RespCam.AI - Remote monitoring of breathing patterns and automatic classification using artificial intelligence for early detection of a deterioration in the health status of patients
- Conditions
- respiratory disorders
- Registration Number
- DRKS00028601
- Lead Sponsor
- niversitätsklinikum der RWTH Aachen
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Enrolling by invitation
- Sex
- All
- Target Recruitment
- 300
Inclusion Criteria
Minimum Age, General Anesthesia, preoperatively enlightened
Exclusion Criteria
The surgical area is in the thoracic area, bandages in the thoracic area, patient is not lung-healthy (COPD GOLD 2-4, lung emphysema, other shortness of breath at rest, etc.)
Study & Design
- Study Type
- observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method (1) use of advanced an non-contact technologies to extract respiratory curves/patterns, (2) analyze or clinically assess them using AI-neural networks and expert systems, and (3) diagnose and possibly even predict specific respiratory disorders
- Secondary Outcome Measures
Name Time Method Analyze or clinically evaluate breathing curves recorded by the chest strap (1) using AI - neural networks and expert systems - and (2) diagnose and possibly even predict specific breathing disorders