<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/NCT03289572</url>
  </required_header>
  <id_info>
    <org_study_id>STUDY00003073</org_study_id>
    <nct_id>NCT03289572</nct_id>
  </id_info>
  <brief_title>Microgrid II - Electrocorticography Signals for Human Hand Prosthetics</brief_title>
  <official_title>Microgrid II - Electrocorticography Signals for Human Hand Prosthetics</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Washington</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>University of Washington</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Neurologic disease with loss of motor function is a major health burden. Brain-computer&#xD;
      interfaces (BCI) are systems that use brain signals to power an external device, such as a&#xD;
      communication board or a prosthetic device, which may help people with loss of motor&#xD;
      function. Electrocorticography (ECoG) has been used to decode hand movements and as a control&#xD;
      signal for brain-computer interface (BCI). This study hopes to use a smaller spacing of ECoG&#xD;
      to see if a better motor signal can be found and used as a BCI control signal.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Stroke, spinal cord injury, extremity injury and degenerative/locked-in syndromes are among&#xD;
      those conditions that may benefit from sustainable neuroprosthetic options. The investigators&#xD;
      have studied human motor cortex and related cortical areas with direct brain recording&#xD;
      (electrocorticography or ECoG) as a signal for motor neuroprosthetics. Completing exciting&#xD;
      studies in humans with local fields using intracortical electrodes and long-term working&#xD;
      brain-computer interfaces with EEG, electrocorticography surveys an intermediate level of&#xD;
      spatial specificity and may have durability in long-term recordings. ECoG signals could&#xD;
      ultimately be obtained epidurally or even more superficially if the exact signals were better&#xD;
      understood. To date, the investigators have demonstrated that ECoG signals from motor cortex&#xD;
      can be used to decode movement and have a precision using clinic arrays (1 cm resolution)&#xD;
      that can decode hand movement and allow for the separation of digit movement. These signals&#xD;
      have been used for brain-computer interface and can be used to control a prosthetic hand in&#xD;
      humans.&#xD;
&#xD;
      Electrocorticography (ECoG) is the recording of brain signals directly from the cortical&#xD;
      surface. In patients undergoing surgical treatment of epilepsy, these signals have been&#xD;
      available and have shown to be rich sources of motor-related signals that can drive a hand&#xD;
      neuroprosthetic as part of a brain-computer interface (BCI). Though the clinically available&#xD;
      resolution of 1 cm allows for separation of different types of finger movement by using the&#xD;
      high-frequency characteristics of the ECoG recording (70-100Hz), higher spatial resolutions&#xD;
      (3mm) increases the ability to decode finger movements and more complicated hand movements,&#xD;
      such as grasping of different objects. Ideal resolution is one of the several gaps in&#xD;
      knowledge limit pursuing implementation of ECoG-based BCI along with uncertainty about the&#xD;
      longevity of ECoG signals and human implementation of feedback directly to cortex through&#xD;
      electrical stimulation.&#xD;
&#xD;
      Specific Aim:&#xD;
&#xD;
      Higher resolution arrays over subacute (1 week) time frame to allow for adaptation and BCI&#xD;
      use of the higher resolution signals. An 8x8 array of 3mm resolution will be placed over&#xD;
      sensorimotor cortex. Grasp synergies will be determined and mapped onto the electrodes to&#xD;
      determine control channels for each synergy. Control of multiple synergies will move a&#xD;
      simulated robotic hand to a visually cued target shape&#xD;
&#xD;
        1. Hand synergies will be independently mapped onto the 3mm x 3mm (microarray) with at&#xD;
           least one independent electrode for each of the first three synergies&#xD;
&#xD;
        2. Using the signals from the microarray, participants will correctly move the robotic hand&#xD;
           into one of 6 target postures with 50% accuracy.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Recruiting</overall_status>
  <start_date type="Actual">November 2015</start_date>
  <completion_date type="Anticipated">December 2024</completion_date>
  <primary_completion_date type="Anticipated">December 2023</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Only</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>This is an observational study and the outcome is successful measurement of motor-related corticography signals.</measure>
    <time_frame>7-10 days</time_frame>
    <description>Successful measurement of motor-related corticography signals</description>
  </primary_outcome>
  <enrollment type="Anticipated">20</enrollment>
  <condition>Epilepsy Intractable</condition>
  <eligibility>
    <study_pop>
      <textblock>
        Patients with intractable epilepsy ages 18 and above scheduled to undergo grid placement&#xD;
        for epilepsy treatment.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Must be able to speak and read English&#xD;
&#xD;
          -  Cognitive ability to follow study directions&#xD;
&#xD;
          -  Patients that are scheduled to undergo grid placement clinically for treatment of&#xD;
&#xD;
          -  intractable epilepsy&#xD;
&#xD;
          -  18 years of age or older&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Patients who are not considered candidates for epilepsy surgery&#xD;
&#xD;
          -  Individuals who have a diagnosis that would not allow them to participate in research&#xD;
             procedures. For example, a physical disability that would limit hand movements and&#xD;
             range of motion.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Jeffrey G Ojemann, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Washington</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Amy m Anderson, BSN</last_name>
    <phone>206-744-9364</phone>
    <email>amya9@uw.edu</email>
  </overall_contact>
  <location>
    <facility>
      <name>Harborview Medical Center</name>
      <address>
        <city>Seattle</city>
        <state>Washington</state>
        <zip>98104</zip>
        <country>United States</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Amy Anderson</last_name>
      <phone>206-744-9364</phone>
      <email>amya9@uw.edu</email>
    </contact>
    <investigator>
      <last_name>Jeffrey G Ojemann, MD</last_name>
      <role>Principal Investigator</role>
    </investigator>
    <investigator>
      <last_name>Andrew Ko, MD</last_name>
      <role>Sub-Investigator</role>
    </investigator>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>April 2021</verification_date>
  <study_first_submitted>September 15, 2017</study_first_submitted>
  <study_first_submitted_qc>September 19, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">September 21, 2017</study_first_posted>
  <last_update_submitted>April 26, 2021</last_update_submitted>
  <last_update_submitted_qc>April 26, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">April 27, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Washington</investigator_affiliation>
    <investigator_full_name>Jeffrey Ojemann</investigator_full_name>
    <investigator_title>Professor Neurological Surgery</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Drug Resistant Epilepsy</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </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/NCT03289572
org study id: STUDY00003073
nct id: NCT03289572
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Neurologic disease with loss of motor function is a major health burden. Brain-computer
      interfaces (BCI) are systems that use brain signals to power an external device, such as a
      communication board or a prosthetic device, which may help people with loss of motor
      function. Electrocorticography (ECoG) has been used to decode hand movements and as a control
      signal for brain-computer interface (BCI). This study hopes to use a smaller spacing of ECoG
      to see if a better motor signal can be found and used as a BCI control signal.
Stroke, spinal cord injury, extremity injury and degenerative/locked-in syndromes are among
      those conditions that may benefit from sustainable neuroprosthetic options. The investigators
      have studied human motor cortex and related cortical areas with direct brain recording
      (electrocorticography or ECoG) as a signal for motor neuroprosthetics. Completing exciting
      studies in humans with local fields using intracortical electrodes and long-term working
      brain-computer interfaces with EEG, electrocorticography surveys an intermediate level of
      spatial specificity and may have durability in long-term recordings. ECoG signals could
      ultimately be obtained epidurally or even more superficially if the exact signals were better
      understood. To date, the investigators have demonstrated that ECoG signals from motor cortex
      can be used to decode movement and have a precision using clinic arrays (1 cm resolution)
      that can decode hand movement and allow for the separation of digit movement. These signals
      have been used for brain-computer interface and can be used to control a prosthetic hand in
      humans.

