Real-time Neuromuscular Control of Exoskeletons

NCT ID: NCT04661891

Last Updated: 2025-05-25

Basic Information

• Recruitment Status: ACTIVE_NOT_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 80 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2021-05-05
• Study Completion Date: 2025-12-31

Brief Summary

The purpose of this study is to develop a real-time controller for exoskeletons using neural information embedded in human musculature. This controller will consist of an online interface that anticipates human movement based on high-density electromyography (HD-EMG) recordings, and then translates it into functional assistance. This study will be carried out in both healthy participants and participants post-stroke.

The researchers will develop an online algorithm (decoder) in currently existing exoskeletons that can extract hundreds of motor unit (MU) spiking activity out of HD-EMG recordings. The MU spiking activity is a train of action potentials coded by its timing of occurrence that gives access to a representative part of the neural code of human movement. The researchers will also develop a command encoder that can anticipate human intent (multi-joint position and force commands) from MU spiking activity to translate the neural information to movement. The researchers will integrate the decoder with the command encoder to showcase the real-time control of multiple joint lower-limb exoskeletons.

Detailed Description

The researchers will record muscle activity in healthy participants and participants post-stroke from up to eight lower limb muscles (soleus, gastrocnemius, tibialis anterior, rectus femoris, vastus lateralis, and hamstring) during functional tasks (e.g., single-joint movement, gait, squatting, cycling). These measurements will provide the physiological dataset of lower limb movement and locomotion for the neural decoder. Then, the researchers will apply online deep learning methods for MU spiking activity decomposition from over eight muscles, and develop a real-time neural decoder. This will provide real-time decomposition of hundreds of MUs concurrently active during natural lower limb human behavior. The researchers will validate this approach by comparing our results with a gold standard, the blind source separation method. Blind source separation algorithms can separate or decompose the HD-EMG signals, a convolutive mix of MU action potentials, into the times at which individual MUs discharge their action potentials. With the decomposed MU spiking data, the researchers will develop methods to translate MU spiking activity in position, force, and hybrid commands for exoskeletons that will become a command encoder implemented into currently existing research exoskeletons that can anticipate human intent (multi-joint position and force commands) to estimate the level of assistance required by the task, (e.g., add knee torque during the stance phase).

The researchers will combine the MU spiking activity decoder with the subspace projection methods into a neural real-time interface between individuals and a currently existing research lower extremity exoskeleton for locomotion augmentation. This will become an integrated high-resolution human-machine interface that can be used for real-time control of exoskeletons so that commands will be delivered at a rate higher than the muscles' electromechanical delay, i.e., the elapsed time between neural command and muscle force generation of movement.

For Experiment A, the investigators will recruit healthy volunteers (n = 20) and participants post-stroke (n = 20) and complete single-joint movement and locomotor tasks to collect muscle activity data via HD-EMG.

For Experiment B, the investigators will showcase the generalization of our approach recruiting and interfacing healthy volunteers (n = 20) and participants post-stroke (n = 20) with the assistive exoskeleton. Subjects will perform single-joint and locomotor tasks to calibrate the decoder, and then repeat single-joint and locomotor tasks with the decoder providing real-time assistance. Participants post-stroke will repeat up to 10 sessions to evaluate the stability of the ability of the decoder to extract motor units.

Conditions

Stroke

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: BASIC_SCIENCE
• Blinding Strategy: NONE

Study Groups

Healthy Participants

The investigators will look at muscle activity of healthy participants from eight lower limb muscles during functional tasks (e.g. single-joint movement, walking, squatting, cycling).

Group Type: EXPERIMENTAL

Isometric contractions

Intervention Type: OTHER

HD-EMG grids will be applied to the lower limb muscles of interest. Isometric contractions will consist of applying joint torque to reach a pre-defined torque level based on the subject's maximal voluntary contraction (i.e., 25%, 60%, 70%, 80%, 90%). The participant will control torque intensity by responding to a biofeedback displayed on a screen. The joint will be secured with non-compliant bands to prevent any movement of the participant. The order of the joints tested (i.e., dominant ankle, knee, or hip joint) will be randomized.

