Artificial Intelligence-Based Motion Analysis for Early Detection of COPD

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

56 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-08-01

Study Completion Date

2026-03-01

Brief Summary

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This study aims to develop a non-invasive and contact-free diagnostic system that uses artificial intelligence (AI) to detect Chronic Obstructive Pulmonary Disease (COPD) by analyzing walking patterns.

Participants in this study will include individuals with a diagnosis of COPD and healthy volunteers. All participants will undergo a 6-minute walk test (6MWT), during which their movements will be recorded using video. In addition, they will complete a breathing test (spirometry) and a short questionnaire about symptoms.

The recorded videos will be analyzed using an AI model based on motion tracking software. This model will evaluate walking-related parameters such as step count, step length, walking time, and total walking distance. The goal is to determine whether walking patterns can be used to detect COPD with high accuracy, especially in situations where traditional lung function tests may not be available or feasible.

This study is observational and does not involve any experimental drug or treatment. The results may help to create new diagnostic tools that are easy to use, safe, and accessible for early detection of COPD.

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Detailed Description

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Conditions

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Chronic Obstructive Pulmonary Disease (COPD)

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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COPD Group

Participants with a confirmed diagnosis of Chronic Obstructive Pulmonary Disease (COPD) based on spirometry.

Gait Video Recording and Analysis

Intervention Type OTHER

Participants undergo a 6-minute walk test (6MWT) while being recorded on video. The footage is later analyzed using artificial intelligence algorithms to assess gait parameters.

Control Group

Healthy volunteers with no history of pulmonary disease and normal spirometry results.

Gait Video Recording and Analysis

Intervention Type OTHER

Participants undergo a 6-minute walk test (6MWT) while being recorded on video. The footage is later analyzed using artificial intelligence algorithms to assess gait parameters.

Interventions

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Gait Video Recording and Analysis

Participants undergo a 6-minute walk test (6MWT) while being recorded on video. The footage is later analyzed using artificial intelligence algorithms to assess gait parameters.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Aged between 40 and 80 years
* Ability to provide informed consent
* For COPD group: Previously diagnosed with COPD based on GOLD criteria (FEV1/FVC \< 0.70)
* For control group: No history of pulmonary disease and normal spirometry results
* Physically able to perform the 6-minute walk test
* Willingness to participate in video recording during gait analysis

Exclusion Criteria

* Younger than 40 or older than 80 years
* Acute respiratory tract infection or other active infections
* Severe heart failure, advanced arrhythmias, or other serious cardiovascular conditions
* Physical disability preventing completion of the 6-minute walk test
* Neurological or orthopedic conditions causing major gait disturbance
* Inability to perform spirometry due to physical or cognitive limitations
* Pregnant or breastfeeding women Diagnosed with other serious pulmonary diseases (e.g., interstitial lung disease, active tuberculosis) Refusal to give informed consent or to be video recorded

Minimum Eligible Age

40 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes