Validity of pervasive computing based continuous physical activity assessment in community-dwelling old and oldest-old

Schütz, Narayan (Gerontechnology & Rehabilitation Group, University of Bern, Bern, Switzerland) ; Saner, Hugo (Gerontechnology & Rehabilitation Group, University of Bern, Bern, Switzerland; 2Department of Cardiology, University Hospital Bern (Inselspital), University of Bern, Bern, Switzerland) ; Rudin, Beatrice (Höhere Fachschule Pflege, Berufsbildungszentrum Olten, Olten, Switzerland) ; Botros, Angela (Gerontechnology & Rehabilitation Group, University of Bern, Bern, Switzerland) ; Pais, Bruno (La Source, School of nursing sciences, HES-SO University of Applied Sciences and Arts of Western Switzerland, Lausanne) ; Santschi, Valérie (La Source, School of nursing sciences, HES-SO University of Applied Sciences and Arts of Western Switzerland, Lausanne) ; Buluschek, Philipp (DomoSafety S.A., Lausanne, Switzerland) ; Gatica-Perez, Daniel (Idiap Research Institute, Martigny, Switzerland; École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland) ; Urwyler, Prabita (Gerontechnology & Rehabilitation Group, University of Bern, Bern, Switzerland; Department of Neurology, University Neurorehabilitation Unit, University Hospital Bern (Inselspital), University of Bern, Bern, Switzerland) ; Marchal-Crespo, Laura (Gerontechnology & Rehabilitation Group, University of Bern, Bern, Switzerland; ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland; Sensory‐Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), Department of Health Sciences and Technology (D‐HEST), ETH Zürich, Zürich, Switzerland) ; Müri, René M. (Gerontechnology & Rehabilitation Group, University of Bern, Bern, Switzerland; Department of Neurology, University Neurorehabilitation Unit, University Hospital Bern (Inselspital), University of Bern, Bern, Switzerland) ; Nef, Tobias (Gerontechnology & Rehabilitation Group, University of Bern, Bern, Switzerland; ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland)

In older adults, physical activity is crucial for healthy aging and associated with numerous health indicators and outcomes. Regular assessments of physical activity can help detect early health-related changes and manage physical activity targeted interventions. The quantification of physical activity, however, is difficult as commonly used self-reported measures are biased and rather unprecise point in time measurements. Modern alternatives are commonly based on wearable technologies which are accurate but suffer from usability and compliance issues. In this study, we assessed the potential of an unobtrusive ambient-sensor based system for continuous, long-term physical activity quantification. Towards this goal, we analysed one year of longitudinal sensor- and medical-records stemming from thirteen community-dwelling old and oldest old subjects. Based on the sensor data the daily number of room-transitions as well as the raw sensor activity were calculated. We did find the number of roomtransitions, and to some degree also the raw sensor activity, to capture numerous known associations of physical activity with cognitive, well-being and motor health indicators and outcomes. The results of this study indicate that such low-cost unobtrusive ambient-sensor systems can provide an adequate approximation of older adults’ overall physical activity, sufficient to capture relevant associations with health indicators and outcomes.


Keywords:
Article Type:
scientifique
Faculty:
Santé
School:
La Source
Institute:
Secteur Recherche et Développement (Ra&D) de l'Institut et Haute Ecole de la Santé La Source
Subject(s):
Santé
Date:
2019-04
Pagination:
9 p.
Published in:
Scientific Reports
Numeration (vol. no.):
2019, vol. 9(9662)
DOI:
ISSN:
2045-2322
Appears in Collection:



 Record created 2019-07-05, last modified 2019-08-13

Fulltext:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)