Isokinetic contractions

Intervention Type: OTHER

HD-EMG grids will be applied to the lower limb muscles of interest. Isometric contractions will consist of moving a joint to completing a set of contractions (10-20 contractions) at various velocities (i.e., 10 degrees per second, 30 degrees per second, 60 degrees per second). The joint will be secured with non-compliant bands to prevent any movement of the participant. The order of the joints tested (i.e., dominant ankle, knee, or hip joint) will be randomized.

Dynamic contractions

Intervention Type: DEVICE

HD-EMG grids will be applied to the lower limb muscles of interest. Multi-joint tasks (i.e. walking, squatting, cycling) will be performed at a given frequency. A motion capture system will be used to record the joint angles and ground reaction forces simultaneously.

Isometric contraction with muscle fatigue

Intervention Type: DEVICE

An identical experiment will be performed as stated in "Isometric contraction" with the addition of induced muscle fatigue by repeatedly maintaining 40% of muscle torque until failure to maintain a contraction for 5 seconds.

Multi-joint functional activities while wearing exoskeleton

Intervention Type: DEVICE

Participants will be measured and fitted with the bilateral exoskeleton, and sufficient range of motion to used exoskeleton will be confirmed. HD-EMG grids will be applied to the lower limb muscles of interest. The participant will perform single-joint movements to calibrate the decoder parameters. The participant will then perform multi-joint activities (e.g., standing, squatting, walking overground or on a treadmill, cycling, or stair climbing) in a movement analysis laboratory

Clinical Participants

The investigators will look at muscle activity of participants post-stroke from eight lower limb muscles during functional tasks (e.g. single-joint movement, walking, squatting, cycling).

Group Type: EXPERIMENTAL

Isometric contractions

Intervention Type: OTHER

HD-EMG grids will be applied to the lower limb muscles of interest. Isometric contractions will consist of applying joint torque to reach a pre-defined torque level based on the subject's maximal voluntary contraction (i.e., 25%, 60%, 70%, 80%, 90%). The participant will control torque intensity by responding to a biofeedback displayed on a screen. The joint will be secured with non-compliant bands to prevent any movement of the participant. The order of the joints tested (i.e., dominant ankle, knee, or hip joint) will be randomized.

Isokinetic contractions

Intervention Type: OTHER

HD-EMG grids will be applied to the lower limb muscles of interest. Isometric contractions will consist of moving a joint to completing a set of contractions (10-20 contractions) at various velocities (i.e., 10 degrees per second, 30 degrees per second, 60 degrees per second). The joint will be secured with non-compliant bands to prevent any movement of the participant. The order of the joints tested (i.e., dominant ankle, knee, or hip joint) will be randomized.

Dynamic contractions

Intervention Type: DEVICE

HD-EMG grids will be applied to the lower limb muscles of interest. Multi-joint tasks (i.e. walking, squatting, cycling) will be performed at a given frequency. A motion capture system will be used to record the joint angles and ground reaction forces simultaneously.

Multi-joint functional activities while wearing exoskeleton

Intervention Type: DEVICE

Participants will be measured and fitted with the bilateral exoskeleton, and sufficient range of motion to used exoskeleton will be confirmed. HD-EMG grids will be applied to the lower limb muscles of interest. The participant will perform single-joint movements to calibrate the decoder parameters. The participant will then perform multi-joint activities (e.g., standing, squatting, walking overground or on a treadmill, cycling, or stair climbing) in a movement analysis laboratory

Clinical Assessments

Intervention Type: OTHER

Subjects may complete a 10 meter walk test (10MWT) overground or over a pressure-sensitive walkway, 6 minute walk test (6MWT), Berg Balance scale (BBS), and/or Functional Gait Assessment (FGA). They may also complete step ups or squats.

Interventions

Isometric contractions

HD-EMG grids will be applied to the lower limb muscles of interest. Isometric contractions will consist of applying joint torque to reach a pre-defined torque level based on the subject's maximal voluntary contraction (i.e., 25%, 60%, 70%, 80%, 90%). The participant will control torque intensity by responding to a biofeedback displayed on a screen. The joint will be secured with non-compliant bands to prevent any movement of the participant. The order of the joints tested (i.e., dominant ankle, knee, or hip joint) will be randomized.

