Nonparametric discovery of movement patterns from accelerometer signals
Open accessIntegrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Pattern recognition and pattern matching techniques have been used to extract specific movement patterns from long-term datasets obtained by wearable sensor devices, especially those equipped with accelerometers and IMUs.
“Pattern recognition and pattern matching techniques have been used to extract specific movement patterns from long-term datasets obtained by wearable sensor devices, especially those equipped with accelerometers and IMUs [135].”
From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [135]
Non-parametric discovery of human movement patterns for walking, sedentary activities, running and jumping from accelerometer data using a Hierarchical Dirichlet process model implemented using Support Vector Machine exhibited precision of 0.81 and recall of 0.77 for sliding window time durations.
“Non-parametric discovery of human movement patterns for walking, sedentary activities, running and jumping from accelerometer data using a Hierarchical Dirichlet process (HDP) model implemented using Support Vector Machine (SVM) exhibited precision of 0.81 and recall of 0.77 for sliding window time durations.”
From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [135]
An HDP model cannot estimate activity levels automatically over lengthy periods of time.
“However, studies have shown that an HDP model cannot estimate activity levels automatically over lengthy periods of time [135].”
From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [135]
Cites
Introduction to information retrieval
(2009) · Choice Reviews Online · doi:10.5860/choice.46-2715 · Cited by 12,278 · see citing works
Introduction to Information Retrieval
Manning, C. D., Raghavan, P., & Schütze, H. (2008) · doi:10.1017/cbo9780511809071 · Cited by 11,288 · see citing works
Clustering by Passing Messages Between Data Points
Frey, B. J., & Dueck, D. (2007) · Science · doi:10.1126/science.1136800 · Cited by 6,733 · see citing works
A Bayesian Analysis of Some Nonparametric Problems
Ferguson, T. S. (1973) · The Annals of Statistics · doi:10.1214/aos/1176342360 · Cited by 4,814 · see citing works
Hierarchical Dirichlet Processes
Teh, Y. W., Jordan, M. I., Beal, M. J., & Blei, D. M. (2006) · Journal of the American Statistical Association · doi:10.1198/016214506000000302 · Cited by 3,445 · see citing works
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 · see citing works
Tsoumakas, G., & Katakis, I. (2007) · International Journal of Data Warehousing and Mining · doi:10.4018/jdwm.2007070101 · Cited by 2,512 · see citing works
Markov Chain Sampling Methods for Dirichlet Process Mixture Models
Neal, R. M. (2000) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2000.10474879 · Cited by 2,204 · see citing works
A Constructive Definition of Dirichlet Priors
Sethuraman, J. (1991) · doi:10.21236/ada238689 · Cited by 1,605 · see citing works
Tsoumakas, G., Katakis, I., & Vlahavas, I. P. (2009) · Springer eBooks · doi:10.1007/978-0-387-09823-4_34 · Cited by 1,466 · see citing works
Activity recognition from accelerometer data
Ravi, N., Dandekar, N., Mysore, P., & Littman, M. L. (2005) · Cited by 1,434 · see citing works
Karantonis, D. M., Narayanan, M. R., Mathie, M. J., Lovell, N. H., & Celler, B. G. (2006) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2005.856864 · Cited by 1,239 · see citing works
Data mining and knowledge discovery handbook
(2011) · Choice Reviews Online · doi:10.5860/choice.48-5729 · Cited by 1,174 · see citing works
The Experience Sampling Method
Larson, R. W., & Csíkszentmihályi, M. (2014) · Springer eBooks · doi:10.1007/978-94-017-9088-8_2 · Cited by 1,047 · see citing works
Combinatorial Stochastic Processes
Pitman, J., & Picard, J. (2006) · Springer eBooks · doi:10.1007/b11601500 · Cited by 988 · see citing works
Bouten, C. V. C., Koekkoek, K. K., Verduin, M., Kodde, R., & Janssen, J. J. (1997) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.554760 · Cited by 911 · see citing works
Shephard, R. J. (2011) · Yearbook of Sports Medicine · doi:10.1016/j.yspm.2011.03.006 · Cited by 872 · see citing works
