Prediction of Eating Activity using Smartwatch

Kamachi, Haruka; Hossain, Tahera; Tokuyama, Fuyuka; Yokokubo, Anna; Lopez, Guillaume

doi:10.1145/3460418.3479348

Cited by 3 publications

(1 citation statement)

References 23 publications

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“…However, user acceptability was not formally tested for most wrist devices. Whilst none of the devices could provide an assessment of the actual foods consumed or the energy and nutrient intake, one device could distinguish between the use of different types of cutleries ( 28 ), one could distinguish between a limited number of food types (ramen, pasta, bread, onigiri, gyudon, cake) ( 43 ), and one could capture (but not provide an assessment of) food type via an embedded camera ( 34 ).…”

Section: Resultsmentioning

confidence: 99%

Enhancing Nutrition Care Through Real-Time, Sensor-Based Capture of Eating Occasions: A Scoping Review

et al. 2022

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As food intake patterns become less structured, different methods of dietary assessment may be required to capture frequently omitted snacks, smaller meals, and the time of day when they are consumed. Incorporating sensors that passively and objectively detect eating behavior may assist in capturing these eating occasions into dietary assessment methods. The aim of this study was to identify and collate sensor-based technologies that are feasible for dietitians to use to assist with performing dietary assessments in real-world practice settings. A scoping review was conducted using the PRISMA extension for scoping reviews (PRISMA-ScR) framework. Studies were included if they were published between January 2016 and December 2021 and evaluated the performance of sensor-based devices for identifying and recording the time of food intake. Devices from included studies were further evaluated against a set of feasibility criteria to determine whether they could potentially be used to assist dietitians in conducting dietary assessments. The feasibility criteria were, in brief, consisting of an accuracy ≥80%; tested in settings where subjects were free to choose their own foods and activities; social acceptability and comfort; a long battery life; and a relatively rapid detection of an eating episode. Fifty-four studies describing 53 unique devices and 4 device combinations worn on the wrist (n = 18), head (n = 16), neck (n = 9), and other locations (n = 14) were included. Whilst none of the devices strictly met all feasibility criteria currently, continuous refinement and testing of device software and hardware are likely given the rapidly changing nature of this emerging field. The main reasons devices failed to meet the feasibility criteria were: an insufficient or lack of reporting on battery life (91%), the use of a limited number of foods and behaviors to evaluate device performance (63%), and the device being socially unacceptable or uncomfortable to wear for long durations (46%). Until sensor-based dietary assessment tools have been designed into more inconspicuous prototypes and are able to detect most food and beverage consumption throughout the day, their use will not be feasible for dietitians in practice settings.

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Section: Resultsmentioning

confidence: 99%