The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Using acceleration measurements for activity recognition: An effective learning algorithm for constructing neural classifiers
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A direct adaptive method for faster backpropagation learning: the RPROP algorithm
Riedmiller, M., & Braun, H. (2002) · IEEE International Conference on Neural Networks · doi:10.1109/icnn.1993.298623 · Cited by 3,917
Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions
Maurer, U., Smailagic, A., Siewiorek, D. P., & Deisher, M. (2006) · doi:10.21236/ada534437 · Cited by 266
Cited by
(2013) · RECERCAT (Consorci de Serveis Universitaris de Catalunya) · Cited by 1,959
Qiu, S., Zhao, H., Jiang, N., Wang, Z., Liu, L., An, Y., Zhao, H., Miao, X., Liu, R., & Fortino, G. (2022) · Information Fusion · doi:10.1016/j.inffus.2021.11.006 · Cited by 671
Direct measurement of human movement by accelerometry
Godfrey, A., Conway, R., Meagher, D., & ÓLaighin, G. (2008) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2008.09.005 · Cited by 591
Machine learning in medical applications: a review of state-of-the-art methods
Shehab, M., Abualigah, L., Shambour, Q., Abu-Hashem, M. A., Shambour, M. K. Y., Alsalibi, A. I., & Gandomi, A. H. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105458 · Cited by 542
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
Metadata
- Authors
- Yang, J.-Y., Wang, J.-S., & Chen, Y.-P.
- Venue
- Pattern Recognition Letters
- Publisher
- Elsevier BV
- Published
- 2008-12
- Volume
- 29
- Issue
- 16
- Pages
- 2213-2220
- ISSN
- 0167-8655 (ISSN-L)
- OpenAlex
- W2068006147
- Cited by
- 335
- References
- 2
- FWCI
- 18.14
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Using acceleration measurements for activity recognition: An effective learning algorithm for constructing neural classifiers. https://app.cochat.ai/papers/10.1016/j.patrec.2008.08.002
- The paper
- Yang, J.-Y., Wang, J.-S., & Chen, Y.-P. (2008). Using acceleration measurements for activity recognition: An effective learning algorithm for constructing neural classifiers. Pattern Recognition Letters. https://doi.org/10.1016/j.patrec.2008.08.002
Data sources
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.