Análise de aplicativos móveis voltados para controle parental: revisão narrativa / Analysis of mobile applications aimed at parental control: narrative review / Análisis de aplicaciones móviles orientadas al control parental: revisión narrativa

Crianças e adolescentes usam a tecnologia móvel para diversas finalidades, como lazer, entretenimento, estudos e comunicação. No entanto, faz-se necessário o controle e mediação parental pois o uso inadequado pode gerar danos à saúde. Existem aplicativos voltados para esta tarefa e com funcionalidades e características variadas. Diante disso, este estudo teve como objetivo analisar as aplicações móveis disponíveis para download na plataforma Google Play Store por meio de uma revisão narrativa e com auxílio do software IRAMUTEQ para revisão dos dados, analisar os comentários deixados pelos usuários. Foram investigadas as informações de 138 aplicativos, boa parte deles realizam funções essenciais, como controlar o tempo de acesso, bloquear sites e apps indesejados, porém, há muitas críticas relacionadas a problemas técnicos, aplicabilidade e prejuízos gerados pelo excessivo controle dos pais. A investigação mostrou que cinco softwares para o controle parental apresentavam as principais funções de acordo com a aplicabilidade (limite de tempo, filtros, localizador GPS, monitoramento de chamadas e mensagens), nota acima de 3,0 e ano de atualização em 2021. A análise dos comentários feita pelo software IRAMUTEQ, destacou as palavras "App" (referente à aplicativo), "filho", "celular", "bloquear", "funcionar", "criança", "instalar" e "desinstalar" como as mais importantes pelos usuários.

Children and teenagers use mobile technology for different purposes, such as leisure, entertainment, studies and communication. However, parental control and mediation is necessary, as inappropriate use can cause health damage. There are applications aimed at this task and with varied functionalities and characteristics. Therefore, this study aimed to analyze the mobile applications available for download on the Google Play Store platform through a narrative review and with the help of the IRAMUTEQ software to review the data, analyze the comments left by users. Information from 138 applications was investigated, most of which perform essential functions, such as controlling access time, blocking unwanted websites and apps, however, there are many criticisms related to technical problems, applicability and damage caused by excessive parental control. The investigation showed that five parental control software had the main functions according to applicability (time limit, filters, GPS locator, call and message monitoring), grade above 3.0 and year of update in 2021. The analysis of the comments made by the IRAMUTEQ software, highlighted the words "App" (referring to the application), "son", "cell phone", "block", "work", "child", "install" and "uninstall" as the most important for users.

Los niños y adolescentes utilizan la tecnología móvil para diferentes fines, como el ocio, el entretenimiento, los estudios y la comunicación. Sin embargo, es necesario el control y la mediación parental, ya que un uso inadecuado puede causar daños a la salud. Existen aplicaciones destinadas a esta tarea y con funcionalidades y características variadas. Por lo tanto, este estudio tuvo como objetivo analizar las aplicaciones móviles disponibles para su descarga en la plataforma Google Play Store a través de una revisión narrativa y con la ayuda del software IRAMUTEQ para revisar los datos, analizar los comentarios dejados por los usuarios. Se investigó la información de 138 aplicaciones, la mayoría de las cuales cumplen funciones esenciales, como controlar el tiempo de acceso, bloquear sitios web y apps no deseadas, sin embargo, existen muchas críticas relacionadas con problemas técnicos, de aplicabilidad y daños causados por el excesivo control parental. La investigación mostró que cinco programas de control parental tenían las funciones principales según aplicabilidad (límite de tiempo, filtros, localizador GPS, monitorización de llamadas y mensajes), grado superior a 3.0 y año de actualización en 2021. El análisis de los comentarios realizados por el software IRAMUTEQ, destacó las palabras "App" (refiriéndose a la aplicación), "hijo", "móvil", "bloquear", "trabajar", "niño", "instalar" y "desinstalar" como las más importantes para los usuarios.

Preliminary Study of Vibrotactile Feedback during Home-Based Balance and Coordination Training in Individuals with Cerebellar Ataxia.

Intensive balance and coordination training is the mainstay of treatment for symptoms of impaired balance and mobility in individuals with hereditary cerebellar ataxia. In this study, we compared the effects of home-based balance and coordination training with and without vibrotactile SA for individuals with hereditary cerebellar ataxia. Ten participants (five males, five females; 47 ± 12 years) with inherited forms of cerebellar ataxia were recruited to participate in a 12-week crossover study during which they completed two six-week blocks of balance and coordination training with and without vibrotactile SA. Participants were instructed to perform balance and coordination exercises five times per week using smartphone balance trainers that provided written, graphic, and video guidance and measured trunk sway. The pre-, per-, and post-training performance were assessed using the Scale for the Assessment and Rating of Ataxia (SARA), SARAposture&gait sub-scores, Dynamic Gait Index, modified Clinical Test of Sensory Interaction in Balance, Timed Up and Go performed with and without a cup of water, and multiple kinematic measures of postural sway measured with a single inertial measurement unit placed on the participants' trunks. To explore the effects of training with and without vibrotactile SA, we compared the changes in performance achieved after participants completed each six-week block of training. Among the seven participants who completed both blocks of training, the change in the SARA scores and SARAposture&gait sub-scores following training with vibrotactile SA was not significantly different from the change achieved following training without SA (p>0.05). However, a trend toward improved SARA scores and SARAposture&gait sub-scores was observed following training with vibrotactile SA; compared to their pre-vibrotacile SA training scores, participants significantly improved their SARA scores (mean=−1.21, p=0.02) and SARAposture&gait sub-scores (mean=−1.00, p=0.01). In contrast, no significant changes in SARA scores and SARAposture&gait sub-scores were observed following the six weeks of training without SA compared to their pre-training scores immediately preceding the training block without vibrotactile SA (p>0.05). No significant changes in trunk kinematic sway parameters were observed as a result of training (p>0.05). Based on the findings from this preliminary study, balance and coordination training improved the participants' motor performance, as captured through the SARA. Vibrotactile SA may be a beneficial addition to training regimens for individuals with hereditary cerebellar ataxia, but additional research with larger sample sizes is needed to assess the significance and generalizability of these findings.

Smartphone-Based Screening for Cardiovascular Diseases: A Trend?

Abstract Cardiovascular diseases are the leading cause of death in the world. People living in vulnerable and poor places such as slums, rural areas and remote locations have difficulty in accessing medical care and diagnostic tests. In addition, given the COVID-19 pandemic, we are witnessing an increase in the use of telemedicine and non-invasive tools for monitoring vital signs. These questions motivate us to write this point of view and to describe some of the main innovations used for non-invasive screening of heart diseases. Smartphones are widely used by the population and are perfect tools for screening cardiovascular diseases. They are equipped with camera, flashlight, microphone, processor, and internet connection, which allow optical, electrical, and acoustic analysis of cardiovascular phenomena. Thus, when using signal processing and artificial intelligence approaches, smartphones may have predictive power for cardiovascular diseases. Here we present different smartphone approaches to analyze signals obtained from various methods including photoplethysmography, phonocardiograph, and electrocardiography to estimate heart rate, blood pressure, oxygen saturation (SpO2), heart murmurs and electrical conduction. Our objective is to present innovations in non-invasive diagnostics using the smartphone and to reflect on these trending approaches. These could help to improve health access and the screening of cardiovascular diseases for millions of people, particularly those living in needy areas.

