Analysis of Chewing Sounds for Dietary Monitoring

Data Mining

Witten, I. H. (2008) · Cited by 9,143

Data mining

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

Analysis and visualization of classifier performance: comparison under imprecise class and cost distributions

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

SoundSense

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

MAHI: 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

DeepEar

Lane, N. D., Georgiev, P., & Qendro, L. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2804262 · Cited by 310

Fit4life: the design of a persuasive technology promoting healthy behavior and ideal weight

Purpura, S., Schwanda, V., Williams, K., Stubler, W., & Sengers, P. (2011) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979003 · Cited by 264

Platemate

Noronha, J., Hysen, E., Zhang, H., & Gajos, K. Z. (2011) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/2047196.2047198 · Cited by 247

SpiroSmart: using a microphone to measure lung function on a mobile phone

Larson, E. C., Goel, M., Boriello, G., Heltshe, S., Rosenfeld, M., & Patel, S. N. (2012) · Proceedings of the 2012 ACM Conference on Ubiquitous Computing · doi:10.1145/2370216.2370261 · Cited by 245

Recognition of dietary activity events using on-body sensors

Amft, O., & Tröster, G. (2008) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2007.11.007 · Cited by 220

SeeMon

Kang, S., Lee, J., Jang, H., Lee, H., Lee, Y., Park, S., Park, T., & Song, J. (2008) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/1378600.1378630 · Cited by 185

EarBit

Bedri, A., Li, R. Z., Haynes, M., Kosaraju, R. P., Grover, I., Prioleau, T., Beh, M. Y., Goel, M., Starner, T. E., & Abowd, G. D. (2017) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3130902 · Cited by 191

On-Body Sensing Solutions for Automatic Dietary Monitoring

Amft, O., & Tröster, G. (2009) · IEEE Pervasive Computing · doi:10.1109/mprv.2009.32 · Cited by 175

Wearable Food Intake Monitoring Technologies: A Comprehensive Review

Vu, T., Lin, F., Alshurafa, N. I., & Xu, W. (2017) · Computers · doi:10.3390/computers6010004 · Cited by 175

Rethinking the Mobile Food Journal

Cordeiro, F., Bales, E., Cherry, E., & Fogarty, J. A. (2015) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702154 · Cited by 166

BodyBeat

Rahman, T., Adams, A. T., Zhang, M., Cherry, E., Zhou, B., Peng, H., & Choudhury, T. (2014) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/2594368.2594386 · Cited by 159

A survey on big data-driven digital phenotyping of mental health

Liang, Y., Zheng, X., & Zeng, D. D. (2019) · Information Fusion · doi:10.1016/j.inffus.2019.04.001 · Cited by 164

Active Capacitive Sensing: Exploring a New Wearable Sensing Modality for Activity Recognition

Cheng, J., Amft, O., & Lukowicz, P. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-12654-3_19 · Cited by 154

UbiComp 2005: Ubiquitous Computing

(2005) · Lecture notes in computer science · doi:10.1007/11551201 · Cited by 143

Earables for Personal-Scale Behavior Analytics

Kawsar, F., Min, C., Mathur, A., & Montanari, A. (2018) · IEEE Pervasive Computing · doi:10.1109/mprv.2018.03367740 · Cited by 141

A roadmap on smart textiles

Schwarz, A., Langenhove, L. V., Guermonprez, P., & Deguillemont, D. (2010) · Textile Progress · doi:10.1080/00405160903465220 · Cited by 130

Monitoring Chewing and Eating in Free-Living Using Smart Eyeglasses

Zhang, R., & Amft, O. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2698523 · Cited by 127

Bite Weight Prediction From Acoustic Recognition of Chewing

Amft, O., Kusserow, M., & Troster, G. (2009) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2009.2015873 · Cited by 123

An Intelligent Food-Intake Monitoring System Using Wearable Sensors

Liu, J., Johns, E., Atallah, L., Pettitt, C., Lo, B. P. L., Frost, G. S., & Yang, G. (2012) · Wearable and Implantable Body Sensor Networks · doi:10.1109/bsn.2012.11 · Cited by 121

A wearable earpad sensor for chewing monitoring

Amft, O. (2010) · Proceedings of IEEE Sensors/Proceedings of IEEE Sensors ... · doi:10.1109/icsens.2010.5690449 · Cited by 117

Influence of immediate predation risk by lions on the vigilance of prey of different body size

Périquet, S., Todd‐Jones, L., Valeix, M., Stapelkamp, B., Elliot, N. B., Wijers, M., Pays, O., Fortin, D., Madzikanda, H., Fritz, H., et al. (2012) · Behavioral Ecology · doi:10.1093/beheco/ars060 · Cited by 115

A Review of Emerging Technologies for the Management of Diabetes Mellitus

Zarkogianni, K., Litsa, E. E., Mitsis, K., Wu, P.-Y., Kaddi, C. D., Cheng, C., Wang, M. D., & Nikita, K. S. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2470521 · Cited by 115

The Diet-Aware Dining Table: Observing Dietary Behaviors over a Tabletop Surface

Chang, K.-H., Liu, S.-Y., Chu, H.-H., Hsu, J. Y.-J., Chen, C., Lin, T.-Y., Chen, C., & Polly Huang, B. (2006) · Lecture notes in computer science · doi:10.1007/11748625_23 · Cited by 111

Food intake monitoring: an acoustical approach to automated food intake activity detection and classification of consumed food

Päßler, S., Wolff, M., & Fischer, W. (2012) · Physiological Measurement · doi:10.1088/0967-3334/33/6/1073 · Cited by 110

Automated estimation of food type and amount consumed from body-worn audio and motion sensors

Mirtchouk, M., Merck, C., & Kleinberg, S. (2016) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2971648.2971677 · Cited by 101

Auracle

Bi, S., Wang, T., Tobias, N., Nordrum, J., Wang, S., Halvorsen, G., Sen, S., Peterson, R., Odame, K. M., Caine, K. E., et al. (2018) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3264902 · Cited by 100

Methods for Detection and Classification of Normal Swallowing from Muscle Activation and Sound

Amft, O., & Tröster, G. (2006) · doi:10.1109/pcthealth.2006.361624 · Cited by 100

Induced or routine vigilance while foraging

Blanchard, P., & Fritz, H. (2007) · Oikos · doi:10.1111/j.0030-1299.2007.15799.x · Cited by 95

A Novel Chewing Detection System Based on PPG, Audio, and Accelerometry

Papapanagiotou, V., Diou, C., Zhou, L., van den Boer, J., Mars, M., & Delopoulos, A. N. (2016) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2625271 · Cited by 91

The case for smartwatch-based diet monitoring

Sen, S., Subbaraju, V., Misra, A., Balan, R. K., & Lee, Y. (2015) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2015.7134103 · Cited by 89

Food Intake Monitoring: Automated Chew Event Detection in Chewing Sounds

Päßler, S., & Fischer, W. (2013) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2013.2268663 · Cited by 88

FitByte: Automatic Diet Monitoring in Unconstrained Situations Using Multimodal Sensing on Eyeglasses

Bedri, A., Li, D., Khurana, R., Bhuwalka, K., & Goel, M. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376869 · Cited by 83

Making Regular Eyeglasses Smart

Amft, O., Wahl, F., Ishimaru, S., & Kunze, K. S. (2015) · IEEE Pervasive Computing · doi:10.1109/mprv.2015.60 · Cited by 76

Smart table surface: A novel approach to pervasive dining monitoring

Zhou, B., Cheng, J., Sundholm, M., Reiss, A., Huang, W., Amft, O., & Lukowicz, P. (2015) · IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom.2015.7146522 · Cited by 75

Diet eyeglasses: Recognising food chewing using EMG and smart eyeglasses

Zhang, R., Bernhart, S., & Amft, O. (2016) · Wearable and Implantable Body Sensor Networks · doi:10.1109/bsn.2016.7516224 · Cited by 71

A Scalable and Energy-Efficient Context Monitoring Framework for Mobile Personal Sensor Networks

Kang, S., Lee, J., Jang, H., Lee, Y., Park, S., & Song, J. (2009) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2009.154 · Cited by 71

Unobtrusive and Wearable Systems for Automatic Dietary Monitoring

Prioleau, T., Moore, E., & Ghovanloo, M. (2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2631246 · Cited by 69

Wearable context-aware food recognition for calorie monitoring

Shroff, G., Smailagic, A., & Siewiorek, D. P. (2008) · Proceedings · doi:10.1109/iswc.2008.4911602 · Cited by 64

iHear Food: Eating Detection Using Commodity Bluetooth Headsets

Gao, Y., Zhang, N., Wang, H., Ding, X., Ye, X., Chen, G., & Cao, Y. (2016) · 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) · doi:10.1109/chase.2016.14 · Cited by 63

