A Hickey1, J Newham2, M M Slawinska3, D Kwasnicka4, S McDonald2, S Del Din1, F F Sniehotta2, P A Davis3, A Godfrey5. 1. Institute of Neuroscience, Newcastle University Institute for Ageing, Newcastle University, UK. 2. Institute of Health and Society, Newcastle University, Newcastle upon Tyne NE2 4AX, UK. 3. Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne NE1 8ST, UK. 4. School of Psychology and Speech Pathology, Curtin University, Bentley, Australia. 5. Institute of Neuroscience, Newcastle University Institute for Ageing, Newcastle University, UK. Electronic address: alan.godfrey@ncl.ac.uk.
Abstract
UNLABELLED: Wearable technology is readily available for continuous assessment due to a growing number of commercial devices with increased data capture capabilities. However, many commercial devices fail to support suitable parameters (cut points) derived from the literature to help quantify physical activity (PA) due to differences in manufacturing. A simple metric to estimate cut points for new wearables is needed to aid data analysis. OBJECTIVE: The purpose of this pilot study was to investigate a simple methodology to determine cut points based on ratios between sedentary behaviour (SB) and PA intensities for a new wrist worn device (PRO-Diary™) by comparing its output to a validated and well characterised 'gold standard' (ActiGraph™). STUDY DESIGN: Twelve participants completed a semi-structured (four-phase) treadmill protocol encompassing SB and three PA intensity levels (light, moderate, vigorous). The outputs of the devices were compared accounting for relative intensity. RESULTS: Count ratios (6.31, 7.68, 4.63, 3.96) were calculated to successfully determine cut-points for the new wrist worn wearable technology during SB (0-426) as well as light (427-803), moderate (804-2085) and vigorous (≥ 2086) activities, respectively. CONCLUSION: Our findings should be utilised as a primary reference for investigations seeking to use new (wrist worn) wearable technology similar to that used here (i.e., PRO-Diary™) for the purposes of quantifying SB and PA intensities. The utility of count ratios may be useful in comparing devices or SB/PA values estimated across different studies. However, a more robust examination is required for different devices, attachment locations and on larger/diverse cohorts.
UNLABELLED: Wearable technology is readily available for continuous assessment due to a growing number of commercial devices with increased data capture capabilities. However, many commercial devices fail to support suitable parameters (cut points) derived from the literature to help quantify physical activity (PA) due to differences in manufacturing. A simple metric to estimate cut points for new wearables is needed to aid data analysis. OBJECTIVE: The purpose of this pilot study was to investigate a simple methodology to determine cut points based on ratios between sedentary behaviour (SB) and PA intensities for a new wrist worn device (PRO-Diary™) by comparing its output to a validated and well characterised 'gold standard' (ActiGraph™). STUDY DESIGN: Twelve participants completed a semi-structured (four-phase) treadmill protocol encompassing SB and three PA intensity levels (light, moderate, vigorous). The outputs of the devices were compared accounting for relative intensity. RESULTS: Count ratios (6.31, 7.68, 4.63, 3.96) were calculated to successfully determine cut-points for the new wrist worn wearable technology during SB (0-426) as well as light (427-803), moderate (804-2085) and vigorous (≥ 2086) activities, respectively. CONCLUSION: Our findings should be utilised as a primary reference for investigations seeking to use new (wrist worn) wearable technology similar to that used here (i.e., PRO-Diary™) for the purposes of quantifying SB and PA intensities. The utility of count ratios may be useful in comparing devices or SB/PA values estimated across different studies. However, a more robust examination is required for different devices, attachment locations and on larger/diverse cohorts.
Authors: Ali K Yetisen; Juan Leonardo Martinez-Hurtado; Barış Ünal; Ali Khademhosseini; Haider Butt Journal: Adv Mater Date: 2018-06-11 Impact factor: 30.849