{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T12:19:26Z","timestamp":1767183566533,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,22]],"date-time":"2020-11-22T00:00:00Z","timestamp":1606003200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Science and Technology, R.O.C","award":["109-2221-E-010-005-"],"award-info":[{"award-number":["109-2221-E-010-005-"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Fluid intake is important for people to maintain body fluid homeostasis. Inadequate fluid intake leads to negative health consequences, such as headache, dizziness and urolithiasis. However, people in busy lifestyles usually forget to drink sufficient water and neglect the importance of fluid intake. Fluid intake management is important to assist people in adopting individual drinking behaviors. This work aims to propose a fluid intake monitoring system with a wearable inertial sensor using a hierarchical approach to detect drinking activities, recognize sip gestures and estimate fluid intake amount. Additionally, container-dependent amount estimation models are developed due to the influence of containers on fluid intake amount. The proposed fluid intake monitoring system could achieve 94.42% accuracy, 90.17% sensitivity, and 40.11% mean absolute percentage error (MAPE) for drinking detection, gesture spotting and amount estimation, respectively. Particularly, MAPE of amount estimation is improved approximately 10% compared to the typical approaches. The results have demonstrated the feasibility and the effectiveness of the proposed fluid intake monitoring system.<\/jats:p>","DOI":"10.3390\/s20226682","type":"journal-article","created":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T01:28:48Z","timestamp":1606094928000},"page":"6682","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Fluid Intake Monitoring System Using a Wearable Inertial Sensor for Fluid Intake Management"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2319-1204","authenticated-orcid":false,"given":"Hsiang-Yun","family":"Huang","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, National Yang-Ming University, Taipei 112, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6771-2067","authenticated-orcid":false,"given":"Chia-Yeh","family":"Hsieh","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, National Yang-Ming University, Taipei 112, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7867-4716","authenticated-orcid":false,"given":"Kai-Chun","family":"Liu","sequence":"additional","affiliation":[{"name":"Research Center for Information Technology Innovation, Academia Sinica, Taipei 115, Taiwan"}]},{"given":"Steen Jun-Ping","family":"Hsu","sequence":"additional","affiliation":[{"name":"Department of Information Management, Minghsin University of Science and Technology, Hsinchu County 304, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0995-601X","authenticated-orcid":false,"given":"Chia-Tai","family":"Chan","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, National Yang-Ming University, Taipei 112, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1152\/nips.01470.2003","article-title":"The physiological regulation of thirst and fluid intake","volume":"19","author":"McKinley","year":"2004","journal-title":"Physiology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"S121","DOI":"10.1111\/j.1753-4887.2012.00539.x","article-title":"Challenges of linking chronic dehydration and fluid consumption to health outcomes","volume":"70","author":"Armstrong","year":"2012","journal-title":"Nutr. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"18","DOI":"10.3389\/fnut.2016.00018","article-title":"Increased hydration can be associated with weight loss","volume":"3","author":"Thornton","year":"2016","journal-title":"Front. Nutr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1007\/s00394-015-0944-8","article-title":"Water intake: Validity of population assessment and recommendations","volume":"54","author":"Gandy","year":"2015","journal-title":"Eur. J. Nutr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"S6","DOI":"10.1111\/j.1753-4887.2005.tb00155.x","article-title":"The importance of good hydration for day-to-day health","volume":"63","author":"Ritz","year":"2005","journal-title":"Nutr. Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1080\/07315724.2012.10720011","article-title":"Cognitive performance and dehydration","volume":"31","author":"Adan","year":"2012","journal-title":"J. Am. Coll. Nutr."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1111\/j.1753-4887.2010.00304.x","article-title":"Water, hydration, and health","volume":"68","author":"Popkin","year":"2010","journal-title":"Nutr. Rev."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1227","DOI":"10.1016\/j.jada.2010.05.005","article-title":"The beverage intake questionnaire: Determining initial validity and reliability","volume":"110","author":"Hedrick","year":"2010","journal-title":"J. Am. Diet. Assoc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1017\/S1368980008003108","article-title":"Self-reported dietary energy intake of normal weight, overweight and obese adolescents","volume":"12","author":"Vance","year":"2009","journal-title":"Public Health Nutr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1139\/y90-143","article-title":"Inaccuracies in self-reported intake identified by comparison with the doubly labelled water method","volume":"68","author":"Schoeller","year":"1990","journal-title":"Can. J. Physiol. Pharmacol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Amft, O., Bannach, D., Pirkl, G., Kreil, M., and Lukowicz, P. (2010, January 24). Towards wearable sensing-based assessment of fluid intake. Proceedings of the 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), Mannheim, Germany.","DOI":"10.1109\/PERCOMW.2010.5470653"},{"key":"ref_12","unstructured":"Hondori, H.M., Khademi, M., and Lopes, C.V. (2012, January 7\u20139). Monitoring intake gestures using sensor fusion (microsoft kinect and inertial sensors) for smart home tele-rehab setting. Proceedings of the 1st Annual IEEE Healthcare Innovation Conference, Houston, TX, USA."