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Mads Hashiba Jensen
Verified Contributor2 Publications in Hub
Research Bibliography
ID: non-exercise-estimation-of-peak-oxygen-uptake-in-patients-with-ischaemic-heart-disease-and-heart-failure-using-seismocardiography2025
Non-exercise estimation of peak oxygen uptake in patients with ischaemic heart disease and heart failure using seismocardiography
This study found that a new heart monitoring method using vibrations (SCG) was not accurate enough to estimate fitness levels or track improvements in heart patients after rehabilitation.
ID: determining-the-respiratory-state-from-a-seismocardiographic-signal--a-machine-learning-approach2018
Determining the Respiratory State From a Seismocardiographic Signal--A Machine Learning Approach
This study shows that chest vibrations from the heart (SCG signals) can predict breathing patterns using advanced machine learning, with neural networks being the most accurate method. This could help monitor breathing and heart health more easily and affordably.