Evidence map›Paper›PMID 40012793›Full record

ArticleExtended abstracts on Human factors in computing systems. CHI Conference2023

Experience: Barriers and Opportunities of Wearables for Eating Research.

Mahdi Pedram, Glenn Fernandes, Christopher Romano, Boyang Wei, Sougata Sen, Josiah Hester, Nabil Alshurafa

Abstract read
In one paragraph

Article in Extended abstracts on Human factors in computing systems. CHI Conference, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mahdi PedramNorthwestern University, Chicago, Illinois, USA.
Glenn FernandesNorthwestern University, Chicago, Illinois, USA.
Christopher RomanoNorthwestern University, Chicago, Illinois, USA.
Boyang WeiNorthwestern University, Chicago, Illinois, USA.
Sougata SenBITS Pilani, Goa Campus, Pilani, Goa, India.
Josiah HesterGeorgia Institute of Technology, Atalanta, Georgia, USA.
Nabil AlshurafaNorthwestern University, Chicago, Illinois, USA.

Funding

EAT: A Reliable Eating Assessment Technology for Free-living Individuals.R01DK129843 · NIDDK · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ALSHURAFA, NABIL · 2021 to 2025
$3.3M
SenseWhy: Overeating in Obesity Through the Lens of Passive Sensing.K25DK113242 · NIDDK · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ALSHURAFA, NABIL · 2018 to 2022
$881k
BehaviorSight: Privacy enhancing wearable system to detect health risk behaviors in real-time.R21EB030305 · NIBIB · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ALSHURAFA, NABIL · 2020 to 2020
$607k
WildCam: A Privacy Conscious Wearable Eating Detection Camera People will Actually Wear in the WildR03DK127128 · NIDDK · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ALSHURAFA, NABIL · 2021 to 2022
$234k
NIBIB NIH HHS R21 EB030305NIDDK NIH HHS K25 DK113242NIDDK NIH HHS R01 DK129843NIDDK NIH HHS R03 DK127128
6 · The paper itself

Abstract

Wearable devices have long held the potential to provide real-time objective measures of behavior. However, due to challenges in real-world deployment, these systems are rarely tested rigorously in free-living settings. To reduce this challenge for future researchers, in this paper, we describe our experience developing several generations of a multi-sensor, neck-worn eating-detection system that has been tested with 130 participants across multiple studies in both laboratory and free-living settings. We describe the challenges faced in the development and deployment of the system by (1) presenting example deployment details captured either by the sensing system or the ground truth collector and (2) using structured interviews and surveys with developers and stakeholders of the system, collecting qualitative data on their experience. We performed thematic analysis and provided detailed lessons learned explaining factors that impact the experience of building and deploying such a wearable in a free-living setting, reducing challenges for future researchers. We believe that our experience will help future researchers develop successful mobile health (mHealth) systems that translate into reliable free-living deployments.

Indexed as

Case studyComputer systems organizationeating detectionHuman-centered computingSensor networksUbiquitous and mobile computing systems and toolsUser studieswearable sensors

Identifiers

PMID40012793
PMCPMC11864365

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.