Smartphone addiction in COVID-19 pandemic times: a longitudinal study with Brazilian dental students / Vício em smartphoneem tempos de pandemia por COVID-19: estudo longitudinal com estudantes de Odontologia

This study aimed to evaluate smartphone addiction, sleep quality, quality of life and depression among dental students before and during the first wave COVID-19 pandemic lockdown and explore how smartphone addiction influences the other variables. 57 dental students answered the smartphone addiction inventory, Pittsburg sleep quality index, WHOQOL-bref and research diagnosis criteria for temporomandibular disorders axis II questionnaires before and during lockdown. Statistical analysis was conducted using Wilcoxon test, Mann-Whitney U test, Spearman tests and linear regression models considering the smartphone addiction inventory total score as the independent variable. The high mean scores on smartphone addiction on both times are remarkable. The smartphoneaddictionprevalence was also high on both times (68.66% and 71.92% respectively). Overall sleep quality improved. However, there was no significant change on overall smartphone addiction, quality of life and depression grade during lockdown. Tolerance using smartphones increased during lockdown, especially for women. Smartphone addiction showed negative correlation to quality of life and positive correlation to depression, subjective sleep quality and sleep medication use. Smartphone addiction was apredictor to total WHOQOL-bref score, all WHOQOL-bref domains, sleep medication use and to depression on both times, before and during lockdown. Smartphone addiction was directly affecting quality of life. Despite the growing smartphone use among university students due to the pandemic restrictions, this study showed that the overall smartphone addiction, quality of life and depression grade were not influenced by the lockdown restrictions. However, it was observed an improvement on sleep quality during this period among dental students (AU).

O objetivo deste estudo foi avaliar o vício emsmartphones, qualidade de vida, qualidade de sono e depressão em estudantes de odontologia antes e durante a quarentena daprimeira onda da pandemia por COVID-19. 57 estudantes de odontologia responderam nos dois tempos os questionários validados:smartphone addiction inventory, índice de qualidade de sono de Pittsburg, WHOQOL-bref e critérios para diagnóstico em pesquisa dasdisfunções temporomandibulares eixo II. Foram realizados os testes estatísticos: Wilcoxon, Mann-Whitney U, Spearman e regressões lineares considerando o total do smartphone addiction inventorycomo variável independente. A prevalência de vício em smartphonesfoi elevada nos dois tempos (68.66% e 71.92% respectivamente). Durante a quarentena a qualidade de sono melhorou e não houve diferença estatisticamente significativa no vício em smartphones, qualidade de vida nem depressão. A tolerância no uso dossmartphonesaumentou, especialmente entre as mulheres. O vício em smartphonesapresentou correlação negativa com qualidade de vida e positiva com a depressão, qualidade subjetiva do sono e necessidade de medicação hipnótica. O vício em smartphonesfoi preditor para todos os domínios do WHOQOL-bref e seu escore total, para o uso de medicação e depressão em ambos os tempos. O vício em smartphonesfoi muito elevado nos dois tempos afetando a qualidade de vida dos estudantes. Apesar do aumento do uso desmartphonesem virtude das restrições impostas pela pandemia, esse estudo mostrou que o vício em smartphones, qualidade de vida e depressão não foram influenciados pela quarentena. Entretanto, foi observada melhora na qualidade de sono durante esse período (AU).

Portable on-chip colorimetric biosensing platform integrated with a smartphone for label/PCR-free detection of Cryptosporidium RNA.

Cryptosporidium, a protozoan pathogen, is a leading threat to public health and the economy. Herein, we report the development of a portable, colorimetric biosensing platform for the sensitive, selective and label/PCR-free detection of Cryptosporidium RNA using oligonucleotides modified gold nanoparticles (AuNPs). A pair of specific thiolated oligonucleotides, complementary to adjacent sequences on Cryptosporidium RNA, were attached to AuNPs. The need for expensive laboratory-based equipment was eliminated by performing the colorimetric assay on a micro-fabricated chip in a 3D-printed holder assembly. A smartphone camera was used to capture an image of the color change for quantitative analysis. The detection was based on the aggregation of the gold nanoparticles due to the hybridization between the complementary Cryptosporidium RNA and the oligonucleotides immobilized on the AuNPs surface. In the complementary RNA's presence, a distinctive color change of the AuNPs (from red to blue) was observed by the naked eye. However, in the presence of non-complementary RNA, no color change was observed. The sensing platform showed wide linear responses between 5 and 100 µM with a low detection limit of 5 µM of Cryptosporidium RNA. Additionally, the sensor developed here can provide information about different Cryptosporidium species present in water resources. This cost-effective, easy-to-use, portable and smartphone integrated on-chip colorimetric biosensor has great potential to be used for real-time and portable POC pathogen monitoring and molecular diagnostics.

