Comparative Evaluation of Gait Analysis in Older Adults Using Pose Estimation Algorithms and an Inertial Measurement Unit-based System: a Reliability Study
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- 入组人数
- 30
- 试验地点
- 1
- 主要终点
- Inertial Measurement Unit (IMU)-Based Gait Analysis Parameters-Gait Speed
研究概览
简要总结
-This observational study aims to compare gait analysis performed using pose estimation algorithms with inertial measurement unit (IMU)-based gait analysis in older adults. Additionally, it aims to determine the reliability of gait analysis using pose estimation algorithms in this population.
The main questions it aims to answer are:
- Are gait analyses using pose estimation algorithms consistent with those performed using an inertial measurement unit-based system in older adults?
- Are gait analyses using pose estimation algorithms reliable in older adults?
Participants will take part in two measurement sessions. In the first session, they will be evaluated for inclusion criteria and general health status, and will complete gait analysis using both G-Walk (BTS Bioengineering) IMU sensors and a standard video camera simultaneously. In the second session, scheduled 1-3 days later, participants will perform only the 4-meter walking test, which will be recorded by video for pose estimation analysis.
详细描述
The primary objective of this observational study is to compare spatio-temporal gait parameters obtained from 2D pose estimation algorithms with those measured by inertial measurement units (IMUs) in older adults. A secondary aim is to evaluate the test-retest reliability of pose estimation-based gait analysis within this population.
Study Type and Sample Size This is an observational study. Based on clinical guidelines and recent instrumental research comparing validity and measurement methods in the literature, the sample size is determined to be at least 30 participants. Volunteers meeting the inclusion criteria will be recruited from patient relatives visiting the Faculty of Physical Therapy and Rehabilitation at Dokuz Eylul University for treatment.
Data Source and Collection No external data sources will be used. Assessments will be conducted via on-site visits. Any incomplete assessment will be considered as missing data. All collected data will be anonymized and stored on a password-protected institutional server. Access will be restricted to authorized research personnel.
Procedure After collecting sociodemographic data, medical history, and past medical records, participants will be screened using the Mini-Mental State Examination (MMSE) and the Timed Up and Go (TUG) test to determine eligibility. For the TUG test, participants will be asked to stand up from an armchair with armrests, walk a distance of 3 meters at a normal pace, turn around, return, and sit down. The time taken will be recorded in seconds. The TUG and MMSE test will be used to screen for basic mobility and functional balance, and to ensure that participants have sufficient physical and mental ability to complete gait trials safely.
In the primary assessment, all participants will undergo a simultaneous 4-meter walk test recorded using both G-Walk (BTS Bioengineering) IMU sensors and a standard video camera. The videos collected simultaneously with the G-Walk measurements will be processed with pose estimation algorithms for gait analysis to extract spatio-temporal gait parameters. To assess test-retest reliability of the pose estimation-based gait analysis (YOLO V.11-Pose Estimation), the same 4-meter walking test using only video recording will be repeated 1 to 3 days later in a subset of participants. Missing data will be documented and addressed accordingly.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 60 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Ability to walk independently
- •Mini-Mental State Examination (MMSE) score ≤ 23/30
排除标准
- •Inability to walk independently for more than 20 meters without assistive devices
- •Inability to understand or comply with test instructions
- •Lack of consent to participate
- •Presence of severe neurological, musculoskeletal, cardiac, or psychological disorders
结局指标
主要结局
Inertial Measurement Unit (IMU)-Based Gait Analysis Parameters-Gait Speed
时间窗: Baseline
Gait analysis will be performed using the BTS G-WALK device, a validated and reliable inertial measurement unit (IMU)-based system. The device will be securely attached at the level of the S1 vertebra using a belt. Start and end points will be marked on the floor, and participants will be asked to walk a distance of 4 meters. The system will measure walking speed as meters/second.
Inertial Measurement Unit (IMU)-Based Gait Analysis Parameters-Cadance
时间窗: Baseline
Gait analysis will be performed using the BTS G-WALK device, a validated and reliable inertial measurement unit (IMU)-based system. The device will be securely attached at the level of the S1 vertebra using a belt. Start and end points will be marked on the floor, and participants will be asked to walk a distance of 4 meters. The system will measure cadence as steps/minute.
