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Memorias de investigación
Artículos en revistas:
Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate
Año:2011
Áreas de investigación
  • Medicina,
  • Ciencias de la computación y tecnología informática
Datos
Descripción
This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators
Internacional
Si
JCR del ISI
Si
Título de la revista
Lecture Notes in Artificial Intelligence
ISSN
0302-9743
Factor de impacto JCR
0,302
Información de impacto
Datos JCR del año 2005
Volumen
DOI
Número de revista
Desde la página
70
Hasta la página
79
Mes
SIN MES
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Fernando Garcia Garcia (UPM)
  • Autor: Gema Garcia Saez (UPM)
  • Autor: Paloma Chausa Fernández (UPM)
  • Autor: Iñaki Martínez Sarriegui (UPM)
  • Autor: Pedro J. Benito
  • Autor: Enrique Javier Gomez Aguilera (UPM)
  • Autor: Maria Elena Hernando Perez (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Tecnología Fotónica y Bioingeniería
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