Feasibility of identifying eating moments from first-person images leveraging human computation

Thomaz, E., Parnami, A., Essa, I. A., & Abowd, G. D. (2013) · doi:10.1145/2526667.2526672 · Cited by 62

Predicting "About-to-Eat" Moments for Just-in-Time Eating Intervention

Rahman, T., Czerwinski, M. P., Gilad-Bachrach, R., & Johns, P. (2016) · International Conference on Digital Health · doi:10.1145/2896338.2896359 · Cited by 64

Wearable Eating Habit Sensing System Using Internal Body Sound

Shuzo, M., Komori, S., Takashima, T., Lopez, G. F., Tatsuta, S., Yanagimoto, S., Warisawa, S., Delaunay, J., & Yamada, I. (2010) · Journal of Advanced Mechanical Design Systems and Manufacturing · doi:10.1299/jamdsm.4.158 · Cited by 62

Exploring audio and kinetic sensing on earable devices

Min, C., Mathur, A., & Kawsar, F. (2018) · doi:10.1145/3211960.3211970 · Cited by 56

Activity recognition and nutrition monitoring in every day situations with a textile capacitive neckband

Cheng, J., Zhou, B., Kunze, K. S., Rheinländer, C. C., Wille, S., Wehn, N., Weppner, J., & Lukowicz, P. (2013) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2494091.2494143 · Cited by 55

Mic2Mic

Mathur, A., Isopoussu, A., Kawsar, F., Bianchi‐Berthouze, N., & Lane, N. D. (2019) · ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) · doi:10.1145/3302506.3310398 · Cited by 54

Detecting Mastication

Bedri, A., Verlekar, A., Thomaz, E., Avva, V., & Starner, T. E. (2015) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/2818346.2820767 · Cited by 53

Recognizing Eating from Body-Worn Sensors

Mirtchouk, M., Lustig, D., Smith, A., Ching, I., Zheng, M., & Kleinberg, S. (2017) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3131894 · Cited by 53

A Device for Detecting and Counting Bites of Food Taken by a Person during Eating

Dong, Y., Hoover, A. W., & Muth, E. R. (2009) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2009.29 · Cited by 52

hEARt: Motion-resilient Heart Rate Monitoring with In-ear Microphones

Butkow, K.-J., Dang, T., Ferlini, A., Ma, D., & Cecilia Mascolo, C. (2023) · IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom56429.2023.10099317 · Cited by 50

Context awareness in a handheld exercise agent

Bickmore, T., Mauer, D., & Brown, T. (2008) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2008.05.004 · Cited by 52

Bitey: an exploration of tooth click gestures for hands-free user interface control

Ashbrook, D., Tejada, C., Mehta, D., Jiminez, A., Muralitharam, G., Gajendra, S., & Tallents, R. (2016) · Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services · doi:10.1145/2935334.2935389 · Cited by 49

Stick it in your ear

Bedri, A., Byrd, D., Presti, P., Sahni, H., Gue, Z., & Starner, T. E. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2800835.2807933 · Cited by 48

Your Glasses Know Your Diet: Dietary Monitoring Using Electromyography Sensors

Huang, Q., Wang, W., & Zhang, Q. (2017) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2656151 · Cited by 48

Acoustical Method for Objective Food Intake Monitoring Using a Wearable Sensor System

Päßler, S., & Fischer, W. (2011) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.4108/icst.pervasivehealth.2011.246029 · Cited by 47

A wearable system for detecting eating activities with proximity sensors in the outer ear

Bedri, A., Verlekar, A., Thomaz, E., Avva, V., & Starner, T. E. (2015) · Proceedings · doi:10.1145/2802083.2808411 · Cited by 45

Head Motion Tracking Through in-Ear Wearables

Ferlini, A., Montanari, A., Cecilia Mascolo, C., & Harle, R. K. (2019) · doi:10.1145/3345615.3361131 · Cited by 45

Probabilistic parsing of dietary activity events

Amft, O., Kusserow, M., & Tröster, G. (2007) · Springer eBooks · doi:10.1007/978-3-540-70994-7_41 · Cited by 43

