Name
Abstract | ||
|---|---|---|
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 fuse... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1049/iet-cvi.2017.0112 | IET Computer Vision |
Keywords | Field | DocType |
accelerometers,biomedical engineering,calorimetry,computer vision,image sensors,medical image processing,sensor fusion,table lookup | Inertial frame of reference,Computer vision,Lookup table,Accelerometer,Wearable computer,Energy expenditure,Ground truth,Inertial measurement unit,Artificial intelligence,Fuse (electrical),Mathematics | Journal |
Volume | Issue | ISSN |
12 | 1 | 1751-9632 |
Citations | PageRank | References |
0 | 0.34 | 30 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lili Tao | 1 | 109 | 8.69 |
| Tilo Burghardt | 2 | 55 | 9.22 |
| Majid Mirmehdi | 3 | 955 | 96.94 |
| Dima Damen | 4 | 225 | 31.54 |
| Ashley Cooper | 5 | 2 | 0.71 |
| massimo camplani | 6 | 286 | 18.08 |
| Sion L. Hannuna | 7 | 69 | 10.37 |
| Adeline Paiement | 8 | 61 | 7.88 |
| Ian Craddock | 9 | 137 | 15.93 |