<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/NCT04462913</url>
  </required_header>
  <id_info>
    <org_study_id>OR001</org_study_id>
    <nct_id>NCT04462913</nct_id>
  </id_info>
  <brief_title>Biometric Recognition and Rehabilitation Assessment of Lower Extremity Sports Injury Based on Gait Touch Information</brief_title>
  <official_title>Biometric Recognition and Rehabilitation Assessment of Lower Extremity Sports Injury Based on Gait Touch Information</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Peking University Third Hospital</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Peking University Third Hospital</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>
      The current common clinical methods cannot truly reflect the biomechanical status of the knee&#xD;
      joint. Based on the foot-knee coupling mechanism, the simple and practical dynamic gait touch&#xD;
      information provided by the 3D force platform are closely related to the knee biomechanics.&#xD;
      The purpose of this study is to investigate the disease feature recognition, computer-aided&#xD;
      diagnosis and rehabilitation assessment based on the gait touch information related to lower&#xD;
      limb injuries.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Background:&#xD;
&#xD;
      The current common clinical methods cannot truly reflect the biomechanical status of the knee&#xD;
      joint. The three-dimensional gait analysis is the gold standard, but it is difficult to apply&#xD;
      clinically. There is an urgent need for a clinically practical method to quantitatively&#xD;
      evaluate the biomechanics of the knee joint under dynamic weight bearing.&#xD;
&#xD;
      Methods:&#xD;
&#xD;
      50 healthy volunteers, 450 sports injuries patients (including hip, knee, and ankle joint&#xD;
      diseases) and 50 patients with degenerative osteoarthritis were recruited.&#xD;
&#xD;
      55 passive reflective markers were placed bilaterally on the body. Lower extremity kinematics&#xD;
      and dynamic plantar pressure during walking, jogging were collected.&#xD;
&#xD;
      Outcome evaluation indicators and statistical methods: The following indicators use repeated&#xD;
      measurement two-factor analysis of variance: the left and right sides, different&#xD;
      rehabilitation times are used as repeated measurement variables, to analyze the biomechanical&#xD;
      changes of the lower limb joint biomechanics and gait touch information. A variety of machine&#xD;
      learning methods (such as PCA, SVM, CNN, etc.) are used to analyze, and select the&#xD;
      appropriate algorithm and parameters according to the learning effect. Finally, this study&#xD;
      will establish a machine learning models for computer-aided diagnosis, treatment, and&#xD;
      rehabilitation assessment.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">July 28, 2017</start_date>
  <completion_date type="Anticipated">December 30, 2022</completion_date>
  <primary_completion_date type="Anticipated">December 1, 2022</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Control</observational_model>
    <time_perspective>Cross-Sectional</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>walking speed</measure>
    <time_frame>On the day of enrollment.</time_frame>
    <description>Three-dimensional gait analysis system and plantar pressure were used during walking.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>ground reaction force</measure>
    <time_frame>On the day of enrollment.</time_frame>
    <description>Three-dimensional gait analysis system and plantar pressure were used during walking.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>knee flexion angle</measure>
    <time_frame>On the day of enrollment.</time_frame>
    <description>Three-dimensional gait analysis system and plantar pressure were used during walking.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>the moment of knee extension in the gait cycle</measure>
    <time_frame>On the day of enrollment.</time_frame>
    <description>Three-dimensional gait analysis system and plantar pressure were used during walking.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>The International Knee Documentation Committee (IKDC) score</measure>
    <time_frame>On the day of enrollment.</time_frame>
    <description>The International Knee Documentation Committee (IKDC) score was used to evaluate the knee health.The patients completed score by themselves. The lowest score is 0 and the highest score is 100.</description>
  </secondary_outcome>
  <number_of_groups>3</number_of_groups>
  <enrollment type="Anticipated">550</enrollment>
  <condition>Sport Injury</condition>
  <condition>Osteoarthritis, Knee</condition>
  <arm_group>
    <arm_group_label>Healthy control</arm_group_label>
    <description>According to the previous clinical diagnosis, volunteers who has never suffered the lower extremity sports injuries.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Patients with sports injuries</arm_group_label>
    <description>According to the previous clinical diagnosis, patients who has suffered the sports injuries(including hip, knee, and ankle joint diseases).</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Patients with degenerative osteoarthritis</arm_group_label>
    <description>According to the previous clinical diagnosis, patients who has suffered the degenerative osteoarthritis.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>no intervention</intervention_name>
    <description>This is an observation study, with no intervention</description>
    <arm_group_label>Healthy control</arm_group_label>
    <arm_group_label>Patients with degenerative osteoarthritis</arm_group_label>
    <arm_group_label>Patients with sports injuries</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Inclusion: one healthy control group: healthy volunteers; and patients with a certain&#xD;
        sports injury (soft tissue injury or degenerative osteoarthritis) of a joint of the lower&#xD;
        limb (hip or knee or ankle or foot).&#xD;
&#xD;
        Exclusion: Cognitive impairment or other injuries affecting movement performance.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  patients with a certain sports injury (soft tissue injury or degenerative&#xD;
             osteoarthritis) of a joint of the lower limb (hip or knee or ankle or foot).&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Cognitive impairment&#xD;
&#xD;
          -  other injuries affecting movement performance.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>N/A</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Hongshi Huang, Doctor</last_name>
    <role>Study Chair</role>
    <affiliation>Peking University Third Hospital</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Hongshi Huang, Doctor</last_name>
    <phone>+8613910093298</phone>
    <email>huanghs@bjmu.edu.cn</email>
  </overall_contact>
  <location>
    <facility>
      <name>Peking University Third Hospital</name>
      <address>
        <city>Beijing</city>
        <zip>100191</zip>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Hongshi Huang, Doctor</last_name>
      <phone>+8613910093298</phone>
      <email>huanghs@bjmu.edu.cn</email>
    </contact>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <verification_date>June 2020</verification_date>
  <study_first_submitted>June 29, 2020</study_first_submitted>
  <study_first_submitted_qc>July 6, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 8, 2020</study_first_posted>
  <last_update_submitted>July 6, 2020</last_update_submitted>
  <last_update_submitted_qc>July 6, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">July 8, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>sports injury</keyword>
  <keyword>gait touch information</keyword>
  <keyword>machine learning</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Osteoarthritis, Knee</mesh_term>
    <mesh_term>Wounds and Injuries</mesh_term>
    <mesh_term>Athletic Injuries</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/NCT04462913
org study id: OR001
nct id: NCT04462913
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The current common clinical methods cannot truly reflect the biomechanical status of the knee
      joint. Based on the foot-knee coupling mechanism, the simple and practical dynamic gait touch
      information provided by the 3D force platform are closely related to the knee biomechanics.
      The purpose of this study is to investigate the disease feature recognition, computer-aided
      diagnosis and rehabilitation assessment based on the gait touch information related to lower
      limb injuries.
Background:

