Identifying Types of Physical Activity With a Single Accelerometer: Evaluating Laboratory-trained Algorithms in Daily Life
- 27 June 2011
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Biomedical Engineering
- Vol. 58 (9), 2656-2663
- https://doi.org/10.1109/tbme.2011.2160723
Abstract
Accurate identification of physical activity types has been achieved in laboratory conditions using single-site accelerometers and classification algorithms. This methodology is then applied to free-living subjects to determine activity behavior. This study is aimed at analyzing the reproducibility of the accuracy of laboratory-trained classification algorithms in free-living subjects during daily life. A support vector machine (SVM), a feed-forward neural network (NN), and a decision tree (DT) were trained with data collected by a waist-mounted accelerometer during a laboratory trial. The reproducibility of the classification performance was tested on data collected in daily life using a multiple-site accelerometer augmented with an activity diary for 20 healthy subjects (age: 30 ± 9; BMI: 23.0 ± 2.6 kg/m2). Leave-one-subject-out cross validation of the training data showed accuracies of 95.1 ± 4.3%, 91.4 ± 6.7%, and 92.2 ± 6.6% for the SVM, NN, and DT, respectively. All algorithms showed a significantly decreased accuracy in daily life as compared to the reference truth represented by the IDEEA and diary classifications (75.6 ± 10.4%, 74.8 ± 9.7%, and 72.2 ± 10.3 %; p <; 0.05). In conclusion, cross validation of training data overestimates the accuracy of the classification algorithms in daily life.Keywords
This publication has 29 references indexed in Scilit:
- Detection of gait and postures using a miniaturised triaxial accelerometer-based system: Accuracy in community-dwelling older adultsAge and Ageing, 2010
- An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometerJournal of Applied Physiology, 2009
- Improving assessment of daily energy expenditure by identifying types of physical activity with a single accelerometerJournal of Applied Physiology, 2009
- The Role of Free-Living Daily Walking in Human Weight Gain and ObesityDiabetes, 2008
- Behavior and Cancer PreventionJournal of Clinical Oncology, 2005
- Low physical activity as a predictor for total and cardiovascular disease mortality in middle-aged men and women in FinlandEuropean Heart Journal, 2004
- The economics of physical activity: Societal trends and rationales for interventionsAmerican Journal of Preventive Medicine, 2004
- Relationship between physical activity and bone mineral status in young adults: the Northern Ireland young hearts projectBone, 2002
- Reproducibility and Validity of a Self-Administered Physical Activity QuestionnaireInternational Journal of Epidemiology, 1994
- Physical activity and incidence of non-insulin-dependent diabetes mellitus in womenThe Lancet, 1991