      Electrocorticography (ECoG) is the recording of brain signals directly from the cortical
      surface. In patients undergoing surgical treatment of epilepsy, these signals have been
      available and have shown to be rich sources of motor-related signals that can drive a hand
      neuroprosthetic as part of a brain-computer interface (BCI). Though the clinically available
      resolution of 1 cm allows for separation of different types of finger movement by using the
      high-frequency characteristics of the ECoG recording (70-100Hz), higher spatial resolutions
      (3mm) increases the ability to decode finger movements and more complicated hand movements,
      such as grasping of different objects. Ideal resolution is one of the several gaps in
      knowledge limit pursuing implementation of ECoG-based BCI along with uncertainty about the
      longevity of ECoG signals and human implementation of feedback directly to cortex through
      electrical stimulation.

      Specific Aim:

      Higher resolution arrays over subacute (1 week) time frame to allow for adaptation and BCI
      use of the higher resolution signals. An 8x8 array of 3mm resolution will be placed over
      sensorimotor cortex. Grasp synergies will be determined and mapped onto the electrodes to
      determine control channels for each synergy. Control of multiple synergies will move a
      simulated robotic hand to a visually cued target shape

        1. Hand synergies will be independently mapped onto the 3mm x 3mm (microarray) with at
           least one independent electrode for each of the first three synergies

        2. Using the signals from the microarray, participants will correctly move the robotic hand
           into one of 6 target postures with 50% accuracy.
observational model: Case-Only
time perspective: Prospective
measure: This is an observational study and the outcome is successful measurement of motor-related corticography signals.
time frame: 7-10 days
description: Successful measurement of motor-related corticography signals
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Jeffrey G Ojemann, MD
role: Principal Investigator
affiliation: University of Washington
last name: Amy m Anderson, BSN
phone: 206-744-9364
email: amya9@uw.edu
facility: 
status: Recruiting
contact: 
investigator: 
investigator: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: University of Washington
investigator full name: Jeffrey Ojemann
investigator title: Professor Neurological Surgery
mesh term: Drug Resistant Epilepsy
sharing ipd: No