system based on deep learning, single-lead ecg sensor and physical activity via accelerometer data  (AliveCor Inc)

Journal: Scientific Reports

Article Title: Developing and comparing a new BMI inclusive energy expenditure algorithm on wrist-worn wearables

doi: 10.1038/s41598-025-99963-0

Figure Lengend Snippet: Devices used in the study: A wearable camera was used to provide visual confirmation of human behavior performed in the wild. We utilized the smartwatch tri-axial accelerometer and gyroscope to estimate energy expenditure using our proposed algorithm and compared it against multiple algorithms , , , , – using the hip-worn ActiGraph.

Article Snippet: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$K_m$$\end{document} motion estimates of accelerometer data segments are calculated by the Panasonic equation and aggregated based on the selected window size (Eq.).

Techniques: