The DOI matches its Crossref record; 34 of the 35 references it cites were found in a registry or an index.
Analysis of Chewing Sounds for Dietary Monitoring
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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?
In the citing paper
“Eating behaviours are also analysed using audio collected from smartwatches and earables [47,51,85].”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [47]
In the citing paper
“In addition to the normal airborne sound, bone conducted sounds collected via wearables have also been analysed for health application, which is generally collected via earables or sensors placed near neck.”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [47]
Citations
Cites
Witten, I. H. (2008) · Cited by 9,143
Witten, I. H., & Frank, E. (2002) · ACM SIGMOD Record · doi:10.1145/507338.507355 · Cited by 5,176
Inferring Activities from Interactions with Objects
Philipose, M., Fishkin, K. P., Perkowitz, M., Patterson, D. J., Fox, D., Kautz, H., & Hähnel, D. (2004) · IEEE Pervasive Computing · doi:10.1109/mprv.2004.7 · Cited by 876
Provost, F. J., & Fawcett, T. E. (1997) · Cited by 723
THE PERCEPTION OF FOOD TEXTURE ‐ THE PHILOSOPHY OF THE BREAKDOWN PATH
Hutchings, J. B., & Lillford, P. J. (1988) · Journal of Texture Studies · doi:10.1111/j.1745-4603.1988.tb00928.x · Cited by 569
Multi-Sensor Context-Awareness in Mobile Devices and Smart Artifacts
Gellersen, H. W., Schmidt, A., & Beigl, M. (2002) · Mobile Networks and Applications · doi:10.1023/a:1016587515822 · Cited by 437
Mediacups: experience with design and use of computer-augmented everyday artefacts
Beigl, M., Gellersen, H. W., & Schmidt, A. (2001) · Computer Networks · doi:10.1016/s1389-1286(00)00180-8 · Cited by 268
Classification of general audio data for content-based retrieval
Li, D., Sethi, I. K., Dimitrova, N., & McGee, T. (2001) · Pattern Recognition Letters · doi:10.1016/s0167-8655(00)00119-7 · Cited by 252
Aware technologies for aging in place: understanding user needs and attitudes
Mynatt, E. D., Melenhorst, A.-S., Fisk, A.-D., & Rogers, W. A. (2004) · IEEE Pervasive Computing · doi:10.1109/mprv.2004.1316816 · Cited by 234
Computational auditory scene recognition
Peltonen, V., Tuomi, J., Klapuri, A. P., Huopaniemi, J., & Sorsa, T. (2002) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2002.5745009 · Cited by 217
Flagged first, then by citations
1 of the 35 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann, San Francisco (1999)
Cited by
Sorted by citations
Items 201–216 of 216
Approaches to Facilitating Analysis of Health and Wellness Data
Mamykina, L., & Mynatt, E. D. (2009) · International Journal of Advanced Pervasive and Ubiquitous Computing · doi:10.4018/japuc.2009040103
Packet-based cellular systems with overprovisioned IP backbone
Yang, S., & Defee, I. (2002) · International Conference on Communications · doi:10.1109/icc.2001.936591
A mobile context monitoring platform for pervasive computing environments
Lee, Y., Min, C., Ju, Y., Pushp, S., & Song, J. (2011) · IEEE International Conference on Digital Ecosystems and Technologies · doi:10.1109/dest.2011.5936591
A BIG HEALTH APPLICATION USED IN SMART CLOTH & GLASS
Sudersanan, A. (2017) · International Journal of Advanced Research in Computer Science · doi:10.26483/ijarcs.v8i9.4943
Fuzzy classifier based ingestive monitor
Sundari, K. T. (2019) · doi:10.31295/ijecs.v2n1.61
A Survey of Automatic Methods for Nutritional AssessmentPreprint
Brenna, L., Johansen, H. D., & Johansen, D. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1907.07245 · Cited by 2
Towards the Design and Evaluation of Robust Audio-Sensing Systems
Mathur, A., Isopoussu, A., Kawsar, F., Smith, R. E., Bianchi‐Berthouze, N., & Lane, N. D. (2019) · Springer series in adaptive environments · doi:10.1007/978-3-030-13001-5_4
Improving state estimation through projection post-processing for activity recognition in football.Preprint
Ciszewski, M. G., Söhl, J., & Jongbloed, G. (2021) · arXiv (Cornell University)
Audio-Based Onset Detection applied to Chewing Cycle Segmentation
Kopyto, D., Zhang, R., & Amft, O. (2021) · International Symposium on Wearable Computers · doi:10.1145/3460421.3478819
Self-citationKopyto, D., Uhlenberg, L., Zhang, R., Stonawski, V., Horndasch, S., & Amft, O. (2021) · Springer eBooks · doi:10.1007/978-3-030-58080-3_213-1
Self-citationTowards Socially Acceptable Food Type Recognition
Wang, J., Guan, J., Hong, Y. A., Xue, H., Wang, S., Liu, Z., Ren, B., & Zhou, G. (2022) · International Conference on Mobility, Sensing and Networking (MSN) · doi:10.1109/msn57253.2022.00110
LEIB-RHYTHM: An Auditory-Based Intervention for Enhancing Rhythmic Chewing Perception
Zheng, R., Xu, X., & Wan, T. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-93227-4_30
A Knife and a Cutting Board as Implicit User Interface - Towards Context-Aware Kitchen Utilities
Kranz, M., Maldonado, A., Hörnler, B., Rusu, R. B., Beetz, M., Rigoll, G., & Schmidt, A. (2007) · International Conference on Tangible, Embedded, and Embodied Interaction (TEI)
Human activity recognition for pervasive interaction
Pham, C. (2012)
Metadata
- Authors
- Amft, O., Stäger, M., Lukowicz, P., & Tröster, G.
- Affiliations
- ETH Zurich (CH)
- UMIT TIROL - Private University for Health Sciences and Health Technology (AT)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2005
- Pages
- 56-72
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2162226056
- Cited by
- 216
- References
- 35
- Citations by year
- 2025: 3 · 2024: 7 · 2023: 5 · 2022: 8 · 2021: 16 · 2020: 21 · 2019: 15 · 2018: 13 · 2017: 19 · 2016: 19 · 2015: 15 · 2014: 5 · 2013: 8 · 2012: 11
- FWCI
- 5.89
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- TU/e Research Portal (publishedVersion)
- TU/e Research Portal (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Phonocardiography and Auscultation Techniques
- Health Sciences › Health Professions › Health Information Management › Innovation in Digital Healthcare Systems
- Keywords
- dietary monitoring, eating detection, unobtrusive sensing, ubiquitous systems, cardiovascular disease prevention
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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.
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