<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/NCT03750097</url>
  </required_header>
  <id_info>
    <org_study_id>ms-bewegt-Validation</org_study_id>
    <nct_id>NCT03750097</nct_id>
  </id_info>
  <brief_title>Validation of a Smartwatch in Persons With Multiple Sclerosis</brief_title>
  <official_title>Validation of a Commercially Available Smartwatch for Step Detection in Persons With Multiple Sclerosis</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Erlangen-Nürnberg</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Neurological Rehabilitation Center Quellenhof</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>ZTM Bad Kissingen</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Erlangen-Nürnberg</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 study is designed to validate the accuracy of steps detected by a commercially available&#xD;
      smartwatch in persons with multiple sclerosis. Specifically, the investigators examine&#xD;
      whether a smartwatch can detect steps accurately during slow, comfortable and fast overground&#xD;
      walking. The total steps counted by the smartwatch will be compared to those counted by an&#xD;
      accelerometer commonly used in clinical studies and the actually walked steps.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system. It&#xD;
      is one of the most common neurological diseases in young adulthood. The main symptoms of MS&#xD;
      are gait and mobility impairments, which also determine the severity of the disease.&#xD;
      Currently, subjective clinical functional tests are commonly used to evaluate therapy&#xD;
      outcomes. Due to advancing mechanization, body-worn accelerometers have been established as a&#xD;
      potential instrument for the objective detection of mobility in clinical research. The&#xD;
      accuracy of these devices for determining the mobility is therefore essential. However,&#xD;
      current studies, especially in people with altered gait, show large deviations in step&#xD;
      detection accuracy.&#xD;
&#xD;
      In the present study we want to investigate: i) whether a commercially available smartwatch&#xD;
      (Polar M600) counts steps in persons with multiple sclerosis (pwMS) accurately and ii)&#xD;
      whether it counts steps as accurately as an accelerometer commonly used in clinical research&#xD;
      (ActiGraph wGT3X-BT). In addition, the accuracy of the step detection by the algorithms of&#xD;
      the manufacturer of the two devices (Polar M600 and ActiGraph wGT3X-BT) will be compared with&#xD;
      an own-developed algorithm.&#xD;
&#xD;
      For this purpose, 63 pwMS with low to severe functional restriction (EDSS: 0 - 6.5) will&#xD;
      participate in this validation study. The validation protocol consists of three walking tests&#xD;
      with different walking velocities. During these three conditions the participants will wear&#xD;
      the Polar M600 on the wrist and the ActiGraph wGT3X-BT with a belt over the hip. In the first&#xD;
      walking test, the subjects will complete 250 steps with comfortable walking velocity (CWV).&#xD;
      After a sufficient break, the participants will be randomly assigned to either a fast walking&#xD;
      velocity condition (FWV: CWV + 20%) followed by a sufficient period of rest and a slow&#xD;
      walking velocity condition (SWV: CWV - 20%) or vice versa. Each of the walking tests with&#xD;
      modified walking velocity also consists of 250 steps. To analyze the accuracy of step&#xD;
      detection, the measured steps of the devices will be compared with the actually walked 250&#xD;
      steps.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">May 1, 2018</start_date>
  <completion_date type="Actual">January 31, 2019</completion_date>
  <primary_completion_date type="Actual">December 15, 2018</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <primary_purpose>Other</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Step detection during comfortable walking</measure>
    <time_frame>Following the comfortable walking velocity protocol, an average of 2 minutes</time_frame>
    <description>Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during comfortable walking for 250 steps.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Step detection during slow walking</measure>
    <time_frame>Following the slow walking velocity protocol, an average of 2 minutes</time_frame>
    <description>Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during slow walking for 250 steps.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Step detection during fast walking</measure>
    <time_frame>Following the fast walking velocity protocol, an average of 2 minutes</time_frame>
    <description>Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during fast walking for 250 steps.</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">58</enrollment>
  <condition>Multiple Sclerosis</condition>
  <arm_group>
    <arm_group_label>Walking protocol</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Walking for 250 steps with comfortable walking velocity (CWV), slow walking velocity (SWV: CWV - 20%) and fast walking velocity (FWV: CWV + 20%) with sufficient rest between conditions.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Comfortable walking velocity (CWV)</intervention_name>
    <description>Walking for 250 Steps with self-selected comfortable walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT)</description>
    <arm_group_label>Walking protocol</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Slow walking velocity (SWV: CWV - 20%)</intervention_name>
    <description>Walking for 250 Steps with slow walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT). Slow walking consists of walking with 20% slower than the self-selected comfortable walking velocity by following a researcher who controls the walking velocity with a measuring wheel.</description>
    <arm_group_label>Walking protocol</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Fast walking velocity (FWV: CWV + 20%)</intervention_name>
    <description>Walking for 250 Steps with fast walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT). Fast walking consists of walking with 20% faster than the self-selected comfortable walking velocity by following a researcher who controls the walking velocity with a measuring wheel.</description>
    <arm_group_label>Walking protocol</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Multiple Sclerosis with Expanded Disability Status Scale between 0 - 6.5&#xD;
&#xD;
          -  Ability to walk 250 steps with or without an assistive device&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Clinically relevant cardiovascular or orthopaedic disease&#xD;
&#xD;
          -  Severe polyneuropathy&#xD;
&#xD;
          -  Cognitive impairment&#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>Klaus Pfeifer, Prof. Dr.</last_name>
    <role>Principal Investigator</role>
    <affiliation>Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Sport Science and Sport</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Peter Flachenecker, Prof. Dr. med.</last_name>
    <role>Principal Investigator</role>
    <affiliation>Neurological Rehabilitation Center Quellenhof</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Sport Science and Sport, Gebbertstr. 123b</name>
      <address>
        <city>Erlangen</city>
        <zip>91058</zip>
        <country>Germany</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Germany</country>
  </location_countries>
  <link>
    <url>http://www.sport.fau.de/ms-bewegt/</url>
    <description>Project webpage</description>
  </link>
  <verification_date>April 2019</verification_date>
  <study_first_submitted>July 30, 2018</study_first_submitted>
  <study_first_submitted_qc>November 20, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">November 21, 2018</study_first_posted>
  <last_update_submitted>April 11, 2019</last_update_submitted>
  <last_update_submitted_qc>April 11, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">April 12, 2019</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Erlangen-Nürnberg</investigator_affiliation>
    <investigator_full_name>Prof. Dr. Klaus Pfeifer</investigator_full_name>
    <investigator_title>Prof. Dr.</investigator_title>
  </responsible_party>
  <keyword>Multiple Sclerosis</keyword>
  <keyword>Motion sensors</keyword>
  <keyword>Smartwatch</keyword>
  <keyword>Steps</keyword>
  <keyword>Walking</keyword>
  <keyword>Validation</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Multiple Sclerosis</mesh_term>
    <mesh_term>Sclerosis</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Undecided</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/NCT03750097
org study id: ms-bewegt-Validation
nct id: NCT03750097
lead sponsor: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The study is designed to validate the accuracy of steps detected by a commercially available
      smartwatch in persons with multiple sclerosis. Specifically, the investigators examine
      whether a smartwatch can detect steps accurately during slow, comfortable and fast overground
      walking. The total steps counted by the smartwatch will be compared to those counted by an
      accelerometer commonly used in clinical studies and the actually walked steps.
