Tag: wearable technologies

Eating detection with a head-mounted video camera

In this paper, we present a computer-vision based approach to detect eating. Specifically, our goal is to develop a wearable system that is effective and robust enough to automatically detect when people eat, and for how long. We collected video from a cap-mounted camera on 10 participants for about 55 hours in free-living conditions. We evaluated performance of eating detection with four different Convolutional Neural Network (CNN) models. The best model achieved accuracy 90.9% and F1 score 78.7% for eating detection with a 1-minute resolution. We also discuss the resources needed to deploy a 3D CNN model in wearable or mobile platforms, in terms of computation, memory, and power. We believe this paper is the first work to experiment with video-based (rather than image-based) eating detection in free-living scenarios.

To see more from the Auracle research group, check out our publications on Zotero.

Bi, Shengjie and Kotz, David, “Eating detection with a head-mounted video camera” (2021). Computer Science Technical Report TR2021-1002. Dartmouth College. https://digitalcommons.dartmouth.edu/cs_tr/384

New Auracle Dissertation by Byron Lowens

We are proud to announce another Auracle team member’s successful dissertation defense, and to share his doctoral thesis. Dr. Byron Lowens’ dissertation focuses on understanding how to develop privacy control mechanisms that provide adopters (and potential adopters) of wearables with integrated, in-the-moment control over personal information collected by wearables. Lowens describes the four different studies he conducted, on individual preferences on data sharing, the impact of the location of privacy control and decision timing, device-independent interactions to control data privacy, and on noticeability of identified interactions. His findings offer privacy researchers and designers of wearable technologies insight into the future development of wearables.

To learn more, check out Lowens’ dissertation below.

Lowens, Byron M., “Interaction Techniques for In-the-Moment Privacy Control Over Data Generated by Wearable Technologies” (2021). Clemson University Dissertations: 2894. 
https://tigerprints.clemson.edu/all_dissertations/2894