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Systematic review of sensing technology for detecting food intake

Liu, Yuzhi (2025) Systematic review of sensing technology for detecting food intake.

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Abstract:Obesity has emerged as a critical global health challenge, primarily driven by chronic imbalances between energy intake and expenditure. Weight manage- ment strategies have become increasingly vital, with non-pharmacological in- terventions—including dietary modification and physical exercise—representing the predominant therapeutic approach. However, current dietary assessment methods rely heavily on self-reporting, which introduces substantial mea- surement errors and challenges in maintaining long-term adherence. While existing systematic reviews provide valuable insights, the most recent com- prehensive analysis concludes at 2020, potentially overlooking significant technological and methodological advances in the field. This systematic review examines literature from 2021 to identify emerging research dimensions and derive implications for future clinical practice and research directions. Following systematic screening of 316 articles, 34 studies met inclusion criteria for analysis. Result found that the most focused dimension in 2021 is ’when’, counted for 59 percent of all three dimensions, the other two dimension ’what’ and ’how much’ counted for 21 percent respectively. The most widely detected eating phase is ’oral processing’,appeared 22 out of 34 times, counted for 65 percent of all the studies. The most used sensing principle is ’combination’, appeared 14 out of 34 times, counted for 42 percent of all the articles. The ’Motion’ + ’Vision’ is the most widely used combination set, appeared 7 out of 14 times, counted for all the ’combination’ sensing principle. Comparative analysis with previous systematic reviews reveals consistent emphasis on ’when’ dimension detection and eating phase ’oral processing’ research, while identifying notable shifts in eating phase ’ingestion’ research and sensor location ’face’ deployment. These findings suggest continued pri- oritization of foundational detection capabilities while indicating emerging trends toward multimodal sensing. However, single-year analysis limitations may influence observed patterns, necessitating cautious interpretation of apparent research trends.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Business & IT BSc (56066)
Link to this item:https://purl.utwente.nl/essays/107428
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