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system. It
      is one of the most common neurological diseases in young adulthood. The main symptoms of MS
      are gait and mobility impairments, which also determine the severity of the disease.
      Currently, subjective clinical functional tests are commonly used to evaluate therapy
      outcomes. Due to advancing mechanization, body-worn accelerometers have been established as a
      potential instrument for the objective detection of mobility in clinical research. The
      accuracy of these devices for determining the mobility is therefore essential. However,
      current studies, especially in people with altered gait, show large deviations in step
      detection accuracy.

      In the present study we want to investigate: i) whether a commercially available smartwatch
      (Polar M600) counts steps in persons with multiple sclerosis (pwMS) accurately and ii)
      whether it counts steps as accurately as an accelerometer commonly used in clinical research
      (ActiGraph wGT3X-BT). In addition, the accuracy of the step detection by the algorithms of
      the manufacturer of the two devices (Polar M600 and ActiGraph wGT3X-BT) will be compared with
      an own-developed algorithm.

      For this purpose, 63 pwMS with low to severe functional restriction (EDSS: 0 - 6.5) will
      participate in this validation study. The validation protocol consists of three walking tests
      with different walking velocities. During these three conditions the participants will wear
      the Polar M600 on the wrist and the ActiGraph wGT3X-BT with a belt over the hip. In the first
      walking test, the subjects will complete 250 steps with comfortable walking velocity (CWV).
      After a sufficient break, the participants will be randomly assigned to either a fast walking
      velocity condition (FWV: CWV + 20%) followed by a sufficient period of rest and a slow
      walking velocity condition (SWV: CWV - 20%) or vice versa. Each of the walking tests with
      modified walking velocity also consists of 250 steps. To analyze the accuracy of step
      detection, the measured steps of the devices will be compared with the actually walked 250
      steps.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Other
masking: None (Open Label)
measure: Step detection during comfortable walking
time frame: Following the comfortable walking velocity protocol, an average of 2 minutes
description: Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during comfortable walking for 250 steps.
measure: Step detection during slow walking
time frame: Following the slow walking velocity protocol, an average of 2 minutes
description: Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during slow walking for 250 steps.
measure: Step detection during fast walking
time frame: Following the fast walking velocity protocol, an average of 2 minutes
description: Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during fast walking for 250 steps.
arm group label: Walking protocol
arm group type: Experimental
description: Walking for 250 steps with comfortable walking velocity (CWV), slow walking velocity (SWV: CWV - 20%) and fast walking velocity (FWV: CWV + 20%) with sufficient rest between conditions.
intervention type: Behavioral
intervention name: Comfortable walking velocity (CWV)
description: Walking for 250 Steps with self-selected comfortable walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT)
arm group label: Walking protocol
intervention type: Behavioral
intervention name: Slow walking velocity (SWV: CWV - 20%)
description: Walking for 250 Steps with slow walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT). Slow walking consists of walking with 20% slower than the self-selected comfortable walking velocity by following a researcher who controls the walking velocity with a measuring wheel.
arm group label: Walking protocol
intervention type: Behavioral
intervention name: Fast walking velocity (FWV: CWV + 20%)
description: Walking for 250 Steps with fast walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT). Fast walking consists of walking with 20% faster than the self-selected comfortable walking velocity by following a researcher who controls the walking velocity with a measuring wheel.
arm group label: Walking protocol
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Klaus Pfeifer, Prof. Dr.
role: Principal Investigator
affiliation: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Sport Science and Sport
last name: Peter Flachenecker, Prof. Dr. med.
role: Principal Investigator
affiliation: Neurological Rehabilitation Center Quellenhof
facility: 
country: Germany
url: http://www.sport.fau.de/ms-bewegt/
description: Project webpage
responsible party type: Principal Investigator
investigator affiliation: University of Erlangen-Nürnberg
investigator full name: Prof. Dr. Klaus Pfeifer
investigator title: Prof. Dr.
mesh term: Multiple Sclerosis
mesh term: Sclerosis
sharing ipd: Undecided