Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults
Researchers are increasingly using 24 h accelerometer wear protocols. No automated method has been published that accurately distinguishes 'waking' wear time from other data ('in-bed', non-wear, invalid days) in young adults. This study examined the validity of an automated algor...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
| Published: |
Institute of Physics Publishing Ltd
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/35642 |
| _version_ | 1848754551013769216 |
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| author | McVeigh, Joanne Winkler, E. Healy, Genevieve Slater, J. Eastwood, Peter Straker, Leon |
| author_facet | McVeigh, Joanne Winkler, E. Healy, Genevieve Slater, J. Eastwood, Peter Straker, Leon |
| author_sort | McVeigh, Joanne |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Researchers are increasingly using 24 h accelerometer wear protocols. No automated method has been published that accurately distinguishes 'waking' wear time from other data ('in-bed', non-wear, invalid days) in young adults. This study examined the validity of an automated algorithm developed to achieve this for hip-worn Actigraph GT3X + 60 s epoch data. We compared the algorithm against a referent method ('into-bed' and 'out-of-bed' times visually identified by two independent raters) and benchmarked against two published algorithms. All methods used the same non-wear rules. The development sample (n = 11) and validation sample (n = 95) were Australian young adults from the Raine pregnancy cohort (54% female), all aged approximately 22 years. The agreement with Rater 1 in each minute's classification (yes/no) of waking wear time was examined as kappa (κ), limited to valid days (10 h waking wear time per day) according to the algorithm and Rater 1. Bland-Altman methods assessed agreement in daily totals of waking wear and in-bed wear time. Excellent agreement (κ > 0.75) was obtained between the raters for 80% of participants (median κ = 0.94). The algorithm showed excellent agreement with Rater 1 (κ >.75) for 89% of participants and poor agreement (κ < 0.40) for 1%. In this sample, the algorithm (median κ = 0.86) performed better than algorithms validated in children (median κ = 0.77) and adolescents (median κ = 0.66). The mean difference (95% limits of agreement) between Rater 1 and the algorithm was 7 (−220, 234) min d−1 for waking wear time on valid days and −41 (−309, 228) min d−1 for in-bed wear time.In this population, the automated algorithm's validity for identifying waking wear time was mostly good, not worse than inter-rater agreement, and better than the evaluated published alternatives. However, the algorithm requires improvement to better identify in-bed wear time. |
| first_indexed | 2025-11-14T08:42:12Z |
| format | Journal Article |
| id | curtin-20.500.11937-35642 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:42:12Z |
| publishDate | 2016 |
| publisher | Institute of Physics Publishing Ltd |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-356422017-09-13T15:27:37Z Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults McVeigh, Joanne Winkler, E. Healy, Genevieve Slater, J. Eastwood, Peter Straker, Leon Researchers are increasingly using 24 h accelerometer wear protocols. No automated method has been published that accurately distinguishes 'waking' wear time from other data ('in-bed', non-wear, invalid days) in young adults. This study examined the validity of an automated algorithm developed to achieve this for hip-worn Actigraph GT3X + 60 s epoch data. We compared the algorithm against a referent method ('into-bed' and 'out-of-bed' times visually identified by two independent raters) and benchmarked against two published algorithms. All methods used the same non-wear rules. The development sample (n = 11) and validation sample (n = 95) were Australian young adults from the Raine pregnancy cohort (54% female), all aged approximately 22 years. The agreement with Rater 1 in each minute's classification (yes/no) of waking wear time was examined as kappa (κ), limited to valid days (10 h waking wear time per day) according to the algorithm and Rater 1. Bland-Altman methods assessed agreement in daily totals of waking wear and in-bed wear time. Excellent agreement (κ > 0.75) was obtained between the raters for 80% of participants (median κ = 0.94). The algorithm showed excellent agreement with Rater 1 (κ >.75) for 89% of participants and poor agreement (κ < 0.40) for 1%. In this sample, the algorithm (median κ = 0.86) performed better than algorithms validated in children (median κ = 0.77) and adolescents (median κ = 0.66). The mean difference (95% limits of agreement) between Rater 1 and the algorithm was 7 (−220, 234) min d−1 for waking wear time on valid days and −41 (−309, 228) min d−1 for in-bed wear time.In this population, the automated algorithm's validity for identifying waking wear time was mostly good, not worse than inter-rater agreement, and better than the evaluated published alternatives. However, the algorithm requires improvement to better identify in-bed wear time. 2016 Journal Article http://hdl.handle.net/20.500.11937/35642 10.1088/0967-3334/37/10/1636 Institute of Physics Publishing Ltd restricted |
| spellingShingle | McVeigh, Joanne Winkler, E. Healy, Genevieve Slater, J. Eastwood, Peter Straker, Leon Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults |
| title | Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults |
| title_full | Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults |
| title_fullStr | Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults |
| title_full_unstemmed | Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults |
| title_short | Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults |
| title_sort | validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults |
| url | http://hdl.handle.net/20.500.11937/35642 |