<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04453943</url>
  </required_header>
  <id_info>
    <org_study_id>20553</org_study_id>
    <nct_id>NCT04453943</nct_id>
  </id_info>
  <brief_title>Modeling, Optimization, and Control Methods for a Personalized Hybrid Walking Exoskeleton</brief_title>
  <official_title>Modeling, Optimization, and Control Methods for a Personalized Hybrid Walking Exoskeleton</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>North Carolina State University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>U.S. National Science Foundation</agency>
      <agency_class>U.S. Fed</agency_class>
    </collaborator>
    <collaborator>
      <agency>University of North Carolina, Chapel Hill</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>North Carolina State University</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>Yes</is_fda_regulated_device>
    <is_unapproved_device>Yes</is_unapproved_device>
    <is_us_export>No</is_us_export>
  </oversight_info>
  <brief_summary>
    <textblock>
      The central objective of this study is to validate new algorithms that coordinate between&#xD;
      functional electrical stimulation (FES) and the exoskeleton during sitting-to-standing,&#xD;
      walking, and standing-to-sitting movements. The secondary objective is to optimize the&#xD;
      algorithms as well as assess their ability to reduce FES-induced muscle fatigue by using&#xD;
      ultrasound imaging as a sensing modality. This study will include persons with no&#xD;
      disabilities and persons with Spinal Cord Injury (SCI). A research set-up comprising of a&#xD;
      lower-limb exoskeleton and FES system will be used to achieve sitting-to-standing, walking,&#xD;
      and standing-to-sitting movements. Ultrasound Imaging probes may be used to record muscle&#xD;
      activity of the stimulated muscles. The signals derived from ultrasound will be used to&#xD;
      optimize FES in order to reduce muscle fatigue as well as assess muscle fatigue.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Research activities involve use of computer-controlled functional electrical stimulation&#xD;
      (FES) and electric motor-driven orthosis (powered exoskeleton) to generate functional&#xD;
      lower-limb movements for; i.e., standing and walking. The computer-controlled algorithms will&#xD;
      get feedback from sensors such as optical encoders, load cells, force sensitive resistors,&#xD;
      and inertial measurement units that are or will be inbuilt in the orthosis or these feedback&#xD;
      algorithms will be combined with precomputed optimized algorithms based on the estimated&#xD;
      musculoskeletal model of a participant. Multiple computer algorithms will be designed to&#xD;
      coordinate FES with electric motors and other components of the walking device to reproduce&#xD;
      or restore standing and walking movements. The study involves validation of computer&#xD;
      algorithms to estimate and control the walking and sitting/standing movements. The Rifton&#xD;
      E-Pacer motorized walker, arm crutches, parallel bars, or a conventional walker may be used&#xD;
      in order to assist donning and doffing of the exoskeleton system, standing, and walking for&#xD;
      all subjects, at any time during experimentation, for as long as is deemed necessary by the&#xD;
      experimental goals. Using the E-Pacer or a walker should improve experiment safety and reduce&#xD;
      the subject's overall physical exertion because it reduces load on the subject's body.&#xD;
      Sitting/Standing and/or walking movements will be elicited by the hybrid walking platform&#xD;
      that combines a powered exoskeleton and an FES system. The powered exoskeleton can provide&#xD;
      joint actuation at the hip and knee joints of a participant. The FES system can stimulate the&#xD;
      quadriceps, hamstrings muscle, glutes, and ankle muscles. The electrodes for stimulation are&#xD;
      placed on the skin at locations that provide an optimal limb movement. The algorithms are&#xD;
      designed such that the stimulation of different muscles are coordinated to achieve walking&#xD;
      and/or sitting/standing. A precedent experiment will be performed on a Group B participant&#xD;
      before it is tested on Group A. Unlike the paraplegic participants (Group A), if the device&#xD;
      should fail or act unexpectedly the persons without disability (Group B) will be able to&#xD;
      intervene . Therefore, testing the device on persons without disability first will allow us&#xD;
      to further assess and address any risks before testing on individuals with SCI, who are&#xD;
      incapable of intervening with the device. All the sessions for Group A participants will be&#xD;
      performed in the supervision of a physical therapist. The therapist will also assist the&#xD;
      Group A participants in transferring them from their wheelchairs to a cushioned table for&#xD;
      seating if required or to the exoskeleton. Group A participant will also be supported by a&#xD;
      body-unweighing system to prevent falling during standing and walking. Before each experiment&#xD;
      involving electrical stimulation, a participant's heart rate and blood pressure will be&#xD;
      recorded. Therapists will also assist the participants in transferring them from their&#xD;
      wheelchairs to the therapy table. A participant or an individual operating the device will&#xD;
      initiate walking and/or standing movement. A participant can stop the movements if he/she&#xD;
      feels not comfortable or unsafe by using a safety-stop button, which will be given to them.&#xD;
      During these sessions participants will wear a heart rate monitor to ensure that they do not&#xD;
