A smart utensil for detecting food pick-up gesture and amount while eating

Abstract

Seemingly trivial eating habits, such as eating too fast, have been linked to diverse and rather serious health issues. While technology-mediated interventions have leveraged several strategies to promote healthy dietary habits, designing successful pervasive interventions remains challenging. This thesis first offers three contributions with the aim of assisting in the design of eating interventions: 1) a review of 62 studies which focused on interventions targeting eating habits; 2) a generative design framework with multiple design parameters; and, 3) an exploration of the potential efficacy of the developed framework. These contributions will improve

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

“…Fifty-three unique devices and four combinations of devices ( 77 – 80 ) identified from 54 studies were included in the data extraction table ( Supplementary Table 1 ). Of the 53 unique devices, 18 devices were placed on the wrist ( 27 – 44 ); nine were worn around the neck ( 45 – 52 ); nine were placed in or around the ears ( 53 – 61 ); seven were glasses-like devices ( 62 – 68 ); and ten were categorized as “Other Devices” ( 30 , 36 , 69 – 76 ) where devices were worn in less common locations of the body or were non-wearable ( 69 , 72 ).…”

“…Non-wearable technology included a WiFi transmitter and a receiver, using interferences in the WiFi signaling between a WiFi access point and a smartphone to deduce human body motion ( 69 ). Another non-wearable was a smart fork that detected food pick-up gestures and bite quantity using a load cell embedded inside the fork to measure the weight of each bite ( 72 ). This could potentially be used to estimate caloric intake.…”

“…Most of the devices in this category were still in preliminary developmental stages and were tested on a limited number of foods and/or behaviors in laboratory settings ( 30 , 36 , 68 – 72 ). However, devices worn on the chin ( 73 ) and teeth ( 74 ) were small and discreet and had been tested in free-living settings.…”

A Review of Digital Innovations for Diet Monitoring and Precision Nutrition

“…(d) Smart fork utensil. 9 (e) Epidermal sweat sensor (from Sempionatto et al 10 ). Personalized nutrition is achieved by combining (f) continuous glucose monitors, (g) microbiome information and (h) machine learning techniques.…”

“…Personalized nutrition is achieved by combining (f) continuous glucose monitors, (g) microbiome information and (h) machine learning techniques. (a) Provided, with permission, by Undermyfork, (b) reprinted (adapted) with permission from authors 7 (c) reprinted (adapted) with permission from Tseng et al, 8 (d) reprinted (adapted) with permission from Zhang et al, 9 (e) reprinted (adapted) with permission from Sempionatto et al, 10 Copyright 2020 American Chemical Society, (f) photo credit: iStock.com/AzmanJaka, (g) photo credit: iStock.com/Design Cells, and (h) photo credit: iStock.com/KENGKAT.…”