{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:34:36Z","timestamp":1760240076292,"version":"build-2065373602"},"reference-count":59,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,2,4]],"date-time":"2019-02-04T00:00:00Z","timestamp":1549238400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["YO 226\/1-1"],"award-info":[{"award-number":["YO 226\/1-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/K031910\/1"],"award-info":[{"award-number":["EP\/K031910\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Wellbeing is often affected by health-related conditions. Among them are nutrition-related health conditions, which can significantly decrease the quality of life. We envision a system that monitors the kitchen activities of patients and that based on the detected eating behaviour could provide clinicians with indicators for improving a patient\u2019s health. To be successful, such system has to reason about the person\u2019s actions and goals. To address this problem, we introduce a symbolic behaviour recognition approach, called Computational Causal Behaviour Models (CCBM). CCBM combines symbolic representation of person\u2019s behaviour with probabilistic inference to reason about one\u2019s actions, the type of meal being prepared, and its potential health impact. To evaluate the approach, we use a cooking dataset of unscripted kitchen activities, which contains data from various sensors in a real kitchen. The results show that the approach is able to reason about the person\u2019s cooking actions. It is also able to recognise the goal in terms of type of prepared meal and whether it is healthy. Furthermore, we compare CCBM to state-of-the-art approaches such as Hidden Markov Models (HMM) and decision trees (DT). The results show that our approach performs comparable to the HMM and DT when used for activity recognition. It outperformed the HMM for goal recognition of the type of meal with median accuracy of 1 compared to median accuracy of 0.12 when applying the HMM. Our approach also outperformed the HMM for recognising whether a meal is healthy with a median accuracy of 1 compared to median accuracy of 0.5 with the HMM.<\/jats:p>","DOI":"10.3390\/s19030646","type":"journal-article","created":{"date-parts":[[2019,2,5]],"date-time":"2019-02-05T11:31:07Z","timestamp":1549366267000},"page":"646","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Analysing Cooking Behaviour in Home Settings: Towards Health Monitoring"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6428-1062","authenticated-orcid":false,"given":"Kristina","family":"Yordanova","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Rostock, 18051 Rostock, Germany"},{"name":"Department of Electrical and Electronic Engineering, University of Bristol, Bristol BS8 1UB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"L\u00fcdtke","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Rostock, 18051 Rostock, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4306-8876","authenticated-orcid":false,"given":"Samuel","family":"Whitehouse","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, University of Bristol, Bristol BS8 1UB, UK"},{"name":"Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7925-3363","authenticated-orcid":false,"given":"Frank","family":"Kr\u00fcger","sequence":"additional","affiliation":[{"name":"Department of Communications Engineering, University of Rostock, 18051 Rostock, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5114-1514","authenticated-orcid":false,"given":"Adeline","family":"Paiement","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Toulon, 83957 Toulon, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6478-1403","authenticated-orcid":false,"given":"Majid","family":"Mirmehdi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ian","family":"Craddock","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, University of Bristol, Bristol BS8 1UB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Kirste","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Rostock, 18051 Rostock, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"579","DOI":"10.3945\/an.113.004176","article-title":"Nutrition research to affect food and a healthy lifespan","volume":"4","author":"Ohlhorst","year":"2013","journal-title":"Adv. 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