      overexert themselves, and so that sufficient rest periods may be given. The participants'&#xD;
      heart rate will be checked before and after each trial by an individual conducting the&#xD;
      experiments. The Borg scale will be administered for Group A to check for their exertion&#xD;
      level. The sessions will be stopped as per the limits prescribed by the Borg scale (see&#xD;
      stopping criteria in risks section). Please note that for all experiments described, a&#xD;
      minimum of 1-2 days is required between visits for experimentation. These activities are&#xD;
      divided into Aim 1 and Aim 2. Please note that Aims 1-2 are not sequential. Aim 1: To elicit&#xD;
      sitting/standing and walking movements by using an optimized powered exoskeleton and&#xD;
      functional electrical stimulation (FES) assistance. The objective of this aim is to&#xD;
      experimentally validate an optimal controller that allocates FES and exoskeleton contribution&#xD;
      based on a person-specific model of a participant. The controller will produce lower-limb&#xD;
      movements in persons with no disabilities and persons with spinal cord injury. Group A and&#xD;
      Group B will participate in approximately 20 sessions. The number of sessions is approximate&#xD;
      and it may exceed this number and there is not cut-off number of sessions that will prohibit&#xD;
      further participation. The session duration will be up to 4 hours, at the maximum. The&#xD;
      session durations are approximate and it can be more or less than the specified. The total&#xD;
      number sessions may overshoot by few sessions for some participants due to unanticipated&#xD;
      technical or erroneous experimental data. These experiments will be conducted in the&#xD;
      Neuromuscular Control and Robotics Laboratory (NCRL) or at the Outpatient Rehabilitation&#xD;
      Clinic at Chapel-Hill run by the principal investigator. These experiments are divided into 2&#xD;
      tasks. Task 1: Initial visits for familiarization, training and model identification.&#xD;
      Familiarization and training visits will allow us to customize and optimize the hybrid&#xD;
      walking exoskeleton to each participating individual. For this task the participants will&#xD;
      visit the NCRL for approximately 3 sessions. These sessions will take no more than 4 hours.&#xD;
      The session durations are approximate and it can be more or less than the specified. The&#xD;
      total number sessions may overshoot by few sessions for some participants due to&#xD;
      unanticipated technical or erroneous experimental data. In the first visit, adjustments to&#xD;
      the hybrid device will be made to fit the device to the participant. In these visits, the&#xD;
      objectives are to train them for sit-to-stand transfers and perform walking movements with&#xD;
      the hybrid walking device. Computer controlled algorithms will be used for performing&#xD;
      sit-to-stand, stand-to-sit, and walking movements. Model identification experiments to find&#xD;
      model parameters for each individual can be run during initial training and familiarization&#xD;
      studies. These model identification experiments can be conducted while a participant&#xD;
      sits/stands or walk in the hybrid walking device. Once the subject-specific parameters are&#xD;
      identified, a walking and/or standing algorithm that coordinates FES with the powered&#xD;
      exoskeleton will be derived or optimized using offline dynamic optimizations. Task 2:&#xD;
      Validation of a sitting/standing and/or walking algorithm. After initial visits (Task 1),&#xD;
      walking and/or standing algorithm will be tested. The algorithm is a computer program that&#xD;
      takes sensory information from different sensors such optical encoders, inertial measurement&#xD;
      units, and heel contact sensors in-built in the hybrid walking system to optimally coordinate&#xD;
      FES and electric motors of the powered exoskeleton. The algorithm will be experimentally&#xD;
      validated on each participant in approximately 7 sessions. Each session will run for no more&#xD;
      than 4 hours, which includes time to perform standing, walking, periods of rest, time&#xD;
      required to adjust bracing, and time required to update the computer code if needed. Note&#xD;
      that the number of sessions and duration are estimates and are subject to change based on&#xD;
      conditions of the experiment. A motion capture system may also be used to measure joint&#xD;
      angles so that spatiotemporal gait characteristics can be compared with the normal gait of a&#xD;
      healthy control subject. The recorded gait data will also be used to assess the performance&#xD;
      of the control systems of the device, and to show how the user's gait changes over time as&#xD;
      they become more comfortable with using the device. These sessions may be recorded so that&#xD;
      the application and efficacy of the device may be illustrated. Aim 2: Integrating&#xD;
      ultrasound-based feedback to control a hybrid exoskeleton. The objectives of this aim are to&#xD;
      investigate if ultrasound imaging can be used as a tool to measure muscle fatigue induced by&#xD;
      FES and further use the US-derived signals to optimize FES and exoskeleton assistance. The&#xD;
      first objective of this aim is to develop an ultrasound based fatigue model to indicate the&#xD;
      onset of muscle fatigue. The second objective is to use the ultrasound-based fatigue model in&#xD;
      an algorithm that coordinates control of FES and electric motor during sitting-to-standing,&#xD;
