Leg edema quantification for heart failure patients via 3D imaging
Open accessAbstract
Heart failure is a common cardiac disease in elderly patients. After discharge, approximately 50% of all patients are readmitted to a hospital within six months. Recent studies show that home monitoring of heart failure patients can reduce the number of readmissions. Still, a large number of false positive alarms as well as underdiagnoses in other cases require more accurate alarm generation algorithms. New low-cost sensors for leg edema detection could be the missing link to help home monitoring to its breakthrough. We evaluated a 3D camera-based measurement setup in order to geometrically detect and quantify leg edemas. 3D images of legs were taken and geometric parameters were extracted semi-automatically from the images. Intra-subject variability for five healthy subjects was evaluated. Thereafter, correlation of 3D parameters with body weight and leg circumference was assessed during a clinical study at the Medical University of Graz. Strong correlation was found in between both reference values and instep height, while correlation in between curvature of the lower leg and references was very low. We conclude that 3D imaging might be a useful and cost-effective extension of home monitoring for heart failure patients, though further (prospective) studies are needed.
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Newer optical scanners utilize non-contact depth sensing methods to create advanced 3D images for determining changes in leg shape, size, and consistency.
“Newer optical scanners utilize non‐contact depth sensing methods to create advanced 3D images for determining changes in leg shape, size, and consistency. 81”
From Prioritizing symptom management in the treatment of chronic heart failure (2020) · cites this paper as [81]
The State-of-the-Art section says optical 3D scanners use non-contact depth sensing, and the Measurement Setup describes extracting leg geometry from 3D images. The paper supports assessing changes in leg shape and size, but our copy does not describe using these images to determine leg consistency. (LLM, conf=0.88)
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- Authors
- Hayn, D., Fruhwald, F., Riedel, A., Falgenhauer, M., & Schreier, G.
- Affiliations
- AIT Austrian Institute of Technology GmbH (AT)
- Medical University of Graz (AT)
- Corresponding author
- Hayn, Dieter
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2013-08-14
- Volume
- 13
- Issue
- 8
- Pages
- 10584-10598
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC3812619
- OpenAlex
- W2046547922
- Cited by
- 10
- References
- 19
- Citations by year
- 2026: 2 · 2025: 2 · 2023: 1 · 2022: 1 · 2021: 2 · 2020: 1 · 2016: 1
- FWCI
- 0.23
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Failure Treatment and Management
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- heart failure, lower limb edema, edema quantification, 3D imaging, home monitoring, remote patient monitoring, 3D camera, geometric parameters, leg circumference, body weight, false positive alerts, hospital readmission, low-cost sensors
- MeSH terms
- Adult, Algorithms, Artificial Intelligence, Edema, Heart Failure, Humans, Image Interpretation, Computer-Assisted, Leg, Male, Sensitivity and Specificity, Reproducibility of Results, Imaging, Three-Dimensional
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