Intervention Type: OTHER

Isokinetic contractions

HD-EMG grids will be applied to the lower limb muscles of interest. Isometric contractions will consist of moving a joint to completing a set of contractions (10-20 contractions) at various velocities (i.e., 10 degrees per second, 30 degrees per second, 60 degrees per second). The joint will be secured with non-compliant bands to prevent any movement of the participant. The order of the joints tested (i.e., dominant ankle, knee, or hip joint) will be randomized.

Intervention Type: OTHER

Dynamic contractions

HD-EMG grids will be applied to the lower limb muscles of interest. Multi-joint tasks (i.e. walking, squatting, cycling) will be performed at a given frequency. A motion capture system will be used to record the joint angles and ground reaction forces simultaneously.

Intervention Type: DEVICE

Isometric contraction with muscle fatigue

An identical experiment will be performed as stated in "Isometric contraction" with the addition of induced muscle fatigue by repeatedly maintaining 40% of muscle torque until failure to maintain a contraction for 5 seconds.

Intervention Type: DEVICE

Multi-joint functional activities while wearing exoskeleton

Participants will be measured and fitted with the bilateral exoskeleton, and sufficient range of motion to used exoskeleton will be confirmed. HD-EMG grids will be applied to the lower limb muscles of interest. The participant will perform single-joint movements to calibrate the decoder parameters. The participant will then perform multi-joint activities (e.g., standing, squatting, walking overground or on a treadmill, cycling, or stair climbing) in a movement analysis laboratory

Intervention Type: DEVICE

Clinical Assessments

Subjects may complete a 10 meter walk test (10MWT) overground or over a pressure-sensitive walkway, 6 minute walk test (6MWT), Berg Balance scale (BBS), and/or Functional Gait Assessment (FGA). They may also complete step ups or squats.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Age from 18 to 80 years
• No history of a brain and/or skull lesion
• Normal hearing and vision, both can be corrected
• Able to understand and give informed consent
• No neurological disorders
• Absence of pathology that could cause abnormal movements of extremities (e.g.,
• epilepsy, stroke, marked arthritis, chronic pain, musculoskeletal injuries)
• Able to understand and speak English
• Height between 3 foot 6 inches (1.1 meters) and 6 foot 9 inches (2.1 meters)

• Age from 18 to 80 years
• History of unilateral, supratentorial, ischemic or hemorrhage stroke greater than 6 months
• Ability to walk independently on level ground, allowed to use assistive device or bracing
• as needed
• Medically stable
• No planned surgeries, medical treatments or outpatient therapy during the study period
• Normal hearing and vision, both can be corrected
• Able to understand and give informed consent
• Able to understand and speak English
• Height between 3 foot 6 inches (1.1 meters) and 6 foot 9 inches (2.1 meters)

Exclusion Criteria

• Weight over 220 lbs
• Pregnancy (ruled out by pregnancy questionnaire)
• Any neurological diagnoses or medications influencing brain function
• History of significant head trauma (i.e., extended loss of consciousness, neurological
• sequelae)
• Known structural brain lesion
• Significant other disease (heart disease, malignant tumors, mental disorders)
• Non prescribed drug use (as reported by subject)
• History of current substance abuse (exception: current nicotine use is allowed)
• Recreational marijuana
• Dementia; severe depression; or prior neurosurgical procedures
• Failure to perform the behavioral or locomotor tasks
• Prisoners

• Weight over 220 lbs
• Pregnancy (ruled out by pregnancy questionnaire)
• Botox (botulinum toxin) injection to lower limbs within the prior 3 months, or planned
• injection during study period.
• History of current substance abuse (exception: current nicotine use is allowed)
• Reduced cognitive function
• Severe aphasia
• Prisoners
• Co-existence of other neurological diseases (ex: (Parkinson's disease, traumatic brain
• injury, multiple sclerosis, etc.)
• Mixed or complex tremors
• Severe hip, or knee arthritis
• Osteoporosis (as reported by subject)
• Medical (cardiac, renal, hepatic, oncological) or psychiatric disease that would
• interfere with study procedures for HD-EMG

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Shirley Ryan AbilityLab

OTHER

Sponsor Role: lead

Responsible Party

Jose Pons

Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Jose L Pons, Ph.D

Role: PRINCIPAL_INVESTIGATOR

Shirley Ryan AbilityLab

Locations

Shirley Ryan AbilityLab

Chicago, Illinois, United States

Countries

United States

Other Identifiers

STU00212191

Identifier Type: -

Identifier Source: org_study_id