      walking, and standing-to-sitting activities. Group A and Group B individuals will participate&#xD;
      in this aim. They will participate in approximately 10 sessions of no more than 4 hours each.&#xD;
      The total number sessions can be more or less than 10 due to unanticipated technical or&#xD;
      erroneous experimental data or if the participant leaves the study. These experiments will be&#xD;
      conducted in NCRL or at the Outpatient Rehabilitation Clinic at Chapel-Hill. Task 1:&#xD;
      Development of an ultrasound imaging based fatigue and recovery measures of leg muscles. A&#xD;
      stimulation protocol will be followed that produces muscle fatigue. Muscle fatigue is defined&#xD;
      as some percentage decline in isometric torque generated by FES of the quadriceps muscle.&#xD;
      Because decline in the isometric torque could differ in different participants a common&#xD;
      stimulation protocol will be employed for all the participants. This will be done during&#xD;
      approximately two sessions that will each last no more than 4 hours. The session durations&#xD;
      are approximate and it can be more or less than the specified. The total number sessions may&#xD;
      overshoot by few sessions for some participants due to unanticipated technical or erroneous&#xD;
      experimental data. Both ultrasound (using the imaging probe placed in between the electrodes)&#xD;
      and torque data (from the load sensor) will be collected. A hand-held commercial ultrasound&#xD;
      transducer (5- 20 MHz clinical transducer) connected to a commercial ultrasound system&#xD;
      (S-Sharp Corporation, Taiwan) placed against the skin. A warm gel is applied to the skin to&#xD;
      help with imaging. All the ultrasound imaging parameters including intensity and frame rates&#xD;
      etc. are below safety guidelines for clinical ultrasound imaging (MI values less than 1.9).&#xD;
      After these experiments, the processed ultrasound data will be correlated with the measured&#xD;
      torque to determine fatigue and recovery measures. Task 2: Incorporation of the&#xD;
      ultrasound-based fatigue model in a control allocation algorithm. The ultrasound&#xD;
      imaging-based fatigue and recovery measures can be used to predict the onset of muscle&#xD;
      fatigue. The experimental studies will be conducted on (Group A) and (Group B) over 2&#xD;
      sessions will each last no more than 4 hours. The session durations are approximate and it&#xD;
      can be more or less than the specified. The total number sessions may overshoot by few&#xD;
      sessions for some participants due to unanticipated technical or erroneous experimental data.&#xD;
      The algorithms in Task 2 of Aim 1 will be modified to incorporate the ultrasound-based&#xD;
      fatigue and recovery measures. Remark on stimulation parameters to be used in the&#xD;
      aforementioned aims: A normal range of stimulation to be used in our studies is: pulse width&#xD;
      100-400 micro seconds; Frequency: 20-100 Hz; Current 0-100 mA. Generally during the&#xD;
      experiment, the current is automatically modulated (or in some instances manually) starting&#xD;
      from 0 mA to the value that is required to achieve a task. This is achieved by feedback&#xD;
      signals to the control system that communicates with the stimulator. The control system does&#xD;
      not allow the current to go above its maximum limit. The pulsewidth and frequency are&#xD;
      generally kept constant. The stimulation parameters used for each participant will be&#xD;
      documented for each experimental session and any changes in the stimulation parameters during&#xD;
      a session will also be recorded.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Not yet recruiting</last_known_status>
  <start_date type="Anticipated">July 1, 2020</start_date>
  <completion_date type="Anticipated">January 1, 2023</completion_date>
  <primary_completion_date type="Anticipated">January 1, 2023</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Non-Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <intervention_model_description>The central objective of this study is to validate new algorithms that coordinate between functional electrical stimulation (FES) and the exoskeleton during sitting-to-standing, walking, and standing-to-sitting movements. The secondary objective is to optimize the algorithms as well as assess their ability to reduce FES-induced muscle fatigue by using ultrasound imaging as a sensing modality.&#xD;
This study is performed with two sets of subjects: people with spinal cord injury and people without disability.</intervention_model_description>
    <primary_purpose>Other</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Controls Algorithm Performance - Limb Angle Errors</measure>
    <time_frame>Through study completion, an average of 30 months.</time_frame>
    <description>The computer-controlled algorithms will get feedback from sensors that are inbuilt in the neuroprosthesis (exoskeleton). A motion capture system may also be used to measure joint angles so that spatiotemporal gait characteristics can be compared with the normal gait of a healthy control subject. Ultrasound imaging can be used as a tool to measure muscle fatigue induced by FES. The performance of the controls algorithm and success of the movements generated will be evaluated after this data is collected.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Muscle fatigue Index to Measure FES-Induced Muscle Fatigue</measure>
    <time_frame>Through study completion, an average of 30 months.</time_frame>
    <description>The muscle fatigue index will be measured to assess muscle fatigue in a participant using the hybrid neuroprosthesis/exoskeleton.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Participant Verbal Feedback</measure>
