Skip to main content

Research Repository

Advanced Search

Energy expenditure estimation using visual and inertial sensors

Burghardt, Tilo; Mirmehdi, Majid; Damen, Dima; Cooper, Ashley; Camplani, Massimo; Hannuna, Sion; Paiement, Adeline; Craddock, Ian; Tao, Lili

Energy expenditure estimation using visual and inertial sensors Thumbnail


Authors

Tilo Burghardt

Majid Mirmehdi

Dima Damen

Ashley Cooper

Massimo Camplani

Sion Hannuna

Adeline Paiement

Ian Craddock

Lili Tao



Abstract

© The Institution of Engineering and Technology 2017. Deriving a person's energy expenditure accurately forms the foundation for tracking physical activity levels across many health and lifestyle monitoring tasks. In this study, the authors present a method for estimating calorific expenditure from combined visual and accelerometer sensors by way of an RGB-Depth camera and a wearable inertial sensor. The proposed individual-independent framework fuses information from both modalities which leads to improved estimates beyond the accuracy of single modality and manual metabolic equivalents of task (MET) lookup table based methods. For evaluation, the authors introduce a new dataset called SPHERE_RGBD + Inertial_calorie, for which visual and inertial data are simultaneously obtained with indirect calorimetry ground truth measurements based on gas exchange. Experiments show that the fusion of visual and inertial data reduces the estimation error by 8 and 18% compared with the use of visual only and inertial sensor only, respectively, and by 33% compared with a MET-based approach. The authors conclude from their results that the proposed approach is suitable for home monitoring in a controlled environment.

Citation

Craddock, I., Paiement, A., Hannuna, S., Camplani, M., Cooper, A., Damen, D., …Tao, L. (2018). Energy expenditure estimation using visual and inertial sensors. IET Computer Vision, 12(1), 36-47. https://doi.org/10.1049/iet-cvi.2017.0112

Journal Article Type Article
Acceptance Date Sep 23, 2017
Online Publication Date Sep 29, 2017
Publication Date Feb 1, 2018
Deposit Date Nov 7, 2017
Publicly Available Date Nov 7, 2017
Journal IET Computer Vision
Print ISSN 1751-9632
Electronic ISSN 1751-9640
Publisher Institution of Engineering and Technology (IET)
Peer Reviewed Peer Reviewed
Volume 12
Issue 1
Pages 36-47
DOI https://doi.org/10.1049/iet-cvi.2017.0112
Keywords computer vision, table lookup, calorimetry, medical image processing, accelerometers, image sensors, sensor fusion, biomedical engineering
Public URL https://uwe-repository.worktribe.com/output/860132
Publisher URL http://dx.doi.org/10.1049/iet-cvi.2017.0112
Related Public URLs http://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2017.0112

Files







Downloadable Citations