Gait phase analysis based on a Hidden Markov Model
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Using HMM, hidden states can be inferred from other observations in a sequence of data.
“Using this model the hidden states can be inferred from the other observations in sequence of data [80].”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [80]
Cites
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743 · see citing works
An introduction to hidden Markov models
Rabiner, L., & Juang, B. (1986) · IEEE ASSP Magazine · doi:10.1109/massp.1986.1165342 · Cited by 4,775 · see citing works
Jordan, M. I. (1998) · Springer eBooks · doi:10.1007/978-94-011-5014-9 · Cited by 2,449 · see citing works
Gene prediction with a hidden Markov model and a new intron submodel
Stanke, M., & Waack, S. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg1080 · Cited by 1,643 · see citing works
Perry, J., Slac, K., & Davids, J. R. (1992) · Journal of Pediatric Orthopaedics · doi:10.1097/01241398-199211000-00023 · Cited by 1,125 · see citing works
Gait Analysis Using a Shoe-Integrated Wireless Sensor System
Bamberg, S. J. M., Benbasat, A. Y., Scarborough, D. M., Krebs, D. E., & Paradiso, J. A. (2008) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2007.899493 · Cited by 738 · see citing works
Parametric hidden Markov models for gesture recognition
Wilson, A. D., & Bobick, A. (1999) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.790429 · Cited by 574 · see citing works
A reliable gait phase detection system
Pappas, I. P. I., Popović, M. R., Keller, T., Dietz, V., & Morari, M. (2001) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/7333.928571 · Cited by 497 · see citing works
A Gait Monitoring System Based on Air Pressure Sensors Embedded in a Shoe
Kong, K., & Tomizuka, M. (2009) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2008.2008803 · Cited by 302 · see citing works
Self-citationOnline, interactive learning of gestures for human/robot interfaces
Lee, C., & Xu, Y. (2002) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.1996.509165 · Cited by 191 · see citing works
Shoe-integrated sensor system for wireless gait analysis and real-time feedback
Morris, S. J., & Paradiso, J. A. (2002) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2002.1053379 · Cited by 177 · see citing works
Medicare, A. I., & Lohr, K. N. (1990) · Cited by 73 · see citing works
A mobile gait monitoring system for gait analysis
Bae, J., Kong, K., Byl, N. N., et al. (2009) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2009.5209621 · Cited by 49 · see citing works
Self-citationDetection of abnormalities in a human gait using smart shoes
Kong, K., Bae, J., & Tomizuka, M. (2008) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.776003 · Cited by 22 · see citing works
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Banaee, H., Ahmed, M., & Loutfi, A. (2013) · Sensors · doi:10.3390/s131217472 · Cited by 452 · see citing works
Mannini, A., Trojaniello, D., Cereatti, A., & Sabatini, A. (2016) · Sensors · doi:10.3390/s16010134 · Cited by 242 · see citing works
- Authors
- Bae, J., & Tomizuka, M.
- Affiliations
- University of California, Berkeley (US)
- Corresponding author
- Bae, Joonbum
- Venue
- Mechatronics
- Publisher
- Elsevier BV
- Published
- 2011-09
- Volume
- 21
- Issue
- 6
- Pages
- 961-970
- ISSN
- 0957-4158 (ISSN-L)
- OpenAlex
- W2056873772
- Cited by
- 106
- References
- 14
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 3 · 2023: 5 · 2022: 7 · 2021: 9 · 2020: 7 · 2019: 12 · 2018: 11 · 2017: 7 · 2016: 8 · 2015: 8 · 2014: 9 · 2013: 6 · 2012: 4
- FWCI
- 3.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Mechatronics (publishedVersion)
- Scholarworks@UNIST (Ulsan National Institute of Science and Technology) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Gait Recognition and Analysis
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Physical Sciences › Engineering › Biomedical Engineering › Lower Extremity Biomechanics and Pathologies
- Keywords
- hidden Markov models, gait rehabilitation, smart shoes, ground reaction force, posterior probability, gait analysis
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.
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