Accuracy of Dental Photography: Professional vs. Smartphone's Camera.

There is a scant literature on the accuracy of dental photographs captured by Digital Single-Lens Reflex (DSLR) and smartphone cameras. The aim was to compare linear measurements of plaster models photographed with DSLR and smartphone's camera with digital models. Thirty maxillary casts were prepared. Vertical and horizontal reference lines were marked on each tooth, with exception to molars. Then, models were scanned with the TRIOS 3 Basic intraoral dental scanner (control). Six photographs were captured for each model: one using DSLR camera (Canon EOS 700D) and five with smartphone (iPhone X) (distance range 16-32 cm). Teeth heights and widths were measured on scans and photographs. The following conclusions could be drawn: (1) the measurements of teeth by means of DSLR and smartphone cameras (at distances of at least 24 cm) and scan did not differ. (2) The measurements of anterior teeth by means of DSLR and smartphone cameras (at all distances tested) and scan exhibited no difference. For documentational purposes, the distortion is negligeable, and both camera devices can be applied. Dentists can rely on DSLR and smartphone cameras (at distances of at least 24 cm) for smile designs providing comparable and reliable linear measurements.

Android malware classification based on random vector functional link and artificial Jellyfish Search optimizer.

Smartphone usage is nearly ubiquitous worldwide, and Android provides the leading open-source operating system, retaining the most significant market share and active user population of all open-source operating systems. Hence, malicious actors target the Android operating system to capitalize on this consumer reliance and vulnerabilities present in the system. Hackers often use confidential user data to exploit users for advertising, extortion, and theft. Notably, most Android malware detection tools depend on conventional machine-learning algorithms; hence, they lose the benefits of metaheuristic optimization. Here, we introduce a novel detection system based on optimizing the random vector functional link (RVFL) using the artificial Jellyfish Search (JS) optimizer following dimensional reduction of Android application features. JS is used to determine the optimal configurations of RVFL to improve classification performance. RVFL+JS minimizes the runtime of the execution of the optimized models with the best performance metrics, based on a dataset consisting of 11,598 multi-class applications and 471 static and dynamic features.

Novel technology at hand to measure skin hydration by Biodisplay smartphone touch screen panel.

Skin hydration is generally evaluated using devices that measure capacitance or conductance. A new technology (Biodisplay) was developed to provide accurate measurements of skin hydration at the contact site. This study aimed to test the reliability of the Biodisplay by comparing its performance results with those of similar devices currently used to objectively assess skin hydration. For each of the 30 participants, skin hydration was measured at each of the defined points on the forearm three times using the Biodisplay and a Hydration probe (HP), an objective measurement device of skin hydration. We also evaluated skin hydration of the arm using both tools after applying moisturizers to evaluate interferences from skin care products. The reliability and reproducibility of each device were analyzed by intraclass correlation coefficients (ICC), and the correlation of the two devices was evaluated by Pearson's correlation coefficients (PCC). The Biodisplay demonstrated moderate-to-excellent reliability (ICC: (0.741-0.980)), but lower reliability than the HP (ICC: (0.953-0.980)). The skin hydration measurements made by the two devices were demonstrated to be significantly correlated, showing moderate correlations (PCC: 0.601). The Biodisplay can provide reasonably reliable and accurate measurements for skin hydration with the strong points of portability and accessibility.

Sociodemographic characteristics of missing data in digital phenotyping.

