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      Wearable Technology to Quantify the Nutritional Intake of Adults: Validation Study

      research-article
      , BSc, RD 1 , , DPhil 1 , , DPhil 1 ,
      (Reviewer), (Reviewer)
      JMIR mHealth and uHealth
      JMIR Publications
      wearable technology, mobile health, mobile phone, food intake, validation study

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          Abstract

          Background

          Wearable and mobile sensor technologies can be useful tools in precision nutrition research and practice, but few are reliable for obtaining accurate and precise measurements of diet and nutrition.

          Objective

          This study aimed to assess the ability of wearable technology to monitor the nutritional intake of adult participants. This paper describes the development of a reference method to validate the wristband’s estimation of daily nutritional intake of 25 free-living study participants and to evaluate the accuracy (kcal/day) and practical utility of the technology.

          Methods

          Participants were asked to use a nutrition tracking wristband and an accompanying mobile app consistently for two 14-day test periods. A reference method was developed to validate the estimation of daily nutritional intake of participants by the wristband. The research team collaborated with a university dining facility to prepare and serve calibrated study meals and record the energy and macronutrient intake of each participant. A continuous glucose monitoring system was used to measure adherence with dietary reporting protocols, but these findings are not reported. Bland-Altman tests were used to compare the reference and test method outputs (kcal/day).

          Results

          A total of 304 input cases were collected of daily dietary intake of participants (kcal/day) measured by both reference and test methods. The Bland-Altman analysis had a mean bias of −105 kcal/day (SD 660), with 95% limits of agreement between −1400 and 1189. The regression equation of the plot was Y=−0.3401X+1963, which was significant ( P<.001), indicating a tendency for the wristband to overestimate for lower calorie intake and underestimate for higher intake. Researchers observed transient signal loss from the sensor technology of the wristband to be a major source of error in computing dietary intake among participants.

          Conclusions

          This study documents high variability in the accuracy and utility of a wristband sensor to track nutritional intake, highlighting the need for reliable, effective measurement tools to facilitate accurate, precision-based technologies for personal dietary guidance and intervention.

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          Most cited references20

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          Biosensors and their applications - A review.

          The various types of biosensors such as enzyme-based, tissue-based, immunosensors, DNA biosensors, thermal and piezoelectric biosensors have been deliberated here to highlight their indispensable applications in multitudinous fields. Some of the popular fields implementing the use of biosensors are food industry to keep a check on its quality and safety, to help distinguish between the natural and artificial; in the fermentation industry and in the saccharification process to detect precise glucose concentrations; in metabolic engineering to enable in vivo monitoring of cellular metabolism. Biosensors and their role in medical science including early stage detection of human interleukin-10 causing heart diseases, rapid detection of human papilloma virus, etc. are important aspects. Fluorescent biosensors play a vital role in drug discovery and in cancer. Biosensor applications are prevalent in the plant biology sector to find out the missing links required in metabolic processes. Other applications are involved in defence, clinical sector, and for marine applications.
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            Recent Advances in Biosensor Technology for Potential Applications – An Overview

            Imperative utilization of biosensors has acquired paramount importance in the field of drug discovery, biomedicine, food safety standards, defense, security, and environmental monitoring. This has led to the invention of precise and powerful analytical tools using biological sensing element as biosensor. Glucometers utilizing the strategy of electrochemical detection of oxygen or hydrogen peroxide using immobilized glucose oxidase electrode seeded the discovery of biosensors. Recent advances in biological techniques and instrumentation involving fluorescence tag to nanomaterials have increased the sensitive limit of biosensors. Use of aptamers or nucleotides, affibodies, peptide arrays, and molecule imprinted polymers provide tools to develop innovative biosensors over classical methods. Integrated approaches provided a better perspective for developing specific and sensitive biosensors with high regenerative potentials. Various biosensors ranging from nanomaterials, polymers to microbes have wider potential applications. It is quite important to integrate multifaceted approaches to design biosensors that have the potential for diverse usage. In light of this, this review provides an overview of different types of biosensors being used ranging from electrochemical, fluorescence tagged, nanomaterials, silica or quartz, and microbes for various biomedical and environmental applications with future outlook of biosensor technology.
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              Validity of the Remote Food Photography Method (RFPM) for estimating energy and nutrient intake in near real-time.

              Two studies are reported; a pilot study to demonstrate feasibility followed by a larger validity study. Study 1's objective was to test the effect of two ecological momentary assessment (EMA) approaches that varied in intensity on the validity/accuracy of estimating energy intake (EI) with the Remote Food Photography Method (RFPM) over 6 days in free-living conditions. When using the RFPM, Smartphones are used to capture images of food selection and plate waste and to send the images to a server for food intake estimation. Consistent with EMA, prompts are sent to the Smartphones reminding participants to capture food images. During Study 1, EI estimated with the RFPM and the gold standard, doubly labeled water (DLW), were compared. Participants were assigned to receive Standard EMA Prompts (n = 24) or Customized Prompts (n = 16) (the latter received more reminders delivered at personalized meal times). The RFPM differed significantly from DLW at estimating EI when Standard (mean ± s.d. = -895 ± 770 kcal/day, P < 0.0001), but not Customized Prompts (-270 ± 748 kcal/day, P = 0.22) were used. Error (EI from the RFPM minus that from DLW) was significantly smaller with Customized vs. Standard Prompts. The objectives of Study 2 included testing the RFPM's ability to accurately estimate EI in free-living adults (N = 50) over 6 days, and energy and nutrient intake in laboratory-based meals. The RFPM did not differ significantly from DLW at estimating free-living EI (-152 ± 694 kcal/day, P = 0.16). During laboratory-based meals, estimating energy and macronutrient intake with the RFPM did not differ significantly compared to directly weighed intake.
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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications (Toronto, Canada )
                2291-5222
                July 2020
                22 July 2020
                : 8
                : 7
                : e16405
                Affiliations
                [1 ] Foods for Health Institute University of California Davis, CA United States
                Author notes
                Corresponding Author: Sara E Schaefer seschaefer@ 123456ucdavis.edu
                Author information
                https://orcid.org/0000-0002-2416-1293
                https://orcid.org/0000-0002-4856-7693
                https://orcid.org/0000-0001-6389-6498
                Article
                v8i7e16405
                10.2196/16405
                7407252
                32706729
                44afb044-47c7-4069-a728-7fb580c9457a
                ©Sarah M Dimitratos, J Bruce German, Sara E Schaefer. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 22.07.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.

                History
                : 26 September 2019
                : 18 November 2019
                : 13 January 2020
                : 10 April 2020
                Categories
                Original Paper
                Original Paper

                wearable technology,mobile health,mobile phone,food intake,validation study

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