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Physical activity monitoring based on accelerometry: validation and comparison with video observation
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Citations
Cited by
Activity Recognition from User-Annotated Acceleration Data
Bao, L., & Intille, S. S. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24646-6_1 · Cited by 3,147
Preprocessing techniques for context recognition from accelerometer data
Figo, D., Diniz, P. C., Ferreira, D. R., & Cardoso, J. M. P. (2010) · Personal and Ubiquitous Computing · doi:10.1007/s00779-010-0293-9 · Cited by 578
Preece, S. J., Goulermas, J. Y., Kenney, L. P. J., & Howard, D. (2009) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2008.2006190 · Cited by 551
A Study on Human Activity Recognition Using Accelerometer Data from Smartphones
Bayat, A., Pomplun, M., & Tran, D. A. (2014) · Procedia Computer Science · doi:10.1016/j.procs.2014.07.009 · Cited by 531
“In the end, we select the following 18 relevant features from our original 24-dimensional feature vector: Mean along z-axis (1 feature), MinMax, STD and RMS for Am (3 features), APF along x-axis, y-axis and z-axis (3), VarAPF (1), STD along x-axis, y-axis and z-axis (3), RMS along x-axis, y-axis and z-axis (3), Correl…”
InfluentialActivity Recognition of Assembly Tasks Using Body-Worn Microphones and Accelerometers
Ward, J. A., Lukowicz, P., Troster, G., & Starner, T. E. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.197 · Cited by 431
Dowd, K. P., Szeklicki, R., Minetto, M. A., Murphy, M. H., Polito, A., Ghigo, E., van der Ploeg, H., Ekelund, U., Maciaszek, J., Stemplewski, R., et al. (2018) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-017-0636-2 · Cited by 385
Advances in wearable technology and applications in physical medicine and rehabilitation
Bonato, P. (2005) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-2-2 · Cited by 385
Ambulatory monitoring of physical activities in patients with Parkinson’s disease
Salarian, A., Russmann, H., Vingerhoets, F. J. G., Burkhard, P. R., & Aminian, K. (2007) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2007.896591 · Cited by 217
Self-citationA pilot study of long-term monitoring of human movements in the home using accelerometry
Mathie, M. J., Coster, A. C. F., Lovell, N. H., Celler, B. G., Lord, S. R., & Tiedemann, A. (2004) · Journal of Telemedicine and Telecare · doi:10.1258/135763304323070788 · Cited by 153
Chamroukhi, F., Mohammed, S., Trabelsi, D., Oukhellou, L., & Amirat, Y. (2013) · Neurocomputing · doi:10.1016/j.neucom.2013.04.003 · Cited by 88
Detecting activities from body-worn accelerometers via instance-based algorithms
Bicocchi, N., Mamei, M., & Zambonelli, F. (2010) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2010.03.004 · Cited by 55
Wood, L. B., & Asada, H. H. (2006) · 2006 International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/iembs.2006.260359 · Cited by 39
Assessment of physical activity of patients with chronic pain
Perruchoud, C., Buchser, E., Johanek, L. M., Aminian, K., Paraschiv-Ionescu, A., & Taylor, R. S. (2014) · Neuromodulation: Technology at the Neural Interface · doi:10.1111/ner.12036 · Cited by 35
Self-citation
Metadata
- Authors
- Aminian, K., Robert, P., Buchser, E. E., Rutschmann, B., Hayoz, D., & Depairon, M.
- Venue
- Medical & Biological Engineering & Computing
- Published
- 1999-05
- Volume
- 37
- Issue
- 3
- Pages
- 304-308
- ISSN
- 0140-0118 (ISSN-L)
- 1741-0444
- OpenAlex
- W1989472717
- Cited by
- 308
- References
- 0
- FWCI
- 2.99
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
