Projects per year
Abstract
This paper serves a survey and empirical evaluation of the state-of-the-art in activity recognition methods using accelerometers. We examine research that has focused on the selection of activities, the features that are extracted from the accelerometer data, the segmentation of the time-series data, the locations of accelerometers, the selection and configuration trade-offs, the test/retest reliability, and the generalisation performance. Furthermore, we study these questions from an experimental platform and show, somewhat surprisingly, that many disparate experimental configurations yield comparable predictive performance on testing data. Our understanding of these results is that the experimental setup directly and indirectly defines a pathway for context to be delivered to the classifier, and that, in some settings, certain configurations are more optimal than alternatives. We conclude by identifying how the main results of this work can be used in practice, specifically in experimental configurations in challenging experimental conditions.
Original language | English |
---|---|
Article number | 27 |
Number of pages | 37 |
Journal | Informatics |
Volume | 5 |
Issue number | 2 |
Early online date | 30 May 2018 |
DOIs | |
Publication status | Published - Jun 2018 |
Structured keywords
- Digital Health
- SPHERE
Keywords
- machine learning
- activity recognition
- activities of daily living
- acelerometers
- sensors
Fingerprint
Dive into the research topics of 'A Comprehensive Study of Activity Recognition using Accelerometers'. Together they form a unique fingerprint.Projects
- 1 Finished
-
SPHERE (EPSRC IRC)
Craddock, I. J., Coyle, D. T., Flach, P. A., Kaleshi, D., Mirmehdi, M., Piechocki, R. J., Stark, B. H., Ascione, R., Ashburn, A. M., Burnett, M. E., Damen, D., Gooberman-Hill, R., Harwin, W. S., Hilton, G., Holderbaum, W., Holley, A. P., Manchester, V. A., Meller, B. J., Stack, E. & Gilchrist, I. D.
1/10/13 → 30/09/18
Project: Research, Parent
Profiles
-
Dr Ryan McConville
- Department of Engineering Mathematics - Senior Lecturer in Data Science, Machine Learning and AI
Person: Academic