Slagboom P. (Eline); Beekman M. (Marian); Stylianos Paraschiakos; Knobbe A. (Arno); Cachucho R. (Ricardo) (2020): GOTOV Human Physical Activity and Energy Expenditure Dataset on Older Individuals. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:d3dd8165-cc4e-4e2a-ab12-82198ab6dc39

Dataset

x choose version: version 2 - 2021-11-15 (latest)

• Health and Support Services
• Other Medical and Health Sciences
• Information Systems
• Human Movement and Sports Science

accelerometer, activities of daily living, activity recognition, ageing, older population, ubiquitous sensing, wearables

CC BY-NC-SA 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Slagboom P. (Eline) , Beekman M. (Marian) , Stylianos Paraschiakos , Knobbe A. (Arno), Cachucho R. (Ricardo)

Wearable sensor-based data of physical activities and indirect calorimetry for 35 (14 female, 21 male) healthy older individuals (over 60 years old). The data has been collected from different body locations and devices: 3x GeneActives accelerometers (ankle, wrist, and chest), 1x Equivital (chest) and COSMED (mask and belt on chest). The 35 individuals followed a protocol of 16 activities of daily living for approximately an hour and a half in a semi-lab environment. These include different types or paces of indoor and outdoor activities with low (lying down, sitting), mid (standing, household activities) and high (walking and cycling) levels of intensity. Additionally, some activities can be specified at different granularities. The study took place at LUMC, between February and May 2015.

• 2020-06-26 first online, published, posted

4TU.Centre for Research Data

media types: application/pdf, application/zip, image/jpeg, text/csv, text/plain

• https://arxiv.org/abs/2006.01169
• https://doi.org/10.1007/s11257-020-09268-2
• https://doi.org/10.1109/embc.2019.8857288

• Netherlands Consortium for Healthy Ageing, 050-060-810

Leiden University Medical Center, Department of Biomedical Data Sciences, Molecular Epidemiology