Inertial Measurement Unit (IMU)-Based Gait Analysis Parameters-Step Length
时间窗: Baseline
Gait analysis will be performed using the BTS G-WALK device, a validated and reliable inertial measurement unit (IMU)-based system. The device will be securely attached at the level of the S1 vertebra using a belt. Start and end points will be marked on the floor, and participants will be asked to walk a distance of 4 meters. The system will measure step length as meters.
Inertial Measurement Unit (IMU)-Based Gait Analysis Parameters-Step Duration
时间窗: Baseline
Gait analysis will be performed using the BTS G-WALK device, a validated and reliable inertial measurement unit (IMU)-based system. The device will be securely attached at the level of the S1 vertebra using a belt. Start and end points will be marked on the floor, and participants will be asked to walk a distance of 4 meters. The system will measure step duration as seconds.
Inertial Measurement Unit (IMU)-Based Gait Analysis Parameters-Stance Time
时间窗: Baseline
Gait analysis will be performed using the BTS G-WALK device, a validated and reliable inertial measurement unit (IMU)-based system. The device will be securely attached at the level of the S1 vertebra using a belt. Start and end points will be marked on the floor, and participants will be asked to walk a distance of 4 meters. Stance time will be measured by the system and expressed as a percentage of the gait cycle (%).
Inertial Measurement Unit (IMU)-Based Gait Analysis Parameters-Swing Time
时间窗: Baseline
Gait analysis will be performed using the BTS G-WALK device, a validated and reliable inertial measurement unit (IMU)-based system. The device will be securely attached at the level of the S1 vertebra using a belt. Start and end points will be marked on the floor, and participants will be asked to walk a distance of 4 meters. Swing time will be measured by the system and expressed as a percentage of the gait cycle (%).
Inertial Measurement Unit (IMU)-Based Gait Analysis Parameters-Double Support Time
时间窗: Baseline
Gait analysis will be performed using the BTS G-WALK device, a validated and reliable inertial measurement unit (IMU)-based system. The device will be securely attached at the level of the S1 vertebra using a belt. Start and end points will be marked on the floor, and participants will be asked to walk a distance of 4 meters. Double support time will be measured by the system and expressed as a percentage of the gait cycle (%).
Inertial Measurement Unit (IMU)-Based Gait Analysis Parameters-Single Support Time
时间窗: Baseline
Gait analysis will be performed using the BTS G-WALK device, a validated and reliable inertial measurement unit (IMU)-based system. The device will be securely attached at the level of the S1 vertebra using a belt. Start and end points will be marked on the floor, and participants will be asked to walk a distance of 4 meters. Single support time will be measured by the system and expressed as a percentage of the gait cycle (%).
Gait Analysis Using Pose Estimation Algorithms-Gait Speed
时间窗: Baseline (first session) and 1-3 days after the baseline (second session)
Video recordings captured simultaneously with the inertial measurement unit (IMU)-based gait analysis system will be processed using a pose estimation algorithm. To ensure temporal alignment with the BTS G-WALK system, the videos will be trimmed and synchronized accordingly. The YOLO 11X-Pose algorithm version 0.25 with a threshold score will be employed for pose estimation. This algorithm dynamically tracks 17 key joint points on the body diagram during gait to extract dynamic gait parameters. To allow valid comparison with the IMU-based system, the algorithm will derive gait speed as meters/second.
Gait Analysis Using Pose Estimation Algorithms-Cadance
时间窗: Baseline (first session) and 1-3 days after the baseline (second session)
Video recordings captured simultaneously with the inertial measurement unit (IMU)-based gait analysis system will be processed using a pose estimation algorithm. To ensure temporal alignment with the BTS G-WALK system, the videos will be trimmed and synchronized accordingly. The YOLO 11X-Pose algorithm version 0.25 with a threshold score will be employed for pose estimation. This algorithm dynamically tracks 17 key joint points on the body diagram during gait to extract dynamic gait parameters. To allow valid comparison with the IMU-based system, the algorithm will derive the cadence as steps/minute.
