The feasibility of using sensecams to measure the type and context of daily sedentary behaviors

Catherine Marinac, Gina Merchant, Suneeta Godbole, Jacqueline H. Chen, Jacqueline Kerr, Bronwyn Clark, Simon Marshall

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

The SenseCam data can be used to estimate time spent in specific episodes of sedentary behaviors, as well as some dimensions of sedentary behaviors. However, it is unknown whether SenseCam data can be aggregated to provide an objective estimate of total sedentary time accumulated during a single day. We compared SenseCam-derived day-level estimates to self-report estimates of time spent in sedentary behaviors using 39 days of concurrent SenseCam and self-report data from a sample of university employed adults (age 18-70 years). We also examined whether SenseCam data can be used to compute day-level estimates of specific dimensions of sedentary behavior (e.g., co-occurring sedentary behaviors and social context). Twenty-four percent of the days of SenseCam image data collected did not have enough image data (i.e., ≥8 hours of data) to generate day-level estimates. Further, the day-level agreement between the SenseCam and self-report estimates of time spent in sedentary behaviors varied considerably by device wear time. In terms of dimensions of sedentary behaviors measured by the SenseCam, over one-third of the total sedentary time involved a social interaction and the majority (71%) of the estimated sedentary time was spent in one behavior. Overall, SenseCam data can be used to compute day-level estimates of time spent in specific episodes of sedentary behaviors and the images provide data on critical dimensions of these behaviors; however, device wear-time significantly influences the accuracy of day-level estimates.

Original languageEnglish
Title of host publicationSenseCam 2013 - Proceedings of the 4th SenseCam and Pervasive Imaging 2013 Conference, in Cooperation with ACM and SIGCHI
PublisherAssociation for Computing Machinery (ACM)
Pages42-49
Number of pages8
ISBN (Print)9781450322478
DOIs
Publication statusPublished - 2013
Externally publishedYes
EventInternational SenseCam and Pervasive Imaging Conference (SenseCam 2013) - University of California, San Diego, San Diego, United States
Duration: 18 Nov 201319 Nov 2013
Conference number: 4th
https://dl-acm-org.ezproxy.lib.monash.edu.au/citation.cfm?id=2526667&picked=prox

Conference

ConferenceInternational SenseCam and Pervasive Imaging Conference (SenseCam 2013)
Abbreviated titleSenseCam 2013
CountryUnited States
CitySan Diego
Period18/11/1319/11/13
Internet address

Keywords

  • Camera
  • Measurement
  • Monitoring
  • Objective behavioral assessment
  • Sitting

Cite this

Marinac, C., Merchant, G., Godbole, S., Chen, J. H., Kerr, J., Clark, B., & Marshall, S. (2013). The feasibility of using sensecams to measure the type and context of daily sedentary behaviors. In SenseCam 2013 - Proceedings of the 4th SenseCam and Pervasive Imaging 2013 Conference, in Cooperation with ACM and SIGCHI (pp. 42-49). Association for Computing Machinery (ACM). https://doi.org/10.1145/2526667.2526674
Marinac, Catherine ; Merchant, Gina ; Godbole, Suneeta ; Chen, Jacqueline H. ; Kerr, Jacqueline ; Clark, Bronwyn ; Marshall, Simon. / The feasibility of using sensecams to measure the type and context of daily sedentary behaviors. SenseCam 2013 - Proceedings of the 4th SenseCam and Pervasive Imaging 2013 Conference, in Cooperation with ACM and SIGCHI. Association for Computing Machinery (ACM), 2013. pp. 42-49
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title = "The feasibility of using sensecams to measure the type and context of daily sedentary behaviors",
abstract = "The SenseCam data can be used to estimate time spent in specific episodes of sedentary behaviors, as well as some dimensions of sedentary behaviors. However, it is unknown whether SenseCam data can be aggregated to provide an objective estimate of total sedentary time accumulated during a single day. We compared SenseCam-derived day-level estimates to self-report estimates of time spent in sedentary behaviors using 39 days of concurrent SenseCam and self-report data from a sample of university employed adults (age 18-70 years). We also examined whether SenseCam data can be used to compute day-level estimates of specific dimensions of sedentary behavior (e.g., co-occurring sedentary behaviors and social context). Twenty-four percent of the days of SenseCam image data collected did not have enough image data (i.e., ≥8 hours of data) to generate day-level estimates. Further, the day-level agreement between the SenseCam and self-report estimates of time spent in sedentary behaviors varied considerably by device wear time. In terms of dimensions of sedentary behaviors measured by the SenseCam, over one-third of the total sedentary time involved a social interaction and the majority (71{\%}) of the estimated sedentary time was spent in one behavior. Overall, SenseCam data can be used to compute day-level estimates of time spent in specific episodes of sedentary behaviors and the images provide data on critical dimensions of these behaviors; however, device wear-time significantly influences the accuracy of day-level estimates.",
keywords = "Camera, Measurement, Monitoring, Objective behavioral assessment, Sitting",
author = "Catherine Marinac and Gina Merchant and Suneeta Godbole and Chen, {Jacqueline H.} and Jacqueline Kerr and Bronwyn Clark and Simon Marshall",
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Marinac, C, Merchant, G, Godbole, S, Chen, JH, Kerr, J, Clark, B & Marshall, S 2013, The feasibility of using sensecams to measure the type and context of daily sedentary behaviors. in SenseCam 2013 - Proceedings of the 4th SenseCam and Pervasive Imaging 2013 Conference, in Cooperation with ACM and SIGCHI. Association for Computing Machinery (ACM), pp. 42-49, International SenseCam and Pervasive Imaging Conference (SenseCam 2013), San Diego, United States, 18/11/13. https://doi.org/10.1145/2526667.2526674

The feasibility of using sensecams to measure the type and context of daily sedentary behaviors. / Marinac, Catherine; Merchant, Gina; Godbole, Suneeta; Chen, Jacqueline H.; Kerr, Jacqueline; Clark, Bronwyn; Marshall, Simon.

SenseCam 2013 - Proceedings of the 4th SenseCam and Pervasive Imaging 2013 Conference, in Cooperation with ACM and SIGCHI. Association for Computing Machinery (ACM), 2013. p. 42-49.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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Marinac C, Merchant G, Godbole S, Chen JH, Kerr J, Clark B et al. The feasibility of using sensecams to measure the type and context of daily sedentary behaviors. In SenseCam 2013 - Proceedings of the 4th SenseCam and Pervasive Imaging 2013 Conference, in Cooperation with ACM and SIGCHI. Association for Computing Machinery (ACM). 2013. p. 42-49 https://doi.org/10.1145/2526667.2526674