Dataset for "Analysing longitudinal wearable physical activity data using Non-stationary Time Series models"

This dataset contains secondary data from the Multidimensional Individualised Physical Activity (MIPACT) randomized controlled trial used for analysis in “Analysing longitudinal wearable physical activity data using Non-stationary Time Series models”. Physical activity data over the 12-week intervention for 80 participants (28 women) aged between 43 and 70 years old is presented in this dataset at hourly resolution.

Keywords:

Physical Activity Wearable data analysis Wearable devices Trend estimation Longitudinal Study Longitudinal data analysis Non-stationary time series TLSW High resolution data Sedentary time

Subjects:

Mathematical sciences

Statistics and Applied Probability

Cite this dataset as:
Del Angel Martinez, M., Thompson, D., Nunes, M., 2025. Dataset for "Analysing longitudinal wearable physical activity data using Non-stationary Time Series models". Bath: University of Bath Research Data Archive. Available from: https://doi.org/10.15125/BATH-01416.

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Data

Hourly_SedTime.csv
application/csv (9MB)
Creative Commons: Attribution 4.0

This dataset contains physical activity data used for analysis in “Analysing longitudinal wearable physical activity data using Non-stationary Time Series models”. See Readme file for details.

Creators

Melina Nohemi Del Angel Martinez
University of Bath

0000-0002-3958-5769

Dylan Thompson
University of Bath

0000-0002-6312-1518

Matthew Nunes
University of Bath

0000-0002-4719-2690

Contributors

University of Bath
Rights Holder

Documentation

Data collection method:

Full details of the methodology for collecting the minute resolution data are provided in the published study protocol. The raw data was aggregated to obtain the number of minutes spent in sedentary time per hour ("Sedentary"). This aggregated data is presented in the current dataset.

Technical details and requirements:

The raw data was processed using the statistical software R (version 4.3.0). The resulting dataset is saved in CSV format and can be opened with any software that supports CSV files, including Microsoft Excel.

Methodology link:

Peacock, O. J., Western, M. J., Batterham, A. M., Stathi, A., Standage, M., Tapp, A., Bennett, P., and Thompson, D., 2015. Multidimensional individualised Physical ACTivity (Mi-PACT) – a technology-enabled intervention to promote physical activity in primary care: study protocol for a randomised controlled trial. Trials, 16(1). Available from: https://doi.org/10.1186/s13063-015-0892-x.

Documentation Files

Readme.docx
application/vnd.openxmlformats-officedocument.wordprocessingml.document (17kB)
Creative Commons: Attribution 4.0

Funders

University of Bath
https://doi.org/10.13039/501100000835

Doctoral Studentship

Publication details

Publication date: 9 June 2025
by: University of Bath

Version: 1

DOI: https://doi.org/10.15125/BATH-01416

URL for this record: https://researchdata.bath.ac.uk/1416

Related datasets and code

Peacock, O., and Thompson, D., 2020. Dataset for "Effect of Novel Technology-Enabled Multidimensional Physical Activity Feedback in Primary Care Patients at Risk of Chronic Disease – the MIPACT study". Version 1. Bath: University of Bath Research Data Archive. Available from: https://doi.org/10.15125/BATH-00713.

Contact information

Please contact the Research Data Service in the first instance for all matters concerning this item.

Contact person: Melina Nohemi Del Angel Martinez

Departments:

Faculty of Humanities & Social Sciences
Health

Research Centres & Institutes
Centre for Nutrition, Exercise and Metabolism (CNEM)