      The current common clinical methods cannot truly reflect the biomechanical status of the knee
      joint. The three-dimensional gait analysis is the gold standard, but it is difficult to apply
      clinically. There is an urgent need for a clinically practical method to quantitatively
      evaluate the biomechanics of the knee joint under dynamic weight bearing.

      Methods:

      50 healthy volunteers, 450 sports injuries patients (including hip, knee, and ankle joint
      diseases) and 50 patients with degenerative osteoarthritis were recruited.

      55 passive reflective markers were placed bilaterally on the body. Lower extremity kinematics
      and dynamic plantar pressure during walking, jogging were collected.

      Outcome evaluation indicators and statistical methods: The following indicators use repeated
      measurement two-factor analysis of variance: the left and right sides, different
      rehabilitation times are used as repeated measurement variables, to analyze the biomechanical
      changes of the lower limb joint biomechanics and gait touch information. A variety of machine
      learning methods (such as PCA, SVM, CNN, etc.) are used to analyze, and select the
      appropriate algorithm and parameters according to the learning effect. Finally, this study
      will establish a machine learning models for computer-aided diagnosis, treatment, and
      rehabilitation assessment.
observational model: Case-Control
time perspective: Cross-Sectional
measure: walking speed
time frame: On the day of enrollment.
description: Three-dimensional gait analysis system and plantar pressure were used during walking.
measure: ground reaction force
time frame: On the day of enrollment.
description: Three-dimensional gait analysis system and plantar pressure were used during walking.
measure: knee flexion angle
time frame: On the day of enrollment.
description: Three-dimensional gait analysis system and plantar pressure were used during walking.
measure: the moment of knee extension in the gait cycle
time frame: On the day of enrollment.
description: Three-dimensional gait analysis system and plantar pressure were used during walking.
measure: The International Knee Documentation Committee (IKDC) score
time frame: On the day of enrollment.
description: The International Knee Documentation Committee (IKDC) score was used to evaluate the knee health.The patients completed score by themselves. The lowest score is 0 and the highest score is 100.
arm group label: Healthy control
description: According to the previous clinical diagnosis, volunteers who has never suffered the lower extremity sports injuries.
arm group label: Patients with sports injuries
description: According to the previous clinical diagnosis, patients who has suffered the sports injuries(including hip, knee, and ankle joint diseases).
arm group label: Patients with degenerative osteoarthritis
description: According to the previous clinical diagnosis, patients who has suffered the degenerative osteoarthritis.
intervention type: Other
intervention name: no intervention
description: This is an observation study, with no intervention
arm group label: Healthy control
arm group label: Patients with degenerative osteoarthritis
arm group label: Patients with sports injuries
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: N/A
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: Hongshi Huang, Doctor
role: Study Chair
affiliation: Peking University Third Hospital
last name: Hongshi Huang, Doctor
phone: +8613910093298
email: huanghs@bjmu.edu.cn
facility: 
status: Recruiting
contact: 
country: China
responsible party type: Sponsor
mesh term: Osteoarthritis, Knee
mesh term: Wounds and Injuries
mesh term: Athletic Injuries
sharing ipd: No