    <time_frame>Through study completion, an average of 30 months.</time_frame>
    <description>We may ask the participant about their qualitative experience about the of our device and algorithms during the experiments.</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Anticipated">30</enrollment>
  <condition>Spinal Cord Injuries</condition>
  <condition>Paraplegia, Spinal</condition>
  <condition>Paraplegia, Incomplete</condition>
  <arm_group>
    <arm_group_label>Group A - SCI</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Ten individuals with SCI at the T1-T10 level will be recruited (Group A). These individuals can have incomplete or complete paraplegia.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Group B - Subjects without disability</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Twenty individuals without disability will be recruited (Group B). Individuals with SCI who have experience in using some kind of walking assistive devices in the recent past will be preferably recruited.</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>Exoskeleton Walking - with or without FES</intervention_name>
    <description>The study involves validation of computer algorithms to estimate and control walking movements. The Rifton E-Pacer motorized walker, arm crutches, parallel bars, or a conventional walker may be used in order to assist donning and doffing of the exoskeleton system, standing, and walking for all subjects, at any time during experimentation. Walking movements will be elicited by the hybrid walking platform that combines a powered exoskeleton and an FES system. The powered exoskeleton can provide joint actuation at the hip and knee joints of a participant. The FES system can stimulate the quadriceps, hamstrings muscle, glutes, and ankle muscles.</description>
    <arm_group_label>Group A - SCI</arm_group_label>
    <arm_group_label>Group B - Subjects without disability</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>Exoskeleton Sitting to Standing - with or without FES</intervention_name>
    <description>The study involves validation of computer algorithms to estimate and control sitting/standing movements. The Rifton E-Pacer motorized walker, arm crutches, parallel bars, or a conventional walker may be used in order to assist donning and doffing of the exoskeleton system, standing, and walking for all subjects, at any time during experimentation. Sitting/Standing movements will be elicited by the hybrid walking platform that combines a powered exoskeleton and an FES system. The powered exoskeleton can provide joint actuation at the hip and knee joints of a participant. The FES system can stimulate the quadriceps, hamstrings muscle, glutes, and ankle muscles.</description>
    <arm_group_label>Group A - SCI</arm_group_label>
    <arm_group_label>Group B - Subjects without disability</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion criteria for persons with SCI:&#xD;
&#xD;
          1. Participants will be men and women age 18-60 and have a primary diagnosis of complete&#xD;
             or incomplete spinal cord injury, weigh less than 220 pounds (100kg), free from acute&#xD;
             illness, and be at least 1 year post injury.&#xD;
&#xD;
          2. Individuals with injury between T-1 and T-10 level will be recruited (injury level for&#xD;
             each participant will be assessed by a therapist on ASIA scale).&#xD;
&#xD;
          3. Medically stable with medical clearance for participation, no evidence of&#xD;
             cardiopulmonary or pulmonary disease, severe spasticity, asymmetric hip positions.&#xD;
&#xD;
          4. Individuals who regularly bear weight bear during transfers (either with or without&#xD;
             braces) so that we are using people who are accustomed to bearing weight on their&#xD;
             lower limbs&#xD;
&#xD;
          5. The subjects who have experience in using some kind of walking assistive devices in&#xD;
             the past or recently will be recruited.&#xD;
&#xD;
          6. Subjects must have at least one lower limb muscle group respond to FES.&#xD;
&#xD;
        Inclusion criteria for persons without SCI:&#xD;
&#xD;
          1. Subjects will be included if they are between the ages of 18 and 60 and weigh less&#xD;
             than 220 lbs (100kg).&#xD;
&#xD;
          2. Healthy, are able to walk normally, are able to sit patiently for 4 hours.&#xD;
&#xD;
          3. People who pass an assessment of safety by Dr. Cleveland. This would be a screen done&#xD;
             by Dr. Cleveland after consent to determine if person is eligible. The proposed&#xD;
             research will exclude children and pregnant women. We first aim to collect research&#xD;
             data from adults as the proposed methods in the study have not been investigated on&#xD;
             children and pregnant women.&#xD;
&#xD;
        Exclusion criteria for persons with SCI:&#xD;
&#xD;
          1. Subjects with other neuromuscular disease such as polio, stroke or multiple sclerosis.&#xD;
&#xD;
          2. Persons with heart conditions and pacemakers will be excluded.&#xD;
&#xD;
          3. Concurrent severe medical disease, pressure sores, open wounds, existing infection,&#xD;
             unstable spine, unhealed limb or pelvic fractures, history of recurrent fractures,&#xD;
             known orthopedic injury to lower extremities, and osteoporosis.&#xD;
&#xD;
          4. Subjects with SCI who have open wounds, weight if with weight exceeds more than 220lb&#xD;
             (100kg)&#xD;
&#xD;
          5. Subjects with SCI with insufficient knee or hip range of motion, i.e. contractures&#xD;
