Literature DB >> 26749436

Physical activity using wrist-worn accelerometers: comparison of dominant and non-dominant wrist.

Olivier Dieu1, Jacques Mikulovic2, Paul S Fardy3, Gilles Bui-Xuan1, Laurent Béghin4,5, Jérémy Vanhelst2,4,5.   

Abstract

The purpose of this study was to determine whether there is a difference in physical activity assessment between a wrist-worn accelerometer at the dominant or non-dominant arm. The secondary purpose was to assess the concurrent validity of measures of physical activity from the wrist-worn accelerometer and the waist-worn accelerometer. Forty adults wore three accelerometers simultaneously, one on the waist and one each on the non-dominant wrist and dominant wrist, respectively, for 24 consecutive hours of free-living conditions. Data were uploaded from the monitor to a computer following a 1-day test period. There were no significant differences in physical activity when comparing the dominant versus the non-dominant wrist, regardless of axis (P>0·05). Mean daily accelerometer output data from both wrists were strongly correlated with average counts per minute from the ActiGraph worn around the waist (r = 0·88, P<0·001). Findings suggest that the choice to wear the accelerometer on the non-dominant or dominant wrist has no impact on results. Data from this study contribute to the knowledge of how to best assess physical activity habits.
© 2016 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

Keywords:  accelerometry; health; methodology; physical patterns

Mesh:

Year:  2016        PMID: 26749436     DOI: 10.1111/cpf.12337

Source DB:  PubMed          Journal:  Clin Physiol Funct Imaging        ISSN: 1475-0961            Impact factor:   2.273


  33 in total

1.  Association of activity status and patterns with salivary cortisol: the population-based CoLaus study.

Authors:  Cédric Gubelmann; Christine Kuehner; Peter Vollenweider; Pedro Marques-Vidal
Journal:  Eur J Appl Physiol       Date:  2018-05-09       Impact factor: 3.078

2.  Estimation of Heart Rate and Energy Expenditure Using a Smart Bracelet during Different Exercise Intensities: A Reliability and Validity Study.

Authors:  Yihui Cai; Zi Wang; Wanxia Zhang; Weiya Kong; Jiayao Jiang; Ruobing Zhao; Dongxue Wang; Leyi Feng; Guoxin Ni
Journal:  Sensors (Basel)       Date:  2022-06-21       Impact factor: 3.847

3.  Examining 24-Hour Activity and Sleep Behaviors and Related Determinants in Latino Adolescents and Young Adults With Obesity.

Authors:  Erica G Soltero; Neeku Navabi; Kiley B Vander Wyst; Edith Hernandez; Felipe G Castro; Stephanie L Ayers; Jenny Mendez; Gabriel Q Shaibi
Journal:  Health Educ Behav       Date:  2021-11-18

4.  Deep CHORES: Estimating Hallmark Measures of Physical Activity Using Deep Learning.

Authors:  Mamoun T Mardini; Subhash Nerella; Amal A Wanigatunga; Santiago Saldana; Ramon Casanova; Todd M Manini
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

5.  Feasibility, Reliability, and Validity of the MotionWatch 8 to Evaluate Physical Activity Among Older Adults With and Without Cognitive Impairment in Assisted Living Settings.

Authors:  Barbara Resnick; Marie Boltz; Elizabeth Galik; Steven Fix; Shijun Zhu
Journal:  J Aging Phys Act       Date:  2020-12-25       Impact factor: 1.961

6.  Physical activity in young children and their parents-An Early STOPP Sweden-China comparison study.

Authors:  Elin Johansson; Hong Mei; Lijuan Xiu; Viktoria Svensson; Yueling Xiong; Claude Marcus; Jianduan Zhang; Maria Hagströmer
Journal:  Sci Rep       Date:  2016-07-12       Impact factor: 4.379

7.  Physical activity derived from questionnaires and wrist-worn accelerometers: comparability and the role of demographic, lifestyle, and health factors among a population-based sample of older adults.

Authors:  Chantal M Koolhaas; Frank Ja van Rooij; Magda Cepeda; Henning Tiemeier; Oscar H Franco; Josje D Schoufour
Journal:  Clin Epidemiol       Date:  2017-12-18       Impact factor: 4.790

8.  Location-Enhanced Activity Recognition in Indoor Environments Using Off the Shelf Smart Watch Technology and BLE Beacons.

Authors:  Avgoustinos Filippoupolitis; William Oliff; Babak Takand; George Loukas
Journal:  Sensors (Basel)       Date:  2017-05-27       Impact factor: 3.576

9.  Physical Activity Levels in Chinese One-Year-Old Children and Their Parents, an Early STOPP China Study.

Authors:  Hong Mei; Elin Johansson; Maria Hagströmer; Yuelin Xiong; Lanlan Zhang; Jianduan Zhang; Claude Marcus
Journal:  PLoS One       Date:  2016-04-14       Impact factor: 3.240

10.  How Accurately Can Your Wrist Device Recognize Daily Activities and Detect Falls?

Authors:  Martin Gjoreski; Hristijan Gjoreski; Mitja Luštrek; Matjaž Gams
Journal:  Sensors (Basel)       Date:  2016-06-01       Impact factor: 3.576

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.