WildCam: A Privacy Conscious Wearable Eating Detection Camera People Will Actually Wear in the Wild

Summary

WildCam is a wearable device that collects video data of the user's face and upper torso to capture eating behaviors. WildCam and its accompanying software is privacy conscious, meaning it utilizes a computer vision algorithm that extracts proximal features (the user's body and objects-in-hand) from the video and digitally obfuscates the distal features (background environment and entities therein) to preserve the privacy of the wearer, as well as any bystanders who may be in the device's visual field. The present study tests the impact of 3 different obfuscation techniques on acceptability, including the willingness of users to wear the device. Participants are randomly assigned to 1 of the 3 obfuscation techniques (blurring, masking, or cartooning). Participants wear the WildCam during waking hours during a 7-day period with the randomly selected obfuscation setting enabled and a 7-day period with the raw images (no obfuscation) setting. The order of these periods is counterbalanced, and the two periods are separated by a 7-day washout period during which WildCam is not worn. Structured feedback, including user burden and acceptability surveys, is collected to determine the efficacy of each obfuscation technique on increasing user acceptability, including willingness to use the WildCam device, as opposed to a video-collecting device without obfuscation.

Conditions

• Wearable Electronic Devices

Interventions

DEVICE

Blur Obfuscation

Blurring is applied to objects and people in the background of images.

DEVICE

Edge Obfuscation

Objects and people in the background of images are replaced with an outline of the object.

DEVICE

Cartoon Obfuscation

Blurring is applied to objects and people in the background of images and the wearer's face is concealed with cartoon faces.

DEVICE

Raw images

No editing is performed on images.

Sponsors & Collaborators

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

  collaborator NIH

• Northwestern University

  lead OTHER

Study Design

Allocation

RANDOMIZED

Purpose

BASIC_SCIENCE

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

18 Years

Max Age

64 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2022-09-20

Primary Completion

2023-03-21

Completion

2023-03-21

Countries

• United States

Study Locations