Cited by 223Context-Aware Activity Recognition SystemsMobile Health and mHealth ApplicationsHuman Mobility and Location-Based Analysis

Shakra: Tracking and Sharing Daily Activity Levels with Unaugmented Mobile Phones

Anderson, Ian, Maitland, Julie, Sherwood, Scott, Barkhuus, Louise, Chalmers, Matthew, Hall, Malcolm, Brown, Barry, Muller, Henk·2007·Mobile Networks and Applications

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Registry

Crossref · 10.1007/s11036-007-0011-7

Cites

20 of 20 references verified0 citation errors · 0 not checkable

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  • Previous research has highlighted the benefits of stand-alone app-based interventions on individuals' awareness of eating behaviors and physical activity levels.

    “Previous research has highlighted the benefits of stand-alone app-based interventions on individuals’ awareness of their eating behaviors and physical activity levels [15,16,42,45,46].”
  • Ability to integrate app use into one's daily routine is an important potential facilitator and/or barrier to intervention usage.

    “The impact of users’ availability to interact with the app and take advantage of free moments echoes reports that ability to integrate app use into one’s daily routine is an important potential facilitator and/or barrier to intervention usage [16,24,32,46].”

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Authors
Anderson, I., Maitland, J., Sherwood, S., Barkhuus, L., Chalmers, M., Hall, M., Brown, B., & Muller, H.
Affiliations
  • University of Bristol (GB)
  • University of Glasgow (GB)
Corresponding author
Anderson, Ian
Venue
Mobile Networks and Applications
Published
2007-06
Volume
12
Issue
2-3
Pages
185-199
ISSN
  • 1383-469X (ISSN-L)
  • 1572-8153
OpenAlex
W2068021035
Cited by
223
References
20
Citations by year
2026: 1 · 2025: 3 · 2024: 5 · 2023: 4 · 2022: 1 · 2021: 9 · 2020: 13 · 2019: 11 · 2018: 24 · 2017: 14 · 2016: 14 · 2015: 23 · 2014: 22 · 2013: 19 · 2012: 20
FWCI
12.70
Type
journal article
Language
en
Open access
closed
Locations
  • Mobile Networks and Applications (publishedVersion)
  • Explore Bristol Research (publishedVersion)
  • Bristol Research (University of Bristol) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Transportation › Human Mobility and Location-Based Analysis
Keywords
mobile devices, activity monitoring, exercise monitoring, health promotion, artificial neural networks, motion detection, hidden Markov models, task modeling, unsupervised calibration, social sharing, motivation

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