Activity Classification Using Realistic Data From Wearable Sensors
Pärkkä, J., Ermes, M., Korpipää, P., Mäntyjärvi, J., Peltola, J., & Korhonen, I. (2006) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2005.856863 · Cited by 759 · see citing works
USC-HAD: a daily activity dataset for ubiquitous activity recognition using wearable sensors
Zhang, M., & Sawchuk, A. A. (2012) · Proceedings of the 2012 ACM Conference on Ubiquitous Computing · doi:10.1145/2370216.2370438 · Cited by 554 · see citing works
Discovery of activity patterns using topic models
Huynh, T., Fritz, M., & Schiele, B. (2008) · Ubiquitous Computing · doi:10.1145/1409635.1409638 · Cited by 505 · see citing works
Olguin, D. O., Waber, B. N., Kim, T. J., Mohan, A., Ara, K., & Pentland, A. (2008) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2008.2006638 · Cited by 417 · see citing works
Optimal Placement of Accelerometers for the Detection of Everyday Activities
Cleland, I., Kikhia, B., Nugent, C., Boytsov, A., Hallberg, J., Synnes, K., McClean, S. I., & Finlay, D. (2013) · Sensors · doi:10.3390/s130709183 · Cited by 403 · see citing works
Americas conference on information systems
Berghout, E. W., Schuurman, P., & Wingerden, D. (2009) · Cited by 383 · see citing works
Sensor Positioning for Activity Recognition Using Wearable Accelerometers
Atallah, L., Lo, B., King, R., & Yang, G.-Z. (2011) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2011.2160540 · Cited by 346 · see citing works
Duvivier, B. M. F. M., Schaper, N. C., Bremers, M. A., Crombrugge, G. V., Menheere, P. P. C. A., Kars, M., & Savelberg, H. H. C. M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055542 · Cited by 328 · see citing works
Asztalos, M., Bourdeaudhuij, I. D., & Cardon, G. (2009) · Public Health Nutrition · doi:10.1017/s1368980009992825 · Cited by 160 · see citing works
Human Activity Recognition: Accuracy across Common Locations for Wearable Sensors
õn, D. O. ́., & õn, O. ́. (2006) · Cited by 113 · see citing works
Social Sensors for Automatic Data Collection
Olguı́n, D., & Pentland, A. (2008) · Cited by 58 · see citing works
Nonparametric discovery of human routines from sensor data
Sun, F.-T., Yeh, Y.-T., Cheng, H.-T., et al. (2014) · IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom.2014.6813938 · Cited by 44 · see citing works
A Large Scale Gathering System for Activity Data with Mobile Sensors
Hattori, Y., Inoue, S., & Hirakawa, G. (2011) · International Symposium on Wearable Computers · doi:10.1109/iswc.2011.32 · Cited by 23 · see citing works
A Bayesian Nonparametric Framework for Activity Recognition Using Accelerometer Data
Nguyen, T., Gupta, S., Venkatesh, S., & Phung, D. (2014) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2014.352 · Cited by 11 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
The Experience Sampling Method on Mobile Devices
van Berkel, N., Ferreira, D., & Kostakos, V. (2018) · ACM Computing Surveys · doi:10.1145/3123988 · Cited by 432 · see citing works
Review of Wearable Devices and Data Collection Considerations for Connected Health
Vijayan, V., Connolly, J. P., Condell, J., McKelvey, N., & Gardiner, P. (2021) · Sensors · doi:10.3390/s21165589 · Cited by 435 · see citing works
- Authors
- Nguyen, T., Gupta, S., Venkatesh, S., & Phung, D.
- Affiliations
- RMIT University (AU)
- Deakin University (AU)
- Corresponding author
- Nguyen, Thuong
- Venue
- Pattern Recognition Letters
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 70
- Pages
- 52-58
- ISSN
- 0167-8655 (ISSN-L)
- OpenAlex
- W2177609784
- Cited by
- 8
- References
- 31
- Citations by year
- 2025: 1 · 2021: 1 · 2019: 2 · 2017: 2 · 2016: 2
- FWCI
- 1.16
- Type
- journal article
- Language
- en
- Open access
- green
- figshare.com
- Licence
- Locations
- Pattern Recognition Letters (publishedVersion)
- RMIT Research Repository (RMIT University Library) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Figshare (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Keywords
- accelerometer signals, physical activity monitoring, movement intensity, hierarchical Dirichlet process, Bayesian nonparametric models, ecological momentary assessment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
