6 papers
PM-EKF: A Physiological Model-Based Extended Kalman Filter for Daily-Life Physical Activity Energy Expenditure Estimation
Shuhao Que, Remco Poelarends, Valentina Breschi +1
Monitoring physical activity energy expenditure (PAEE) in daily life is essential for characterizing individual health and metabolic status. Although indirect calorimetry provides…
Synthetic Data Guided Feature Selection for Robust Activity Recognition in Older Adults
Shuhao Que, Dieuwke van Dartel, Ilse Heeringa +3
Physical activity during hip fracture rehabilitation is essential for mitigating long-term functional decline in geriatric patients. However, it is rarely quantified in clinical pr…
PMB-NN: Physiology-Centred Hybrid AI for Personalized Hemodynamic Monitoring from Photoplethysmography
Yaowen Zhang, Libera Fresiello, Peter H. Veltink +2
Continuous monitoring of blood pressure (BP) and hemodynamic parameters such as peripheral resistance (R) and arterial compliance (C) are critical for early vascular dysfunction de…
Accelerometry-based Energy Expenditure Estimation During Activities of Daily Living: A Comparison Among Different Accelerometer Compositions
Shuhao Que, Remco Poelarends, Peter Veltink +2
Physical activity energy expenditure (PAEE) can be measured from breath-by-breath respiratory data, which can serve as a reference. Alternatively, PAEE can be predicted from the bo…
A Physiological-Model-Based Neural Network Framework for Blood Pressure Estimation from Photoplethysmography Signals
Yaowen Zhang, Libera Fresiello, Peter H. Veltink +2
Continuous blood pressure (BP) estimation via photoplethysmography (PPG) remains a significant challenge, particularly in providing comprehensive cardiovascular insights for hypert…
Evaluating Multi-Sensor Placement and Neural Network Architectures for Physical Activity Level Classification
Bo Cui, Xiaowen Song, Tabak Monique +2
Accurate physical activity level (PAL) classification could be beneficial for osteoarthritis (OA) management. This study examines the impact of sensor placement and deep learning m…