LEADER 06164nam 2201585z- 450 001 9910557147403321 005 20231214133501.0 035 $a(CKB)5400000000040584 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/68592 035 $a(EXLCZ)995400000000040584 100 $a20202105d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvancement in Dietary Assessment and Self-Monitoring Using Technology 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 electronic resource (348 p.) 311 $a3-03928-058-9 311 $a3-03928-059-7 330 $aAlthough methods to assess or self-monitor intake may be considered similar, the intended function of each is quite distinct. For the assessment of dietary intake, methods aim to measure food and nutrient intake and/or to derive dietary patterns for determining diet-disease relationships, population surveillance or the effectiveness of interventions. In comparison, dietary self-monitoring primarily aims to create awareness of and reinforce individual eating behaviours, in addition to tracking foods consumed. Advancements in the capabilities of technologies, such as smartphones and wearable devices, have enhanced the collection, analysis and interpretation of dietary intake data in both contexts. This Special Issue invites submissions on the use of novel technology-based approaches for the assessment of food and/or nutrient intake and for self-monitoring eating behaviours. Submissions may document any part of the development and evaluation of the technology-based approaches. Examples may include: web adaption of existing dietary assessment or self-monitoring tools (e.g., food frequency questionnaires, screeners) image-based or image-assisted methods mobile/smartphone applications for capturing intake for assessment or self-monitoring wearable cameras to record dietary intake or eating behaviours body sensors to measure eating behaviours and/or dietary intake use of technology-based methods to complement aspects of traditional dietary assessment or self-monitoring, such as portion size estimation. 606 $aResearch & information: general$2bicssc 606 $aBiology, life sciences$2bicssc 610 $achildren 610 $adietary assessment 610 $anutrients 610 $acarbohydrate counting 610 $aprotein and fat counting 610 $acalorie counting 610 $aautomatic bolus calculator 610 $avoice description of meals 610 $ainsulin dosage 610 $aglycemic control 610 $adiabetes mellitus 610 $anutrition 610 $afood measurement 610 $anutrient database 610 $aenergy intake 610 $avalidity 610 $areliability 610 $afood frequency questionnaire 610 $aweb 610 $aunder-reporting 610 $aover-reporting 610 $amobile applications 610 $aadults 610 $anutritional science 610 $aqualitative research 610 $amobile food record 610 $a24-h recall 610 $adevelopmental disabilities 610 $aspina bifida 610 $adown syndrome 610 $atechnology 610 $apediatrics 610 $aimage-assisted method 610 $ainfant 610 $afood record 610 $adoubly labeled water 610 $anutritional application 610 $asmartphone 610 $aDGA 610 $adietary behaviors 610 $ahousehold food purchase behavior 610 $aobesity 610 $aoverweight weight control 610 $amobile technologies 610 $aWeb-based technologies 610 $ausability 610 $ahuman factors 610 $aAutomated Self-Administered Dietary Assessment Tool (ASA24) 610 $a24-h dietary recall 610 $alow socioeconomic status 610 $adiet 610 $aassessment 610 $afood log 610 $arecall 610 $adiet apps 610 $arecipe calculations 610 $anutrient retention 610 $adietary intake assessment 610 $atechnological innovations 610 $aType 2 diabetes mellitus 610 $adiabetes management 610 $adietary application 610 $aphysical activity 610 $ablood glucose 610 $amHealth 610 $asugar intakes 610 $adietary record 610 $aEast Asians 610 $achewing detection 610 $aAIM 610 $aneural networks 610 $afood intake detection 610 $avideo annotation 610 $asensor validation 610 $adiet assessment 610 $arelative validity 610 $ayoung adults 610 $aapps 610 $amobile app 610 $afruits 610 $avegetables 610 $aself-monitoring 610 $ahealthy diet 610 $ashared plate eating 610 $alower middle income countries 610 $afood energy estimation 610 $agenerative models 610 $agenerative adversarial networks 610 $aimage-to-energy mapping 610 $aregressions 610 $aeating activity detection 610 $ahand-to-mouth movement 610 $awrist-mounted motion tracking sensor 610 $aaccelerometer 610 $agyroscope 610 $atext messages 610 $atype 2 diabetes 610 $adiabetes self-care activities 610 $acardiovascular disease risk awareness 610 $afood availability 610 $afood choices 615 7$aResearch & information: general 615 7$aBiology, life sciences 700 $aBurrows$b Tracy$4edt$01288395 702 $aRollo$b Megan$4edt 702 $aBurrows$b Tracy$4oth 702 $aRollo$b Megan$4oth 906 $aBOOK 912 $a9910557147403321 996 $aAdvancement in Dietary Assessment and Self-Monitoring Using Technology$93031960 997 $aUNINA