Literature DB >> 23684579

Validity and reliability of measuring activities, movement intensity and energy expenditure with the DynaPort MoveMonitor.

Sonja de Groot1, Mieke G Nieuwenhuizen.   

Abstract

The purpose of this study was to evaluate the validity and reliability of assessing activities, movement intensity (MI) and energy expenditure (EE) measured by accelerometry. 28 Able-bodied participants performed standardized tasks while an accelerometer was worn and oxygen uptake was measured. After uploading the accelerometer data to the manufacturer's website, a report was received that gave minute-by-minute MI and EE of the performed activities. Validity was assessed by comparing reported activities and EE with the actual performed activities and calculated EE from the oxygen uptake, and by testing whether MI differed between walking velocities and cycling resistances. Reliability was assessed by performing the protocol twice. Except for standing (classified predominantly (82%) as sitting), most activities were categorized mainly correctly (93-100%). A difference in MI was detected between walking speeds but not between cycling resistances. EE was overestimated for walking (ICC=0.54) and underestimated for cycling (ICC=0.03). Reliability of MI was high (ICC=0.91) but reliability for the relative time spent in activities or the step count was weak to moderate. In conclusion, most activities were categorized correctly, MI seemed to be valid and reliable but reliability is low for relative time spent in activities and EE cannot be estimated well.
Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Activity detection; Adults; Monitoring; Physical activity; Rehabilitation

Mesh:

Substances:

Year:  2013        PMID: 23684579     DOI: 10.1016/j.medengphy.2013.04.004

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  8 in total

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Authors:  Shannon Halloway; Klodian Dhana; Pankaja Desai; Puja Agarwal; Thomas Holland; Neelum T Aggarwal; Jordi Evers; Frank M Sacks; Vincent J Carey; Lisa L Barnes
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2021-10-13       Impact factor: 6.053

2.  Step detection and activity recognition accuracy of seven physical activity monitors.

Authors:  Fabio A Storm; Ben W Heller; Claudia Mazzà
Journal:  PLoS One       Date:  2015-03-19       Impact factor: 3.240

Review 3.  Quantitative Analysis of Motor Status in Parkinson's Disease Using Wearable Devices: From Methodological Considerations to Problems in Clinical Applications.

Authors:  Masahiko Suzuki; Hiroshi Mitoma; Mitsuru Yoneyama
Journal:  Parkinsons Dis       Date:  2017-05-18

4.  Clinical validation of a body-fixed 3D accelerometer and algorithm for activity monitoring in orthopaedic patients.

Authors:  Matthijs Lipperts; Simon van Laarhoven; Rachel Senden; Ide Heyligers; Bernd Grimm
Journal:  J Orthop Translat       Date:  2017-02-27       Impact factor: 5.191

5.  Validity of three accelerometers to investigate lying, sitting, standing and walking.

Authors:  Karin Valkenet; Cindy Veenhof
Journal:  PLoS One       Date:  2019-05-23       Impact factor: 3.240

6.  Measuring physical activity levels in hospitalized patients: a comparison between behavioural mapping and data from an accelerometer.

Authors:  Karin Valkenet; Petra Bor; Lotte van Delft; Cindy Veenhof
Journal:  Clin Rehabil       Date:  2019-03-13       Impact factor: 3.477

7.  Task-specific training for improving propulsion symmetry and gait speed in people in the chronic phase after stroke: a proof-of-concept study.

Authors:  J F Alingh; B E Groen; J F Kamphuis; A C H Geurts; V Weerdesteyn
Journal:  J Neuroeng Rehabil       Date:  2021-04-23       Impact factor: 4.262

8.  The Activ8 activity monitor: Validation of posture and movement classification.

Authors:  Herwin Horemans; Hedwig Kooijmans; Rita van den Berg-Emons; Hans Bussmann
Journal:  J Rehabil Assist Technol Eng       Date:  2020-03-16
  8 in total

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