Sensor-embedded teeth for oral activity recognition

Li, C., Chen, Y., Chen, W.-J., Polly Huang, B., & Chu, H.-H. (2013) · International Symposium on Wearable Computers · doi:10.1145/2493988.2494352 · Cited by 43

I Hear You Eat and Speak: Automatic Recognition of Eating Condition and Food Type, Use-Cases, and Impact on ASR Performance

Hantke, S., Weninger, F. J., Kurle, R., Ringeval, F., Batliner, A. M., Mousa, A. E.-D., & Schuller, B. W. (2016) · PLoS ONE · doi:10.1371/journal.pone.0154486 · Cited by 41

Computational method for segmentation and classification of ingestive sounds in sheep

Milone, D. H., Rufiner, H. L., Galli, J. R., Laca, E. A., & Cangiano, C. A. (2008) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2008.10.004 · Cited by 40

Multimodality Sensing for Eating Recognition

Merck, C., Maher, C., Mirtchouk, M., Zheng, M., Huang, Y., & Kleinberg, S. (2016) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.4108/eai.16-5-2016.2263281 · Cited by 38

Toward a Wearable Sensor for Eating Detection

Bi, S., Wang, T., Davenport, E., Peterson, R., Halter, R. J., Sorber, J. M., & Kotz, D. F. (2017) · Workshop on Wearable Systems and Applications (WearSys) · doi:10.1145/3089351.3089355 · Cited by 38

Learning deep representations for video-based intake gesture detection

Rouast, P. V., & Adam, M. T. P. (2020) · Figshare · Cited by 38

Analysis of Health Consumers' Behavior Using Self-Tracker for Activity, Sleep, and Diet

Kim, J. (2014) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2013.0282 · Cited by 38

Learning Deep Representations for Video-Based Intake Gesture Detection

Rouast, P. V., & Adam, M. T. P. (2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2019.2942845 · Cited by 42

Sensing Technologies and the Player-Middleware for Context-Awareness in Kitchen Environments

Kranz, M., Schmidt, A., Hörnler, B., Rigoll, G., Rusu, R. B., Maldonado, A., & Beetz, M. (2007) · International Conference on Networked Sensing Systems · doi:10.1109/inss.2007.4297417 · Cited by 37

Context-aware kitchen utilities

Kranz, M., Schmidt, A., Maldonado, A., Rusu, R. B., Beetz, M., Hörnler, B., & Rigoll, G. (2007) · International Conference on Tangible, Embedded, and Embodied Interaction (TEI) · doi:10.1145/1226969.1227013 · Cited by 36

EarHealth

Jin, Y., Gao, Y., Guo, X., Wen, J., Li, Z., & Jin, Z. (2022) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/3498361.3538935 · Cited by 36

Assisting Food Journaling with Automatic Eating Detection

Ye, X., Chen, G., Gao, Y., Wang, H., & Cao, Y. (2016) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/2851581.2892426 · Cited by 34

Food object recognition using a mobile device: Evaluation of currently implemented systems

Knez, S., & Šajn, L. (2020) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2020.03.017 · Cited by 34

Automatic Food Intake Monitoring Based on Chewing Activity: A Survey

Selamat, N. A., & Ali, S. H. M. (2020) · IEEE Access · doi:10.1109/access.2020.2978260 · Cited by 33

A comprehensive review of the use of sensors for food intake detection

He, S., Li, S., Nag, A., Feng, S., Han, T., Mukhopadhyay, S. C., & Powell, W. (2020) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2020.112318 · Cited by 33

Smart-U: Smart Utensils Know what You Eat

Huang, Q., Yang, Z., & Zhang, Q. (2018) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom.2018.8486266 · Cited by 31

Human-centred artificial intelligence for mobile health sensing: challenges and opportunities

Dang, T., Spathis, D., Ghosh, A., & Mascolo, C. (2023) · Royal Society Open Science · doi:10.1098/rsos.230806 · Cited by 30

Eating detection and chews counting through sensing mastication muscle contraction

Wang, S., Zhou, G., Ma, Y., Hu, L., Chen, Z., Chen, Y., Zhao, H., & Jung, W. (2018) · Smart Health · doi:10.1016/j.smhl.2018.07.004 · Cited by 30

BreathLive

Huang, C., Chen, H., Yang, L., & Zhang, Q. (2018) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3191744 · Cited by 30

Conductive rubber electrodes for earphone-based eye gesture input interface

Manabe, H., Fukumoto, M., & Yagi, T. (2014) · Personal and Ubiquitous Computing · doi:10.1007/s00779-014-0818-8 · Cited by 29

