Orientation-Based Food Image Capture for Head Mounted Egocentric Camera.

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ID: 93745
2019
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Ranked #93 of 127 articles by views in conference proceedings : annual international conference of the ieee engineering in medicine and biology society ieee engineering in medicine and biology society annual conference

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Abstract
Current head-mounted wearable sensors for monitoring of food intake operates by fusing multiple modalities such as inertial and image sensing. The image capture may be performed periodically, capturing a large number of irrelevant images, increasing power consumption and reducing the battery life. In this manuscript, we propose an efficient approach for food image capture, that captures the images only when the head tilt angle estimated from the accelerometer data matches that during ingestion of food. The method was developed and validated using data from 15 volunteers consuming unrestricted meals in a free-living environment between 12.5 to 18.5 hours. The tilt angle of the head was computed using 3D accelerometer data. A classifier for image capture was developed using a curve fitting approach on the tilt angles of the head. The proposed method achieved a sensitivity of 0.97 and specificity of 0.47 in predicting capture of food images, thus potentially improving the battery life of the wearable device.
Reference Key
hassan2019orientationbasedconference Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hassan, M A;Sazonov, E;
Journal conference proceedings : annual international conference of the ieee engineering in medicine and biology society ieee engineering in medicine and biology society annual conference
Year 2019
DOI
10.1109/EMBC.2019.8857078
URL
Keywords
bluetooth low energy (ble) lora ble long range ieee 802.11ah isa100.11a industrial internet of things (iiot) narrowband iot (nb-iot) time slotted channel hopping (tsch) wifi halow wirelesshart

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