             will be excluded. If someone has contractures it may not be possible, or safe, for&#xD;
             them to be in the device. Persons who do not have following minimum joint angle range&#xD;
             of motion: knee flexion from 0-80°, hip flexion from 0-45° and hip extension 0-10°&#xD;
             will be excluded.&#xD;
&#xD;
          6. Subjects who find FES uncomfortable or painful; particularly, FES of the quadriceps&#xD;
             muscle, hamstrings muscle, and ankle muscles.&#xD;
&#xD;
        Exclusion criteria for persons without SCI: 1. A history of a neurological or an orthopedic&#xD;
        disease that hampers normal lower limb movement 2. Persons with heart conditions and&#xD;
        pacemakers will be excluded. 3. Any difficulty or an orthopedic condition that would impede&#xD;
        knee extension 4. Absent sensation in lower leg 5. Subjects who find FES uncomfortable or&#xD;
        painful; particularly, FES of the quadriceps muscle, hamstrings muscle, and ankle muscles.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>60 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Nitin Sharma, Ph.D.</last_name>
    <phone>919-513-0787</phone>
    <email>nsharm23@ncsu.edu</email>
  </overall_contact>
  <location>
    <facility>
      <name>4212C Engineering Building III 1840 Entrepreneur Dr.</name>
      <address>
        <city>Raleigh</city>
        <state>North Carolina</state>
        <zip>27695</zip>
        <country>United States</country>
      </address>
    </facility>
    <contact>
      <last_name>Nitin Sharma, Ph.D.</last_name>
      <email>nsharm23@ncsu.edu</email>
    </contact>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <reference>
    <citation>Bao X, Kirsch N, Dodson A, Sharma N. Model Predictive Control of a Feedback-Linearized Hybrid Neuroprosthetic System With a Barrier Penalty. J Comput Nonlinear Dyn. 2019 Oct 1;14(10):101009-1010097. doi: 10.1115/1.4042903. Epub 2019 Sep 9.</citation>
    <PMID>32280315</PMID>
  </reference>
  <reference>
    <citation>Kirsch NA, Bao X, Alibeji NA, Dicianno BE, Sharma N. Model-Based Dynamic Control Allocation in a Hybrid Neuroprosthesis. IEEE Trans Neural Syst Rehabil Eng. 2018 Jan;26(1):224-232. doi: 10.1109/TNSRE.2017.2756023. Epub 2017 Sep 22.</citation>
    <PMID>28952946</PMID>
  </reference>
  <reference>
    <citation>Alibeji NA, Molazadeh V, Dicianno BE, Sharma N. A Control Scheme That Uses Dynamic Postural Synergies to Coordinate a Hybrid Walking Neuroprosthesis: Theory and Experiments. Front Neurosci. 2018 Apr 10;12:159. doi: 10.3389/fnins.2018.00159. eCollection 2018.</citation>
    <PMID>29692699</PMID>
  </reference>
  <reference>
    <citation>Alibeji NA, Kirsch NA, Sharma N. A Muscle Synergy-Inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis. Front Bioeng Biotechnol. 2015 Dec 21;3:203. doi: 10.3389/fbioe.2015.00203. eCollection 2015.</citation>
    <PMID>26734606</PMID>
  </reference>
  <reference>
    <citation>Kirsch N, Alibeji N, Fisher L, Gregory C, Sharma N. A semi-active hybrid neuroprosthesis for restoring lower limb function in paraplegics. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:2557-60. doi: 10.1109/EMBC.2014.6944144.</citation>
    <PMID>25570512</PMID>
  </reference>
  <verification_date>June 2020</verification_date>
  <study_first_submitted>May 18, 2020</study_first_submitted>
  <study_first_submitted_qc>June 26, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 1, 2020</study_first_posted>
  <last_update_submitted>June 26, 2020</last_update_submitted>
  <last_update_submitted_qc>June 26, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">July 1, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>North Carolina State University</investigator_affiliation>
    <investigator_full_name>Nitin Sharma</investigator_full_name>
    <investigator_title>Principal Investigator</investigator_title>
  </responsible_party>
  <keyword>Rehabilitative Robotics</keyword>
  <keyword>Exoskeleton</keyword>
  <keyword>Hybrid Neuroprosthesis</keyword>
  <keyword>Spinal Cord Injury</keyword>
  <keyword>Functional Electrical Stimulation</keyword>
  <keyword>Ultrasound</keyword>
  <keyword>Muscular Fatigue</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Spinal Cord Injuries</mesh_term>
    <mesh_term>Paraplegia</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
    <ipd_description>IPD will not be shared outside of this research group. However, selected data may be published in academic journals, conference papers, or other publications. This data will be de-identified, and will not include the full set of data.</ipd_description>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04453943
org study id: 20553
nct id: NCT04453943
lead sponsor: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: Yes
is unapproved device: Yes
is us export: No
The central objective of this study is to validate new algorithms that coordinate between
      functional electrical stimulation (FES) and the exoskeleton during sitting-to-standing,
      walking, and standing-to-sitting movements. The secondary objective is to optimize the
      algorithms as well as assess their ability to reduce FES-induced muscle fatigue by using
      ultrasound imaging as a sensing modality. This study will include persons with no
      disabilities and persons with Spinal Cord Injury (SCI). A research set-up comprising of a
      lower-limb exoskeleton and FES system will be used to achieve sitting-to-standing, walking,
      and standing-to-sitting movements. Ultrasound Imaging probes may be used to record muscle
      activity of the stimulated muscles. The signals derived from ultrasound will be used to
      optimize FES in order to reduce muscle fatigue as well as assess muscle fatigue.
