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DietSensor: Automatic Dietary Intake Measurement Using Mobile 3D Scanning Sensor for Diabetic Patients.
Makhsous, Sepehr; Bharadwaj, Mukund; Atkinson, Benjamin E; Novosselov, Igor V; Mamishev, Alexander V.
Afiliação
  • Makhsous S; Sensors Energy and Automation Laboratory (SEAL), Department of Electrical and Computer Engineering, The University of Washington, Paul Allen Center, 185 E Stevens Way NE AE100R, Seattle, WA 98195, USA.
  • Bharadwaj M; Sensors Energy and Automation Laboratory (SEAL), Department of Electrical and Computer Engineering, The University of Washington, Paul Allen Center, 185 E Stevens Way NE AE100R, Seattle, WA 98195, USA.
  • Atkinson BE; Department of Health Services, Box 357660, School of Public Health, The University of Washington, Seattle, WA 98195, USA.
  • Novosselov IV; Novosselov Research Group (NRG) Laboratory, Department of Mechanical Engineering, Department of Environmental & Occupational Health Sciences (DEOHS), The University of Washington, 3900 E Stevens Way NE, Seattle, WA 98195, USA.
  • Mamishev AV; Sensors Energy and Automation Laboratory (SEAL), Department of Electrical and Computer Engineering, The University of Washington, Paul Allen Center, 185 E Stevens Way NE AE100R, Seattle, WA 98195, USA.
Sensors (Basel) ; 20(12)2020 Jun 15.
Article em En | MEDLINE | ID: mdl-32549356
ABSTRACT
Diabetes is a global epidemic that impacts millions of people every year. Enhanced dietary assessment techniques are critical for maintaining a healthy life for a diabetic patient. Moreover, hospitals must monitor their diabetic patients' food intake to prescribe a certain amount of insulin. Malnutrition significantly increases patient mortality, the duration of the hospital stay, and, ultimately, medical costs. Currently, hospitals are not fully equipped to measure and track a patient's nutritional intake, and the existing solutions require an extensive user input, which introduces a lot of human errors causing endocrinologists to overlook the measurement. This paper presents DietSensor, a wearable three-dimensional (3D) measurement system, which uses an over the counter 3D camera to assist the hospital personnel with measuring a patient's nutritional intake. The structured environment of the hospital provides the opportunity to have access to the total nutritional data of any meal prepared in the kitchen as a cloud database. DietSensor uses the 3D scans and correlates them with the hospital kitchen database to calculate the exact consumed nutrition by the patient. The system was tested on twelve volunteers with no prior background or familiarity with the system. The overall calculated nutrition from the DietSensor phone application was compared with the outputs from the 24-h dietary recall (24HR) web application and MyFitnessPal phone application. The average absolute error on the collected data was 73%, 51%, and 33% for the 24HR, MyFitnessPal, and DietSensor systems, respectively.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus / Dieta / Ingestão de Alimentos / Dispositivos Eletrônicos Vestíveis Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus / Dieta / Ingestão de Alimentos / Dispositivos Eletrônicos Vestíveis Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos