The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Comparative study on classifying human activities with miniature inertial and magnetic sensors
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Citations
Cites
LIBSVM: A library for support vector machines
Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918
Clinical Applications of Sensors for Human Posture and Movement Analysis: A Review
Wong, W. Y., Wong, M. S., & Lo, K. H. (2007) · Prosthetics & Orthotics International · doi:10.1080/03093640600983949 · Cited by 193
Active tremor compensation in microsurgery
Ang, W. T., Pradeep, P. K., & Riviere, C. N. (2005) · The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/iembs.2004.1403784 · Cited by 61 · cited 1×
“For several decades, inertial sensors have been used for navigation of aircraft [1,2], ships, land vehicles, and robots [3–5], for state estimation and dynamic modeling of legged robots [6,7], for shock and vibration analysis in the automotive industry, and in telesurgery [8,9].”
Background
Cited by
Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances
Zhang, S., Li, Y., Zhang, S., Shahabi, F., Xia, S., Deng, Y., & Alshurafa, N. (2022) · Sensors · doi:10.3390/s22041476 · Cited by 625
“6 50–200 Hz 37 Daily & Sports Activities [19] Locomotion 9D IMU 19 25 Hz 37 MHEALTH [30, 31] Locomotion & gesture 9D IMU & ECG 12 50 Hz 33 Opportunity [59] Locomotion & gesture 9D IMU 16 50 Hz 32 PAMAP2 [228] Locomotion & activities 9D IMU & HR monitor 18 100 Hz 32 Daphnet [23] Freezing of gait 3D Acc.”
BackgroundMethodDemrozi, F., Pravadelli, G., Bihorac, A., & Rashidi, P. (2020) · IEEE Access · doi:10.1109/access.2020.3037715 · Cited by 368
Wearable Inertial Sensors for Human Motion Analysis: A Review
Lopez-Nava, I. H., & Munoz-Melendez, A. (2016) · IEEE Sensors Journal · doi:10.1109/jsen.2016.2609392 · Cited by 263
A Comprehensive Analysis on Wearable Acceleration Sensors in Human Activity Recognition
Janidarmian, M., Roshan Fekr, A., Radecka, K., & Zilic, Z. (2017) · Sensors · doi:10.3390/s17030529 · Cited by 217
Benchmarking TinyML Systems: Challenges and Direction
Banbury, C. R., Reddi, V. J., Lam, M., Fu, W., Fazel, A., Holleman, J., Huang, X., Hurtado, R., Kanter, D., Lokhmotov, A., et al. (2020) · arXiv · doi:10.48550/arxiv.2003.04821 · Cited by 216
Metadata
- Authors
- Altun, K., Barshan, B., & Tunçel, O.
- Venue
- Pattern Recognition
- Publisher
- Elsevier BV
- Published
- 2010-10
- Volume
- 43
- Issue
- 10
- Pages
- 3605-3620
- ISSN
- 0031-3203 (ISSN-L)
- OpenAlex
- W2123504417
- Cited by
- 564
- References
- 3
- FWCI
- 18.80
- 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.
