MyDietCam: Development and usability study of a food recognition integrated dietary monitoring smartphone application
Ontology highlight
ABSTRACT: Background
Diet monitoring has been linked with improved eating habits and positive
SUBMITTER: Kong N
PROVIDER: S-EPMC9834938 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:IntroductionDigital technology creates the opportunity to develop and evaluate new tools, such as smartphone applications, to support integrated atrial fibrillation management. This study aimed to develop, evaluate, and validate a new, integrated care application (AF-EduApp) mainly focusing on targeted atrial fibrillation education to improve patient self-care capabilities and therapy adherence.MethodsThe newly developed AF-EduApp, available for Android and iOS, consists of six different modules. The prototype was validated and optimized for its usability and functionality at Jessa Hospital Hasselt and Antwerp University Hospital in two phases: (1) validity evaluation with interviews of an expert panel with 15 healthcare professionals and 10 atrial fibrillation patients, and (2) a pilot study of 1 month with 20 atrial fibrillation patients.ResultsBoth experts and patients found that the application aids atrial fibrillation management. Based on the input of patients and experts, the main optimizations concerned the medication module (patient choice on setting reminder; interactivity of reminders with a "taken" or "snooze" function) and development of a clinical dashboard for the caregivers allowing telemonitoring of measurements and feedback to the patients. After the pilot study (n = 20), 16 patients indicated they wanted to use the app for a longer period. The measurement (27%) and education (17%) modules were the two most used modules with a significant improvement in knowledge (71.9% to 87.5%; P = 0.013).DiscussionThe AF-EduApp received a positive evaluation from health professionals and atrial fibrillation patients. Further development should be focused on the medication module and improvement of the clinical dashboard.
| S-EPMC8725214 | biostudies-literature
Project description:BackgroundDietary monitoring is critical to maintaining human health. Social media platforms are widely used for daily recording and communication for individuals' diets and activities. The textual content shared on social media offers valuable resources for dietary monitoring.ObjectiveThis study aims to describe the development of iFood, an applet providing personal dietary monitoring based on social media content, and validate its usability, which will enable efficient personal dietary monitoring.MethodsThe process of the development and validation of iFood is divided into four steps: Diet datasets construction, diet record and analysis, diet monitoring applet design, and diet monitoring applet usability assessment. The diet datasets were constructed with the data collected from Weibo, Meishijie, and diet guidelines, which will be used as the basic knowledge for further model training in the phase of diet record and analysis. Then, the friendly user interface was designed to link users with backend functions. Finally, the applet was deployed as a WeChat applet and 10 users from the Beijing Union Medical College have been recruited to validate the usability of iFood.ResultsThree dietary datasets, including User Visual-Textual Dataset, Dietary Information Expansion Dataset, and Diet Recipe Dataset have been constructed. The performance of 4 models for recognizing diet and fusing unimodality data was 40.43%(dictionary-based model), 18.45%(rule-based model), 59.95%(Inception-ResNet-v2), and 51.38% (K-nearest neighbor), respectively. Furthermore, we have designed a user-friendly interface for the iFood applet and conducted a usability assessment, which resulted in an above-average usability score.ConclusionsiFood is effective for managing individual dietary behaviors through its seamless integration with social media data. This study suggests that future products could utilize social media data to promote healthy lifestyles.
