Physiological-model-based neural network for modeling the metabolic–heart rate relationship during physical activities
This study confirms the validity of the PMB-NN framework using precise metabolic inputs. This foundational validation enables future integration with wearable-based V̇O<sub>2</sub> estimation systems, ultimately paving the way for personalized, real-time cardiac monitoring during daily life physical activities to enhance HF risk detection.
Authors
- Libera Fresiello (ORCID: https://orcid.org/0000-0003-0972-8340)
- Dirk Wilhelm Donker (ORCID: https://orcid.org/0000-0001-6496-2768)
- Petrus H. Veltink (ORCID: https://orcid.org/0000-0002-1796-9999)
- Ying Wang (ORCID: https://orcid.org/0000-0001-5172-4736)
- Yaowen Zhang (ORCID: https://orcid.org/0000-0003-4218-5771)
Institutions
- University of Twente (NL)
Publication Details
- Journal
- Computer Methods and Programs in Biomedicine
- Published
- 2026-01-09
- DOI
- https://doi.org/10.1016/j.cmpb.2026.109240
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- China Scholarship Council