Chronic Pain of Left Foot (Finding) Clinical Trial
Official title:
Assessment of Reliability and Validity of the OneStep Smartphone Application for Gait Analysis During Treadmill Walking
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.
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. ;