Reliability and Validity of the OneStep Smartphone Application for Gait Analysis

NCT ID: NCT05009303

Last Updated: 2022-05-18

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 100 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2021-05-01
• Study Completion Date: 2022-09-30

Brief Summary

Expanding the availability of quantitative tools for gait quality assessment is essential to enable clinicians to analyze patient's gait, monitor gait changes, and modify the rehabilitation process, when gold-standard tools are not available. The OneStep technology is a smartphone application (app), that uses smartphone sensors to provide ongoing gait diagnostics. This study aims to further evaluate the analytical capability of the OneStep algorithm in recording and analyzing gait parameters and test its reliability and validity. The study will take place at Reuth Rehabilitation Hospital. All participants will be using the App and the C-Mill treadmill (Motek, Amsterdam, Netherlands) built-in gait analysis system, during two separate treadmill walks of up to 15 minutes. All walking sessions will be recorded with two cameras. Data obtained from participants will be collected and analyzed for gait parameters. The study sample will include 30 healthy volunteers and 70 patients.

Detailed Description

Background:

The current gold standard for gait analyses are laboratories equipped for three-dimensional gait analysis. However, a major drawback of these laboratories is their inability to examine gait in patients' own environment. Therefore, there is a need for an inexpensive, portable, easy-to-use, and reliable gait tracking method. Wearable devices and smartphones may provide a solution. The OneStep smartphone application (app) is one such technology. It can be downloaded to a smartphone, placed in the pants pocket, and once activated, can collect gait data while a subject is in motion. In an earlier study, the OneStep app has been used to collect data on patients with lower extremity disability or pain, during in-hospital physiotherapy sessions, self-exercises in the hospital or at home, and other daily activities, to assess patients' adherence to and compliance with the prescribed rehabilitation regimen.

Study Objectives:

The goal of this study is to expand the utilization of the OneStep app in gait parameters analysis by:

1. Collecting and analyzing new walking parameters: main parts of the foot bearing weight; walking base; identification of which part hits the ground first during the initial contact; ankle and knee range of motion; pelvic movement

2. Validating the OneStep app against standard gait measurement tools among both healthy volunteers and patients

3. Assessing the test-retest reliability of the OneStep app gait measurements.

Method:

The study sample will include a total of 100 participants: 30 healthy volunteers and 70 patients. Each participant will have two sessions using the treadmill for walks of up to 15 minutes, with the second walking session used for test-retest reliability assessment. Healthy volunteers will complete the second session on the same day as the first session after a 10-minute break. Patients will complete the second session within one week of the first. A check-in phase will be performed at the beginning of each session, during which the participants (specifically the patients) will be instructed to rest for up to 10 min, to ensure their performance on treadmill is not affected by prior physical activities.

During both sessions, participants will use the C-Mill treadmill (Motek, Amsterdam, Netherlands) and will be equipped with 2 smartphones placed on each hip. As some patients will not be able to keep on walking for 15 minutes, a minimal duration of the required walk was set at 2 minutes. Sessions will be recorded using two high resolution video cameras. The phones will be placed in a participant's front pants pockets; for those without pockets, two leg harnesses will be provided with space to hold the phones.

Data obtained from all participants will be collected and analyzed for gait parameters. Patients were instructed to walk at a comfortable gait speed. Healthy volunteers were given a specific walking protocol of 15 minutes each, which consisted of 14 selected gait types with different speeds and walking styles.

Conditions

Chronic Pain of Left Foot (Finding); Chronic Pain of Right Foot (Finding)

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Participants

Thirty healthy individuals and seventy patients suffering from chronic pain or disability in one or both of their lower extremities

OneStep Smartphone App and C-Mill Treadmill

Intervention Type: DEVICE

OneStep technology is a smartphone application that utilizes smartphone sensors to provide ongoing gait diagnostics. Each participant will have two sessions, during which, they will walk on a C-Mill smart treadmill for up to 15 minutes (with a minimum of 2 minutes), while carrying 2 smartphones and being recorded via two video cameras. The second walking session, conducted under similar conditions, will be used for test-retest reliability.

Interventions

OneStep Smartphone App and C-Mill Treadmill

OneStep technology is a smartphone application that utilizes smartphone sensors to provide ongoing gait diagnostics. Each participant will have two sessions, during which, they will walk on a C-Mill smart treadmill for up to 15 minutes (with a minimum of 2 minutes), while carrying 2 smartphones and being recorded via two video cameras. The second walking session, conducted under similar conditions, will be used for test-retest reliability.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

1. Men and women aged 18 to 65.

2. Able to walk independently or with assistance (human / walking aids).

3. Able to speak and read in Hebrew fluently.

4. Patients requiring lower limb rehabilitation course (inpatient/outpatient) due to lower limb disability or chronic pain

5. Ability to successfully complete a routine 6-minute walking test (as part of treatment)

6. Mini-Mental State Examination (MMSE) Score ≥ 24

Exclusion Criteria

1. Subjects requiring prosthetics or orthoses.

2. Subject unable to step on their foot.

3. Subject unfit to participate in the study according to the judgment of the principal investigator, including but not limited to:

3.1 Known pregnancy. 3.2 Existing cardio-pulmonary disease. 3.3 Balance impairment 3.4 visual disturbances (not rectified by glasses) 3.5 history of falls

4. As walking on the treadmill with a walking aid will not be allowed, patients unable to walk without a walking aid will be excluded (use of handrails during walking will be permitted).

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 65 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Reuth Rehabilitation Hospital

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Dana Gefen-Doron, MD

Role: PRINCIPAL_INVESTIGATOR

Reuth Rehabilitation Hospital

Locations

Reuth Rehabilitation Hospital

Tel Aviv, , Israel

Countries

Israel

Other Identifiers

0003-21-RRH

Identifier Type: -

Identifier Source: org_study_id