Research activities involve use of computer-controlled functional electrical stimulation
      (FES) and electric motor-driven orthosis (powered exoskeleton) to generate functional
      lower-limb movements for; i.e., standing and walking. The computer-controlled algorithms will
      get feedback from sensors such as optical encoders, load cells, force sensitive resistors,
      and inertial measurement units that are or will be inbuilt in the orthosis or these feedback
      algorithms will be combined with precomputed optimized algorithms based on the estimated
      musculoskeletal model of a participant. Multiple computer algorithms will be designed to
      coordinate FES with electric motors and other components of the walking device to reproduce
      or restore standing and walking movements. The study involves validation of computer
      algorithms to estimate and control the walking and sitting/standing movements. The Rifton
      E-Pacer motorized walker, arm crutches, parallel bars, or a conventional walker may be used
      in order to assist donning and doffing of the exoskeleton system, standing, and walking for
      all subjects, at any time during experimentation, for as long as is deemed necessary by the
      experimental goals. Using the E-Pacer or a walker should improve experiment safety and reduce
      the subject's overall physical exertion because it reduces load on the subject's body.
      Sitting/Standing and/or walking movements will be elicited by the hybrid walking platform
      that combines a powered exoskeleton and an FES system. The powered exoskeleton can provide
      joint actuation at the hip and knee joints of a participant. The FES system can stimulate the
      quadriceps, hamstrings muscle, glutes, and ankle muscles. The electrodes for stimulation are
      placed on the skin at locations that provide an optimal limb movement. The algorithms are
      designed such that the stimulation of different muscles are coordinated to achieve walking
      and/or sitting/standing. A precedent experiment will be performed on a Group B participant
      before it is tested on Group A. Unlike the paraplegic participants (Group A), if the device
      should fail or act unexpectedly the persons without disability (Group B) will be able to
      intervene . Therefore, testing the device on persons without disability first will allow us
      to further assess and address any risks before testing on individuals with SCI, who are
      incapable of intervening with the device. All the sessions for Group A participants will be
      performed in the supervision of a physical therapist. The therapist will also assist the
      Group A participants in transferring them from their wheelchairs to a cushioned table for
      seating if required or to the exoskeleton. Group A participant will also be supported by a
      body-unweighing system to prevent falling during standing and walking. Before each experiment
      involving electrical stimulation, a participant's heart rate and blood pressure will be
      recorded. Therapists will also assist the participants in transferring them from their
      wheelchairs to the therapy table. A participant or an individual operating the device will
      initiate walking and/or standing movement. A participant can stop the movements if he/she
      feels not comfortable or unsafe by using a safety-stop button, which will be given to them.
      During these sessions participants will wear a heart rate monitor to ensure that they do not
      overexert themselves, and so that sufficient rest periods may be given. The participants'
      heart rate will be checked before and after each trial by an individual conducting the
      experiments. The Borg scale will be administered for Group A to check for their exertion
      level. The sessions will be stopped as per the limits prescribed by the Borg scale (see
      stopping criteria in risks section). Please note that for all experiments described, a
      minimum of 1-2 days is required between visits for experimentation. These activities are
      divided into Aim 1 and Aim 2. Please note that Aims 1-2 are not sequential. Aim 1: To elicit
      sitting/standing and walking movements by using an optimized powered exoskeleton and
      functional electrical stimulation (FES) assistance. The objective of this aim is to
      experimentally validate an optimal controller that allocates FES and exoskeleton contribution
      based on a person-specific model of a participant. The controller will produce lower-limb
      movements in persons with no disabilities and persons with spinal cord injury. Group A and
      Group B will participate in approximately 20 sessions. The number of sessions is approximate
      and it may exceed this number and there is not cut-off number of sessions that will prohibit
      further participation. The session duration will be up to 4 hours, at the maximum. The
      session durations are approximate and it can be more or less than the specified. The total
      number sessions may overshoot by few sessions for some participants due to unanticipated
      technical or erroneous experimental data. These experiments will be conducted in the
      Neuromuscular Control and Robotics Laboratory (NCRL) or at the Outpatient Rehabilitation
      Clinic at Chapel-Hill run by the principal investigator. These experiments are divided into 2
      tasks. Task 1: Initial visits for familiarization, training and model identification.
      Familiarization and training visits will allow us to customize and optimize the hybrid
      walking exoskeleton to each participating individual. For this task the participants will
      visit the NCRL for approximately 3 sessions. These sessions will take no more than 4 hours.