OREBA: A Dataset for Objectively Recognizing Eating Behavior and Associated Intake

Rouast, P. V., Heydarian, H., Adam, M. T. P., & Rollo, M. E. (2020) · IEEE Access · doi:10.1109/access.2020.3026965 · Cited by 31

ERICA

Radhakrishnan, M., Rathnayake, D., Han, O. K., Hwang, I., & Misra, A. (2020) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/3384419.3430732 · Cited by 29

Earable RCC: Development of an Earphone-Type Reliable Chewing-Count Measurement Device

Taniguchi, K., Kondo, H., Tanaka, T., & Nishikawa, A. (2018) · Journal of Healthcare Engineering · doi:10.1155/2018/6161525 · Cited by 27

Investigating Preferred Food Description Practices in Digital Food Journaling

Silva, L. M., & Epstein, D. A. (2021) · Designing Interactive Systems Conference · doi:10.1145/3461778.3462145 · Cited by 26

Food Watch: Detecting and Characterizing Eating Episodes through Feeding Gestures

Zhang, S., Alharbi, R., Stogin, W., Pourhomayoun, M., Pfammatter, A. F., Spring, B. J., & Alshurafa, N. I. (2017) · International Conference on Body Area Networks · doi:10.4108/eai.15-12-2016.2267793 · Cited by 25

Automatic Dietary Monitoring Using Wearable Accessories

Schiboni, G., & Amft, O. (2017) · Springer eBooks · doi:10.1007/978-3-319-69362-0_13 · Cited by 26

An evaluation of heart rate monitoring with in-ear microphones under motion

Butkow, K.-J., Dang, T., Ferlini, A., Ma, D., Liu, Y., & Cecilia Mascolo, C. (2024) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2024.101913 · Cited by 25

Bite glasses

Zhang, R., & Amft, O. (2016) · ACM International Symposium on Wearable Computers (ISWC) · doi:10.1145/2971763.2971799 · Cited by 25

Pervasive Computing

Cheng, J., Amft, O., Lukowicz, P., Floreen, P., Kruger, A., & Spasojevic, M. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-12654-3 · Cited by 25

A comparison between audio and IMU data to detect chewing events based on an earable device

Lotfi, R., Tzanetakis, G., Eskicioglu, R., & Irani, P. (2020) · Proceedings of the 11th Augmented Human International Conference · doi:10.1145/3396339.3396362 · Cited by 24

Smart medical textiles for monitoring patients with heart conditions

Amft, O., & Habetha, J. (2007) · Elsevier eBooks · doi:10.1533/9781845692933.2.275 · Cited by 24

Transforming Big Data into AI‐ready data for nutrition and obesity research

Thomas, D. M., Knight, R. D., Gilbert, J. A., Cornelis, M. C., Gantz, M. G., Burdekin, K., Cummiskey, K., Sumner, S., Pathmasiri, W., Sazonov, E. E., et al. (2024) · Obesity · doi:10.1002/oby.23989 · Cited by 24

Retrieval and Timing Performance of Chewing-Based Eating Event Detection in Wearable Sensors

Zhang, R., & Amft, O. (2020) · Sensors · doi:10.3390/s20020557 · Cited by 24

Smartwatch-Based Eating Detection: Data Selection for Machine Learning from Imbalanced Data with Imperfect Labels

Stankoski, S., Jordan, M., Gjoreski, H., & Luštrek, M. (2021) · Sensors · doi:10.3390/s21051902 · Cited by 24

u-BabSang: a context-aware food recommendation system

Oh, Y., Choi, A., & Woo, W. (2009) · The Journal of Supercomputing · doi:10.1007/s11227-009-0314-5 · Cited by 24

Recognition of cooking activities through air quality sensor data for supporting food journaling

Gerina, F., Massa, S. M., Moi, F., Recupero, D. R., & Riboni, D. (2020) · Human-centric Computing and Information Sciences · doi:10.1186/s13673-020-00235-9 · Cited by 23

Conductive rubber electrodes for earphone-based eye gesture input interface

Manabe, H., Fukumoto, M., & Yagi, T. (2013) · International Symposium on Wearable Computers · doi:10.1145/2493988.2494329 · Cited by 23

A novel approach for chewing detection based on a wearable PPG sensor

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