Gait Analysis Using Pose Estimation Algorithms-Step Length
时间窗: Baseline (first session) and 1-3 days after the baseline (second session)
Video recordings captured simultaneously with the inertial measurement unit (IMU)-based gait analysis system will be processed using a pose estimation algorithm. To ensure temporal alignment with the BTS G-WALK system, the videos will be trimmed and synchronized accordingly. The YOLO 11X-Pose algorithm version 0.25 with a threshold score will be employed for pose estimation. This algorithm dynamically tracks 17 key joint points on the body diagram during gait to extract dynamic gait parameters. To allow valid comparison with the IMU-based system, the algorithm will derive step length as meters.
Gait Analysis Using Pose Estimation Algorithms-Step Duration
时间窗: Baseline (first session) and 1-3 days after the baseline (second session)
Video recordings captured simultaneously with the inertial measurement unit (IMU)-based gait analysis system will be processed using a pose estimation algorithm. To ensure temporal alignment with the BTS G-WALK system, the videos will be trimmed and synchronized accordingly. The YOLO 11X-Pose algorithm version 0.25 with a threshold score will be employed for pose estimation. This algorithm dynamically tracks 17 key joint points on the body diagram during gait to extract dynamic gait parameters. To allow valid comparison with the IMU-based system, the algorithm will derive the step duration as seconds.
Gait Analysis Using Pose Estimation Algorithms-Stance Time
时间窗: Baseline (first session) and 1-3 days after the baseline (second session)
Video recordings captured simultaneously with the inertial measurement unit (IMU)-based gait analysis system will be processed using a pose estimation algorithm. To ensure temporal alignment with the BTS G-WALK system, the videos will be trimmed and synchronized accordingly. The YOLO 11X-Pose algorithm version 0.25 with a threshold score will be employed for pose estimation. This algorithm dynamically tracks 17 key joint points on the body diagram during gait to extract dynamic gait parameters. To enable valid comparisons with the IMU-based system, the algorithm will calculate stance time and express it as a percentage of the gait cycle (%).
Gait Analysis Using Pose Estimation Algorithms-Swing Time
时间窗: Baseline (first session) and 1-3 days after the baseline (second session)
Video recordings captured simultaneously with the inertial measurement unit (IMU)-based gait analysis system will be processed using a pose estimation algorithm. To ensure temporal alignment with the BTS G-WALK system, the videos will be trimmed and synchronized accordingly. The YOLO 11X-Pose algorithm version 0.25 with a threshold score will be employed for pose estimation. This algorithm dynamically tracks 17 key joint points on the body diagram during gait to extract dynamic gait parameters. To enable valid comparisons with the IMU-based system, the algorithm will calculate swing time and express it as a percentage of the gait cycle (%).
Gait Analysis Using Pose Estimation Algorithms-Double Support Time
时间窗: Baseline (first session) and 1-3 days after the baseline (second session)
Video recordings captured simultaneously with the inertial measurement unit (IMU)-based gait analysis system will be processed using a pose estimation algorithm. To ensure temporal alignment with the BTS G-WALK system, the videos will be trimmed and synchronized accordingly. The YOLO 11X-Pose algorithm version 0.25 with a threshold score will be employed for pose estimation. This algorithm dynamically tracks 17 key joint points on the body diagram during gait to extract dynamic gait parameters. To enable valid comparisons with the IMU-based system, the algorithm will calculate double support time and express it as a percentage of the gait cycle (%).
Gait Analysis Using Pose Estimation Algorithms-Single Support Time
时间窗: Baseline (first session) and 1-3 days after the baseline (second session)
Video recordings captured simultaneously with the inertial measurement unit (IMU)-based gait analysis system will be processed using a pose estimation algorithm. To ensure temporal alignment with the BTS G-WALK system, the videos will be trimmed and synchronized accordingly. The YOLO 11X-Pose algorithm version 0.25 with a threshold score will be employed for pose estimation. This algorithm dynamically tracks 17 key joint points on the body diagram during gait to extract dynamic gait parameters. To enable valid comparisons with the IMU-based system, the algorithm will calculate single support time and express it as a percentage of the gait cycle (%).
次要结局
未报告次要终点
研究者
Gamze Yalcinkaya Colak
Assistant Professor
Bozok University