      The session durations are approximate and it can be more or less than the specified. The
      total number sessions may overshoot by few sessions for some participants due to
      unanticipated technical or erroneous experimental data. In the first visit, adjustments to
      the hybrid device will be made to fit the device to the participant. In these visits, the
      objectives are to train them for sit-to-stand transfers and perform walking movements with
      the hybrid walking device. Computer controlled algorithms will be used for performing
      sit-to-stand, stand-to-sit, and walking movements. Model identification experiments to find
      model parameters for each individual can be run during initial training and familiarization
      studies. These model identification experiments can be conducted while a participant
      sits/stands or walk in the hybrid walking device. Once the subject-specific parameters are
      identified, a walking and/or standing algorithm that coordinates FES with the powered
      exoskeleton will be derived or optimized using offline dynamic optimizations. Task 2:
      Validation of a sitting/standing and/or walking algorithm. After initial visits (Task 1),
      walking and/or standing algorithm will be tested. The algorithm is a computer program that
      takes sensory information from different sensors such optical encoders, inertial measurement
      units, and heel contact sensors in-built in the hybrid walking system to optimally coordinate
      FES and electric motors of the powered exoskeleton. The algorithm will be experimentally
      validated on each participant in approximately 7 sessions. Each session will run for no more
      than 4 hours, which includes time to perform standing, walking, periods of rest, time
      required to adjust bracing, and time required to update the computer code if needed. Note
      that the number of sessions and duration are estimates and are subject to change based on
      conditions of the experiment. A motion capture system may also be used to measure joint
      angles so that spatiotemporal gait characteristics can be compared with the normal gait of a
      healthy control subject. The recorded gait data will also be used to assess the performance
      of the control systems of the device, and to show how the user's gait changes over time as
      they become more comfortable with using the device. These sessions may be recorded so that
      the application and efficacy of the device may be illustrated. Aim 2: Integrating
      ultrasound-based feedback to control a hybrid exoskeleton. The objectives of this aim are to
      investigate if ultrasound imaging can be used as a tool to measure muscle fatigue induced by
      FES and further use the US-derived signals to optimize FES and exoskeleton assistance. The
      first objective of this aim is to develop an ultrasound based fatigue model to indicate the
      onset of muscle fatigue. The second objective is to use the ultrasound-based fatigue model in
      an algorithm that coordinates control of FES and electric motor during sitting-to-standing,
      walking, and standing-to-sitting activities. Group A and Group B individuals will participate
      in this aim. They will participate in approximately 10 sessions of no more than 4 hours each.
      The total number sessions can be more or less than 10 due to unanticipated technical or
      erroneous experimental data or if the participant leaves the study. These experiments will be
      conducted in NCRL or at the Outpatient Rehabilitation Clinic at Chapel-Hill. Task 1:
      Development of an ultrasound imaging based fatigue and recovery measures of leg muscles. A
      stimulation protocol will be followed that produces muscle fatigue. Muscle fatigue is defined
      as some percentage decline in isometric torque generated by FES of the quadriceps muscle.
      Because decline in the isometric torque could differ in different participants a common
      stimulation protocol will be employed for all the participants. This will be done during
      approximately two sessions that will each last no more than 4 hours. The session durations
      are approximate and it can be more or less than the specified. The total number sessions may
      overshoot by few sessions for some participants due to unanticipated technical or erroneous
      experimental data. Both ultrasound (using the imaging probe placed in between the electrodes)
      and torque data (from the load sensor) will be collected. A hand-held commercial ultrasound
      transducer (5- 20 MHz clinical transducer) connected to a commercial ultrasound system
      (S-Sharp Corporation, Taiwan) placed against the skin. A warm gel is applied to the skin to
      help with imaging. All the ultrasound imaging parameters including intensity and frame rates
      etc. are below safety guidelines for clinical ultrasound imaging (MI values less than 1.9).
      After these experiments, the processed ultrasound data will be correlated with the measured
      torque to determine fatigue and recovery measures. Task 2: Incorporation of the
      ultrasound-based fatigue model in a control allocation algorithm. The ultrasound
      imaging-based fatigue and recovery measures can be used to predict the onset of muscle
      fatigue. The experimental studies will be conducted on (Group A) and (Group B) over 2
      sessions will each last no more than 4 hours. The session durations are approximate and it
      can be more or less than the specified. The total number sessions may overshoot by few
      sessions for some participants due to unanticipated technical or erroneous experimental data.
      The algorithms in Task 2 of Aim 1 will be modified to incorporate the ultrasound-based
      fatigue and recovery measures. Remark on stimulation parameters to be used in the
      aforementioned aims: A normal range of stimulation to be used in our studies is: pulse width
      100-400 micro seconds; Frequency: 20-100 Hz; Current 0-100 mA. Generally during the
      experiment, the current is automatically modulated (or in some instances manually) starting
      from 0 mA to the value that is required to achieve a task. This is achieved by feedback
      signals to the control system that communicates with the stimulator. The control system does
      not allow the current to go above its maximum limit. The pulsewidth and frequency are
      generally kept constant. The stimulation parameters used for each participant will be
      documented for each experimental session and any changes in the stimulation parameters during
      a session will also be recorded.
allocation: Non-Randomized
intervention model: Parallel Assignment
intervention model description: The central objective of this study is to validate new algorithms that coordinate between functional electrical stimulation (FES) and the exoskeleton during sitting-to-standing, walking, and standing-to-sitting movements. The secondary objective is to optimize the algorithms as well as assess their ability to reduce FES-induced muscle fatigue by using ultrasound imaging as a sensing modality.
