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Clinical Trials/NCT04052282
NCT04052282
Completed
N/A

Test-retest Reliability and Validity of and a Novel Smartphone Application to Objectively Measure Physical Function in Healthy Individuals

Universidade Federal de Sao Carlos1 site in 1 country20 target enrollmentSeptember 3, 2019
ConditionsHealthy

Overview

Phase
N/A
Intervention
Not specified
Conditions
Healthy
Sponsor
Universidade Federal de Sao Carlos
Enrollment
20
Locations
1
Primary Endpoint
Numeric Rating Scale - TEST RETEST (clinical setting)
Status
Completed
Last Updated
4 years ago

Overview

Brief Summary

The overarching goal is to develop a mHealth App that can use smartphone embedded sensors to objectively collect physical function data in healthy individuals in the context of daily life.

Detailed Description

The goal is to develop a mHealth App using smartphone embedded sensors to objectively collect physical function data in healthy individuals in the context of daily life. The investigators will perform technical development of an internet-interactive App to collect, analyze and transfer the subjects' data. As a proof-of-concept, the mHealth App will execute algorithms that automate deployment of three well-established physical function tests. In a laboratory setting, it will be evaluated usability, acceptability and reliability of the mHealth App compared with traditional performance tests among focus groups. The investigators will then evaluate its usability and acceptability when used in the participants' home environments.

Registry
clinicaltrials.gov
Start Date
September 3, 2019
End Date
August 1, 2021
Last Updated
4 years ago
Study Type
Observational
Sex
All

Investigators

Sponsor
Universidade Federal de Sao Carlos
Responsible Party
Principal Investigator
Principal Investigator

Lucas Ogura Dantas

Co-Principal Investigator

Universidade Federal de Sao Carlos

Eligibility Criteria

Inclusion Criteria

  • Male or female subjects at least 50 years old with symptomatic knee osteoarthritis
  • English Speaker
  • Be able to walk 20 meters without an assistive device, such as a cane, walker or crutches.
  • Have an iPhone 6 or higher with internet connection.

Exclusion Criteria

  • Prior surgery on either knee within 6 months of enrollment
  • Received corticosteroid injection in the knee within 3 months of enrollment
  • Evidence or history of knee disease or trauma

Outcomes

Primary Outcomes

Numeric Rating Scale - TEST RETEST (clinical setting)

Time Frame: 7 days after day 1

A Numeric Rating Scale (NRS) will be applied to measure both knee pain. NRS is a well recognized tool to measure the intensity of pain that visually represents the intensity of pain that the individual believes to present. The scale will be displayed on the app and will have a range of 0 to 10, with 0 being the complete absence of pain and 10, the maximum intensity of pain reported by the individual.

The 20-meter Walk - DIURNAL CHANGE (home setting)

Time Frame: Day 1, day 3, and day 5 (within a week Mon, Wed, Fri)

At home, for the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a standing position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will automatically determine when the 20-meter distance is reached and will say to the patient to gradually stop, measuring the total time to complete the test. After the test is completed, the data will be automatically sent to the cloud system.

The 20-meter Walk - TEST RETEST (clinical setting)

Time Frame: 7 days after day 1

This test assesses gait speed and changes in patient's physical function over time. The clinician asks the patient to walk at a comfortable pace in a 20-meter unobstructed course and measures the time to perform the test. For the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a standing position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will automatically determine when the 20-meter distance is reached and will say to the patient to gradually stop, measuring the total time to complete the test. After the test is completed, the data will be automatically sent to the cloud system.

The 30 Seconds Sit to Stand - TEST RETEST (clinical setting)

Time Frame: 7 days after day 1

In the clinical setting, the clinician asks the patient to sit in the middle of the chair, with the back straight, feet apart resting on the floor and in line with the shoulders. The patient has to rise from a sitting to a standing position as many times as possible in 30 seconds. With the results of this test, it is possible to evaluate a wide variety of skill levels, with scores ranging from 0 (for those unable to complete one repetition) to more than 20 repetitions (for the most physically fit individuals). For the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a sitting position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will automatically count the total sit to stand repetitions within a 30 seconds period. After the test is completed, the data will be automatically sent to the cloud system.

The 30 Seconds Sit to Stand - DIURNAL CHANGE (home setting)

Time Frame: Day 1, day 3, and day 5 (within a week Mon, Wed, Fri)

At home, for the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a sitting position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will automatically count the total sit to stand repetitions within a 30 seconds period. After the test is completed, the data will be automatically sent to the cloud system.

Numeric Rating Scale - DIURNAL CHANGE (home setting)

Time Frame: Day 1, day 3, and day 5 (within a week Mon, Wed, Fri)

At home, a Numeric Rating Scale (NRS) will be applied to measure both knee pain. NRS is a well recognized tool to measure the intensity of pain that visually represents the intensity of pain that the individual believes to present. The scale will be displayed on the app and will have a range of 0 to 10, with 0 being the complete absence of pain and 10, the maximum intensity of pain reported by the individual.

The Get up and Go - TEST RETEST (clinical setting)

Time Frame: 7 days after day 1

In the clinical setting, the clinician asks the patient to stand up from a chair, walk 3 meters, turn around, return and sit back in the chair. The time on the test is used as a predictor of functional independence: below 20 seconds is considered normal and over 30 seconds as potentially indicative of increased risk for falls and functional dependence. For the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a sitting position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will pre-determine and tell the patient how many steps to take to achieve the distance of 3 meters. After the test is completed, the data will be automatically sent to the cloud system.

The Get up and Go - DIURNAL CHANGE (home setting)

Time Frame: Day 1, day 3, and day 5 (within a week Mon, Wed, Fri)

At home, for the automated test, the patient will wear a chest strap fixing the mobile phone over the sternum. On a sitting position, the patient will open the mHealth App and through the use of audible feedback, will receive the same test instructions as in the clinic. With the use of algorithms, the mHealth App will pre-determine and tell the patient how many steps to take to achieve the distance of 3 meters. After the test is completed, the data will be automatically sent to the cloud system.

Study Sites (1)

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