# BehaviorSight: Privacy enhancing wearable system to detect health risk behaviors in real-time.

> **NIH NIH R21** · NORTHWESTERN UNIVERSITY · 2020 · $606,713

## Abstract

Project Summary/Abstract
Health-risk behaviors, such as overeating, smoking, consuming alcohol, and not adhering to medication, are
responsible for increases in morbidity and mortality. To track and intervene during these health-risk behaviors,
clinicians traditionally rely on self-reports. However, self-reports are inaccurate and biased. Therefore, we cannot
use self-reports to validate health-risk behaviors in free-living conditions. Thus, an automated technique for
validating health-risk behaviors is extremely necessary.
With the growth and popularity of wearable devices (e.g., smartwatches), automatic monitoring of physical
activity is possible. However, the devices often do not provide any visual confirmation, making it challenging to
verify activities performed in free-living conditions. Cameras can capture point-of-view videos and can thus be
used as a wearable device to capture videos for visual confirmation of activities, including health-risk behaviors.
Such recordings can help us better understand health-risk behaviors. Additionally, video information can be
automatically processed to confirm and validate health-risk behaviors.
Recording videos of sensitive content and bystanders is associated with privacy and ethical concerns. Currently
there is no privacy-preserving camera that can automatically detect health-risk behaviors, and most people are
unwilling to wear cameras without raising privacy concerns. In addition to privacy concerns, people prefer
wearables that are unobtrusive and small and that do not require frequent charging. Thus, a privacy-preserving,
unobtrusive wearable camera would increase wearability.
Infrared (IR) sensor arrays have the potential to provide independent temperature readings, which allows
determining whether an object is near or far. The IR sensor array can help record only the wearer and objects
near the wearer, while filtering out distant objects. IR sensor arrays have a small power footprint, thus providing
longer battery life. Our project aims to develop a privacy-conscious, unobtrusive, wearable, behavior-detection
platform that will make it possible to detect and intervene upon health-risk behaviors in real time.
In this project, we will (1) develop the wearable behavior-detection device that allows visual confirmation without
burdening the wearer. The device will augment RGB camera data with IR sensor array data for privacy-conscious
recording and automatic behavior detection. (2) We will test various designs to determine a user's acceptability
to wear the device. Then, we will test various image processing techniques and machine learning algorithms to
determine the best algorithm for detecting health-risk behaviors. (3) We will incorporate the best-performing
behavior-detection algorithm so that it can run on the developed wearable device. With a behavior-detection
algorithm running on an acceptable wearable device, the ability to detect health-risk behaviors in real time will
become a reality. Ul...

## Key facts

- **NIH application ID:** 10043674
- **Project number:** 1R21EB030305-01
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Nabil Alshurafa
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $606,713
- **Award type:** 1
- **Project period:** 2020-09-10 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10043674

## Citation

> US National Institutes of Health, RePORTER application 10043674, BehaviorSight: Privacy enhancing wearable system to detect health risk behaviors in real-time. (1R21EB030305-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10043674. Licensed CC0.

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