score indicates a better outcome.
Change in step length. Change in distance at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Step length is the distance between the point of initial contact of one foot and the point of initial contact of the opposite foot. Typically a longer step length is a better outcome, ideally with equal measurements between left and right limbs.
Change in stride length. Change in distance at baseline, midpoint of intervention after 10 training sessions with assistive robot, and endpoint after 10 additional training sessions with the other assistive robot through participant completion, an average of 5 months. Stride length is the distance between successive points of initial contact of the same foot. Right and left stride lengths are normally equal. Typically a longer stride length is a better outcome, ideally with equal measurements between left and right limbs.
Trial Locations
- Locations (1)
Shirley Ryan AbilityLab
🇺🇸Chicago, Illinois, United States