The ubiquity of smartphones, with their increasingly sophisticated array of sensors, presents an unprecedented opportunity for researchers to collect longitudinal, diverse, temporally-dense data about human behavior while minimizing participant burden. Researchers increasingly make use of smartphones for "digital phenotyping," the collection and analysis of raw phone sensor and log data to study the lived experiences of subjects in their natural environments using their own devices. While digital phenotyping has shown promise in fields such as psychiatry and neuroscience, there are fundamental gaps in our knowledge about data collection and non-collection (i.e., missing data) in smartphone-based digital phenotyping. In this meta-study using individual-level data from six different studies, we examined accelerometer and GPS sensor data of 211 participants, amounting to 29,500 person-days of observation, using Bayesian hierarchical negative binomial regression with study- and user-level random intercepts. Sensitivity analyses including alternative model specification and stratified models were conducted. We found that iOS users had lower GPS non-collection than Android users. For GPS data, rates of non-collection did not differ by race/ethnicity, education, age, or gender. For accelerometer data, Black participants had higher rates of non-collection, but rates did not differ by sex, education, or age. For both sensors, non-collection increased by 0.5% to 0.9% per week. These results demonstrate the feasibility of using smartphone-based digital phenotyping across diverse populations, for extended periods of time, and within diverse cohorts. As smartphones become increasingly embedded in everyday life, the insights of this study will help guide the design, planning, and analysis of digital phenotyping studies.

Rationale and validation of a novel mobile application probing motor inhibition: Proof of concept of CALM-IT.

Identification of behavioral mechanisms underlying psychopathology is essential for the development of novel targeted therapeutics. However, this work relies on rigorous, time-intensive, clinic-based laboratory research, making it difficult to translate research paradigms into tools that can be used by clinicians in the community. The broad adoption of smartphone technology provides a promising opportunity to bridge the gap between the mechanisms identified in the laboratory and the clinical interventions targeting them in the community. The goal of the current study is to develop a developmentally appropriate, engaging, novel mobile application called CALM-IT that probes a narrow biologically informed process, inhibitory control. We aim to leverage the rigorous and robust methods traditionally used in laboratory settings to validate this novel mechanism-driven but easily disseminatable tool that can be used by clinicians to probe inhibitory control in the community. The development of CALM-IT has significant implications for the ability to screen for inhibitory control deficits in the community by both clinicians and researchers. By facilitating assessment of inhibitory control outside of the laboratory setting, researchers could have access to larger and more diverse samples. Additionally, in the clinical setting, CALM-IT represents a novel clinical screening measure that could be used to determine personalized courses of treatment based on the presence of inhibitory control deficits.

A Novel Virtual Wet Lab-Using a Smartphone Camera Adapter and a Video Conference Platform to Provide Real-Time Surgical Instruction.

PURPOSE: Proctored surgical instruction has traditionally been taught through in-person interactions in either the operating room or an improvised wet lab. Because of the COVID-19 pandemic, live in-person instruction was not feasible owing to social distancing protocols, so a virtual wet lab (VWL) was proposed and implemented. The purpose of this article is to describe our experience with a VWL as a Descemet membrane endothelial keratoplasty (DMEK) skills-transfer course. This is the first time that a VWL environment has been described for the instruction of ophthalmic surgery. METHODS: Thirteen participant surgeons took part in VWLs designed for DMEK skills transfer in September and October 2020. A smartphone camera adapter and a video conference software platform were the unique media for the VWL. After a didactic session, participants were divided into breakout rooms where their surgical scope view was broadcast live, allowing instructors to virtually proctor their participants in real time. Participants were surveyed to assess their satisfaction with the course. RESULTS: All (100%) participants successfully injected and unfolded their DMEK grafts. Ten of the 13 participants completed the survey. Respondents rated the experience highly favorably. CONCLUSIONS: With the use of readily available technology, VWLs can be successfully implemented in lieu of in-person skills-transfer courses. Further development catering to the needs of the participant might allow VWLs to serve as a viable option of surgical education, currently limited by geographical and social distancing boundaries.

Mobile health and privacy: cross sectional study.

