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
Overview
Integrity signals
Registry
Cites
Statistics
Verification
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?
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
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
Lu, H., Pan, W., Lane, N. D., Choudhury, T., & Campbell, A. T. (2009) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/1555816.1555834 · Cited by 581
A Survey on Activity Detection and Classification Using Wearable Sensors
Cornacchia, M., Ozcan, K., Zheng, Y., & Velipasalar, S. (2016) · IEEE Sensors Journal · doi:10.1109/jsen.2016.2628346 · Cited by 427
Gesture spotting with body-worn inertial sensors to detect user activities
Junker, H., Amft, O., Lukowicz, P., & Tröster, G. (2007) · Pattern Recognition · doi:10.1016/j.patcog.2007.11.016 · Cited by 361
Self-citationMAHI: investigation of social scaffolding for reflective thinking in diabetes management
Mamykina, L., Mynatt, E., Davidson, P., & Greenblatt, D. (2008) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1357054.1357131 · Cited by 355
BodyScope: a wearable acoustic sensor for activity recognition
Yatani, K., & Truong, K. N. (2012) · Proceedings of the 2012 ACM Conference on Ubiquitous Computing · doi:10.1145/2370216.2370269 · Cited by 310
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
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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