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Iosifidis, A., Marami, E., Tefas, A., and Pitas, I. (2012, January 25\u201330). Eating and drinking activity recognition based on discriminant analysis of fuzzy distances and activity volumes. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan.","DOI":"10.1109\/ICASSP.2012.6288350"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Tham, J.S., Chang, Y.C., and Fauzi, M.F.A. (2014, January 2\u20135). Automatic identification of drinking activities at home using depth data from RGB-D camera. Proceedings of the 2014 International Conference on Control, Automation and Information Sciences (ICCAIS 2014), Gwangju, Korea.","DOI":"10.1109\/ICCAIS.2014.7020549"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Liu, K.-C., Hsieh, C.-Y., Huang, H.-Y., Chiu, L.-T., Hsu, S.J.-P., and Chan, C.-T. (2020). Drinking Event Detection and Episode Identification Using 3D-Printed Smart Cup. IEEE Sens. J.","DOI":"10.1109\/JSEN.2020.3004051"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Dong, B., Gallant, R., and Biswas, S. (2014, January 8\u201310). A self-monitoring water bottle for tracking liquid intake. Proceedings of the 2014 IEEE Healthcare Innovation Conference (HIC), Seattle, WA, USA.","DOI":"10.1109\/HIC.2014.7038937"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.pmcj.2016.04.007","article-title":"Real-time fluid intake gesture recognition based on batteryless UHF RFID technology","volume":"34","author":"Jayatilaka","year":"2017","journal-title":"Pervasive Mob. Comput."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Rahman, T., Adams, A.T., Zhang, M., Cherry, E., Zhou, B., Peng, H., and Choudhury, T. (2014, January 16\u201319). BodyBeat: A mobile system for sensing non-speech body sounds. Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys), Bretton Woods, NH, USA.","DOI":"10.1145\/2594368.2594386"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1109\/JSEN.2015.2469095","article-title":"AutoDietary: A wearable acoustic sensor system for food intake recognition in daily life","volume":"16","author":"Bi","year":"2015","journal-title":"IEEE Sens. J."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1007\/s13534-014-0149-8","article-title":"Wearable sensing for liquid intake monitoring via apnea detection in breathing signals","volume":"4","author":"Dong","year":"2014","journal-title":"Biomed. Eng. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2010","DOI":"10.1016\/j.patcog.2007.11.016","article-title":"Gesture spotting with body-worn inertial sensors to detect user activities","volume":"41","author":"Junker","year":"2008","journal-title":"Pattern Recognit."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.artmed.2007.11.007","article-title":"Recognition of dietary activity events using on-body sensors","volume":"42","author":"Amft","year":"2008","journal-title":"Artif. Intell. Med."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Gomes, D., and Sousa, I. (2019). Real-Time drink trigger detection in free-living conditions using inertial sensors. Sensors, 19.","DOI":"10.3390\/s19092145"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1145\/3264923","article-title":"FluidMeter: Gauging the Human Daily Fluid Intake Using Smartwatches","volume":"2","author":"Hamatani","year":"2018","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Gomes, D., Mendes-Moreira, J., Sousa, I., and Silva, J.J.S. (2019). Eating and Drinking Recognition in Free-Living Conditions for Triggering Smart Reminders. Sensors, 19.","DOI":"10.3390\/s19122803"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Chun, K.S., Sanders, A.B., Adaimi, R., Streeper, N., Conroy, D.E., and Thomaz, E. (2019, January 17\u201320). Towards a generalizable method for detecting fluid intake with wrist-mounted sensors and adaptive segmentation. Proceedings of the International Conference on Intelligent User Interfaces, Marina del Ray, CA, USA.","DOI":"10.1145\/3301275.3302315"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zimmermann, C., Zeilfelder, J., Bloecher, T., Diehl, M., Essig, S., and Stork, W. (2017, January 13\u201315). Evaluation of a smart drink monitoring device. Proceedings of the IEEE Sensors Applications Symposium (SAS), Glassboro, NJ, USA.","DOI":"10.1109\/SAS.2017.7894061"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Griffith, H., Shi, Y., and Biswas, S.J.S. (2019). A Container-Attachable Inertial Sensor for Real-Time Hydration Tracking. Sensors, 19.","DOI":"10.3390\/s19184008"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Anderez, D.O., Lotfi, A., and Pourabdollah, A. (2019, January 6\u20138). Temporal convolution neural network for food and drink intake recognition. Proceedings of the 12th ACM International Conference on Pervasive Technologies Related to Assistive Environments, Rhodes, Greece.","DOI":"10.1145\/3316782.3322784"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Anderez, D.O., Lotfi, A., and Langensiepen, C. (2018, January 26\u201329). A hierarchical approach in food and drink intake recognition using wearable inertial sensors. Proceedings of the 11th Pervasive Technologies Related to Assistive Environments Conference, Corfu, Greece.","DOI":"10.1145\/3197768.3201542"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/22\/6682\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:35:48Z","timestamp":1760178948000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/22\/6682"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,22]]},"references-count":30,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2020,11]]}},"alternative-id":["s20226682"],"URL":"https:\/\/doi.org\/10.3390\/s20226682","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2020,11,22]]}}}