OBJECTIVES: To investigate whether and what user data are collected by health related mobile applications (mHealth apps), to characterise the privacy conduct of all the available mHealth apps on Google Play, and to gauge the associated risks to privacy. DESIGN: Cross sectional study SETTING: Health related apps developed for the Android mobile platform, available in the Google Play store in Australia and belonging to the medical and health and fitness categories. PARTICIPANTS: Users of 20 991 mHealth apps (8074 medical and 12 917 health and fitness found in the Google Play store: in-depth analysis was done on 15 838 apps that did not require a download or subscription fee compared with 8468 baseline non-mHealth apps. MAIN OUTCOME MEASURES: Primary outcomes were characterisation of the data collection operations in the apps code and of the data transmissions in the apps traffic; analysis of the primary recipients for each type of user data; presence of adverts and trackers in the app traffic; audit of the app privacy policy and compliance of the privacy conduct with the policy; and analysis of complaints in negative app reviews. RESULTS: 88.0% (n=18 472) of mHealth apps included code that could potentially collect user data. 3.9% (n=616) of apps transmitted user information in their traffic. Most data collection operations in apps code and data transmissions in apps traffic involved external service providers (third parties). The top 50 third parties were responsible for most of the data collection operations in app code and data transmissions in app traffic (68.0% (2140), collectively). 23.0% (724) of user data transmissions occurred on insecure communication protocols. 28.1% (5903) of apps provided no privacy policies, whereas 47.0% (1479) of user data transmissions complied with the privacy policy. 1.3% (3609) of user reviews raised concerns about privacy. CONCLUSIONS: This analysis found serious problems with privacy and inconsistent privacy practices in mHealth apps. Clinicians should be aware of these and articulate them to patients when determining the benefits and risks of mHealth apps.

Method for Detecting Emission Spectral Change of Bioluminescent Ratiometric Indicators by a Smartphone.

The application of smartphones as detectors is essential to achieve ubiquitous measurement targeting biomolecules. Because bioluminescence (BL), as a tag for a target sample, does not require an excitation light source, it can be combined with a smartphone to constitute a compact and mobile measurement system. A method was recently established to detect the spectral change of ratiometric indicators based on bioluminescence resonance energy transfer with a smartphone camera. For example, it was possible to detect changes in the BL color of the Ca2+ indicator quantitatively and easily calculate the concentration of free Ca2+ by setting appropriate image acquisition conditions in a smartphone application. In this paper, we describe techniques to obtain scientifically relevant and reliable BL data with such a convenient instrument. This protocol expands the potential of the smartphone as a personal imaging device with high mobility that can be used anywhere.

Compressive recovery of smartphone RGB spectral sensitivity functions.

Spectral response (or sensitivity) functions of a three-color image sensor (or trichromatic camera) allow a mapping from spectral stimuli to RGB color values. Like biological photosensors, digital RGB spectral responses are device dependent and significantly vary from model to model. Thus, the information on the RGB spectral response functions of a specific device is vital in a variety of computer vision as well as mobile health (mHealth) applications. Theoretically, spectral response functions can directly be measured with sophisticated calibration equipment in a specialized laboratory setting, which is not easily accessible for most application developers. As a result, several mathematical methods have been proposed relying on standard color references. Typical optimization frameworks with constraints are often complicated, requiring a large number of colors. We report a compressive sensing framework in the frequency domain for accurately predicting RGB spectral response functions only with several primary colors. Using a scientific camera, we first validate the estimation method with direct spectral sensitivity measurements and ensure that the root mean square errors between the ground truth and recovered RGB spectral response functions are negligible. We further recover the RGB spectral response functions of smartphones and validate with an expanded color checker reference. We expect that this simple yet reliable estimation method of RGB spectral sensitivity can easily be applied for color calibration and standardization in machine vision, hyperspectral filters, and mHealth applications that capitalize on the built-in cameras of smartphones.

Fall risk classification for people with lower extremity amputations using random forests and smartphone sensor features from a 6-minute walk test.