This study is performed with two sets of subjects: people with spinal cord injury and people without disability.
primary purpose: Other
masking: None (Open Label)
measure: Controls Algorithm Performance - Limb Angle Errors
time frame: Through study completion, an average of 30 months.
description: The computer-controlled algorithms will get feedback from sensors that are inbuilt in the neuroprosthesis (exoskeleton). A motion capture system may also be used to measure joint angles so that spatiotemporal gait characteristics can be compared with the normal gait of a healthy control subject. Ultrasound imaging can be used as a tool to measure muscle fatigue induced by FES. The performance of the controls algorithm and success of the movements generated will be evaluated after this data is collected.
measure: Muscle fatigue Index to Measure FES-Induced Muscle Fatigue
time frame: Through study completion, an average of 30 months.
description: The muscle fatigue index will be measured to assess muscle fatigue in a participant using the hybrid neuroprosthesis/exoskeleton.
measure: Participant Verbal Feedback
time frame: Through study completion, an average of 30 months.
description: We may ask the participant about their qualitative experience about the of our device and algorithms during the experiments.
arm group label: Group A - SCI
arm group type: Experimental
description: Ten individuals with SCI at the T1-T10 level will be recruited (Group A). These individuals can have incomplete or complete paraplegia.
arm group label: Group B - Subjects without disability
arm group type: Experimental
description: Twenty individuals without disability will be recruited (Group B). Individuals with SCI who have experience in using some kind of walking assistive devices in the recent past will be preferably recruited.
intervention type: Device
intervention name: Exoskeleton Walking - with or without FES
description: The study involves validation of computer algorithms to estimate and control walking movements. The Rifton E-Pacer motorized walker, arm crutches, parallel bars, or a conventional walker may be used in order to assist donning and doffing of the exoskeleton system, standing, and walking for all subjects, at any time during experimentation. Walking movements will be elicited by the hybrid walking platform that combines a powered exoskeleton and an FES system. The powered exoskeleton can provide joint actuation at the hip and knee joints of a participant. The FES system can stimulate the quadriceps, hamstrings muscle, glutes, and ankle muscles.
arm group label: Group A - SCI
arm group label: Group B - Subjects without disability
intervention type: Device
intervention name: Exoskeleton Sitting to Standing - with or without FES
description: The study involves validation of computer algorithms to estimate and control sitting/standing movements. The Rifton E-Pacer motorized walker, arm crutches, parallel bars, or a conventional walker may be used in order to assist donning and doffing of the exoskeleton system, standing, and walking for all subjects, at any time during experimentation. Sitting/Standing movements will be elicited by the hybrid walking platform that combines a powered exoskeleton and an FES system. The powered exoskeleton can provide joint actuation at the hip and knee joints of a participant. The FES system can stimulate the quadriceps, hamstrings muscle, glutes, and ankle muscles.
arm group label: Group A - SCI
arm group label: Group B - Subjects without disability
criteria: 
gender: All
minimum age: 18 Years
maximum age: 60 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Nitin Sharma, Ph.D.
phone: 919-513-0787
email: nsharm23@ncsu.edu
facility: 
contact: 
country: United States
citation: Bao X, Kirsch N, Dodson A, Sharma N. Model Predictive Control of a Feedback-Linearized Hybrid Neuroprosthetic System With a Barrier Penalty. J Comput Nonlinear Dyn. 2019 Oct 1;14(10):101009-1010097. doi: 10.1115/1.4042903. Epub 2019 Sep 9.
PMID: 32280315
citation: Kirsch NA, Bao X, Alibeji NA, Dicianno BE, Sharma N. Model-Based Dynamic Control Allocation in a Hybrid Neuroprosthesis. IEEE Trans Neural Syst Rehabil Eng. 2018 Jan;26(1):224-232. doi: 10.1109/TNSRE.2017.2756023. Epub 2017 Sep 22.
PMID: 28952946
citation: Alibeji NA, Molazadeh V, Dicianno BE, Sharma N. A Control Scheme That Uses Dynamic Postural Synergies to Coordinate a Hybrid Walking Neuroprosthesis: Theory and Experiments. Front Neurosci. 2018 Apr 10;12:159. doi: 10.3389/fnins.2018.00159. eCollection 2018.
PMID: 29692699
citation: Alibeji NA, Kirsch NA, Sharma N. A Muscle Synergy-Inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis. Front Bioeng Biotechnol. 2015 Dec 21;3:203. doi: 10.3389/fbioe.2015.00203. eCollection 2015.
PMID: 26734606
citation: Kirsch N, Alibeji N, Fisher L, Gregory C, Sharma N. A semi-active hybrid neuroprosthesis for restoring lower limb function in paraplegics. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:2557-60. doi: 10.1109/EMBC.2014.6944144.
PMID: 25570512
responsible party type: Principal Investigator
investigator affiliation: North Carolina State University
investigator full name: Nitin Sharma
investigator title: Principal Investigator
mesh term: Spinal Cord Injuries
mesh term: Paraplegia
sharing ipd: No
ipd description: IPD will not be shared outside of this research group. However, selected data may be published in academic journals, conference papers, or other publications. This data will be de-identified, and will not include the full set of data.