Fall-risk classification is a challenging but necessary task to enable the recommendation of preventative programs for individuals identified at risk for falling. Existing research has primarily focused on older adults, with no predictive fall-risk models for lower limb amputees, despite their greater likelihood of fall-risk than older adults. In this study, 89 amputees with varying degrees of lower limb amputation were asked if they had fallen in the past 6 months. Those who reported at least one fall were considered a fall risk. Each participant performed a 6 minute walk test (6MWT) with an Android smartphone placed in a holder located on the back of the pelvis. A fall-risk classification method was developed using data from sensors within the smartphone. The Ottawa Hospital Rehabilitation Center Walk Test app captured accelerometer and gyroscope data during the 6MWT. From this data, foot strikes were identified, and 248 features were extracted from the collection of steps. Steps were segmented into turn and straight walking, and four different data sets were created: turn steps, straightaway steps, straightaway and turn steps, and all steps. From these, three feature selection techniques (correlation-based feature selection, relief F, and extra trees classifier ensemble) were used to eliminate redundant or ineffective features. Each feature subset was tested with a random forest classifier and optimized for the best number of trees. The best model used turn data, with three features selected by Correlation-based feature selection (CFS), and used 500 trees in a random forest classifier. The resulting metrics were 81.3% accuracy, 57.2% sensitivity, 94.9% specificity, a Matthews correlation coefficient of 0.587, and an F1 score of 0.83. Since the outcomes are comparable to metrics achieved by existing clinical tests, the classifier may be viable for use in clinical practice.

Use of three-dimensional printing for adapting and optimizing smartphone ophthalmoscopy to existing SD-OCT instrumentation for rodent and teleost ocular research.

Use of animal models for human vision research is now pervasive. To address a range of technical challenges, laboratories either modify existing equipment or purchase products that are purpose designed. Three-dimensional (3D) printing technology now allows the do-it-yourself capability to invent, innovate, and manufacture for a specific purpose. Ophthalmic imaging is often used with a range of other sophisticated experimental retinal imaging techniques, such as spectral domain optical coherence tomography (SD-OCT). The handheld smartphone camera and cost-effective, readily available professional-quality apps now allow accessible high-definition video ophthalmic image recording. However, to our knowledge, there are few reports of adapting smartphone ophthalmic imaging to existing experimental SD-OCT imaging instrumentation. This would offer better accuracy, reproducibility, and most importantly, precision. The objective of the present study was to use 3D printing to enhance the functionality and precision of existing SD-OCT instrumentation and smartphone-based ophthalmic imaging through construction of a custom 3D-printed assembly. The assembly can be controlled either manually or by the highly precise rodent stage of the SD-OCT instrument. Using this technical approach, 3D printing facilitated a novel methodology for high-quality ophthalmic imaging with low cost and ease of production either manually or by enhancing existing SD-OCT instrumentation.

Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq.

To collect dietary intake data in a fast and reliable manner, a flexible and innovative smartphone application (app) called Traqq was developed (iOS/Android). This app can be used as a food record and 24-h recall (or shorter recall periods). Different sampling schemes can be created on either prespecified or random days/times within a predetermined period for both methods, with push notifications to urge the participants to register their food intake. In case of non-response, notifications are automatically rescheduled to ensure complete data collection. For use as a food record, respondents can access the app and log their food intake throughout the day. Food records close automatically at the end of the day; recalls close after submission of the consumed items. The recall as well as the food record module provide access to an extensive food list based on the Dutch food composition database (FCDB), which can be accustomed to fit different research purposes. When selecting a food item, respondents are simultaneously prompted to insert portion size, i.e., in household measures (e.g., cups, spoons, glasses), standard portion sizes (e.g., small, medium, large), or weight in grams, and eating occasion/time of consumption. Portion size options can be adjusted, e.g., only entry in grams in case of a weighed food record or time of consumption instead of eating occasion). The app also includes a My Dishes function, which allows the respondent to create their own recipes or product combinations (e.g., a daily breakfast) and only report the total quantity consumed. Subsequently, the app accounts for yield and retention factors. The data are stored on a secure server. If desired, additional questions, i.e., in general or those related to specific food items or eating occasions can be incorporated. This paper describes the development of the system (app and backend), including expert evaluations and usability testing.