| S-EPMC10617295 | biostudies-literature
Project description:BackgroundObesity interventions face the problem of weight regain after treatment as a result of low compliance. Mobile health (mHealth) technologies could potentially increase compliance and aid both health care providers and patients.ObjectiveThis study aimed to evaluate the acceptability and usability and define system constraints of an mHealth system used to monitor dietary habits of adolescents in real life, as a first step in the development of a self-monitoring and lifestyle management system against adolescent obesity.MethodsWe recruited 26 students from a high school in Stockholm, Sweden. After a 30-minute information meeting and 5-minute individual instruction on how to use an mHealth system (smartphone with app and two external sensors), participants used it for 2-3 weeks to objectively collect dietary habits. The app and sensors were used by the participants, without supervision, to record as many main meals and snacks as possible in real life. Feasibility was assessed following the "mHealth evidence reporting and assessment checklist," and usability was assessed by questionnaires. Compliance was estimated based on system use, where a registration frequency of 3 main meals (breakfast, lunch, and dinner) per day for the period of the experiment, constituted 100% compliance.ResultsParticipants included in the analysis had a mean age of 16.8 years (SD 0.7 years) and BMI of 21.9 kg/m2 (SD 4.1 kg/m2). Due to deviations from study instructions, 2 participants were excluded from the analysis. During the study, 6 participants required additional information on system use. The system received a 'Good' grade (77.1 of 100 points) on the System Usability Scale, with most participants reporting that they were comfortable using the smartphone app. Participants expressed a willingness to use the app mostly at home, but also at school; most of their improvement suggestions concerned design choices for the app. Of all main meals, the registration frequency increased from 70% the first week to 76% the second week. Participants reported that 40% of the registered meals were home-prepared, while 34% of the reported drinks contained sugar. On average, breakfasts took place at 8:30 AM (from 5:00 AM to 2:00 PM), lunches took place at 12:15 PM (from 10:15 AM to 6:15 PM), and dinners took place at 7:30 PM (from 3:00 PM to 11:45 PM). When comparing meal occurrence during weekdays vs weekends, breakfasts and lunches were eaten 3 hours later during weekends, while dinner timing was unaffected.ConclusionsFrom an infrastructural and functional perspective, system use was feasible in the current context. The smartphone app appears to have high acceptability and usability in high school students, which are the intended end-users. The system appears promising as a relatively low-effort method to provide real-life dietary habit measurements associated with overweight and obesity risk.
| S-EPMC7404017 | biostudies-literature
Project description:Organophosphate (OP) pesticides remain a worldwide health concern due to their acute or chronic poisoning and widespread use in agriculture around the world. There is a need for robust and field-deployable tools for onsite detection of OP pesticides in food and water. Herein, we present an integrated smartphone/resistive biosensor for simple, rapid, reagentless, and sensitive monitoring of OP pesticides in food and environmental water. The biosensor leverages the hydrolytic activity of acetylcholinesterase (AChE) to its substrate, acetylcholine (ACh), and unique transport properties of polyaniline nanofibers (PAnNFs) of chitosan/AChE/PAnNF/carbon nanotube (CNT) nanocomposite film on a gold interdigitated electrode. The principle of the sensor relies on OP inhibiting AChE, thus, reducing the rate of ACh hydrolysis and consequently decreasing the rate of protons doping the PAnNFs. Such resulted decrease in conductance of PAnNF can be used to quantify OP pesticides in a sample. A mobile app for the biosensor was developed for analyzing measurement data and displaying and sharing testing results. Under optimal conditions, the biosensor demonstrated a wide linear range (1 ppt-100 ppb) with a low detection limit (0.304 ppt) and high reproducibility (RSD <5%) for Paraoxon-Methyl (PM), a model analyte. Furthermore, the biosensor was successfully applied for analyzing PM spiked food/water samples with an average recovery rate of 98.3% and provided comparable results with liquid chromatography-mass spectrometry. As such, the nanosensing platform provides a promising tool for onsite rapid and sensitive detection of OP pesticides in food and environmental water.
| S-EPMC10732357 | biostudies-literature
Project description:BackgroundThe rising number of dementia diagnoses and imminent adoption of disease-modifying treatments necessitate innovative approaches to identify individuals at risk, monitor disease course and intervene non-pharmacologically earlier in the disease course. Digital assessments of dementia risk and cognitive function have the potential to outperform traditional in-person assessments in terms of their affordability, accuracy and longitudinal tracking abilities. However, their accessibility and reliability in older adults is unclear.AimsTo evaluate the usability and reliability of a smartphone assessment of lifestyle and cognitive factors relevant to dementia risk in a group of UK-based older adults.MethodCognitively healthy adults (n = 756) recruited through the Dementias Platform UK Great Minds volunteer register completed three assessments of cognitive function and dementia risk over a 3-month period and provided usability feedback on the Five Lives smartphone application (app). We evaluated cognitive test scores for age, gender and higher education effects, normality distributions, test-retest reliability and their relationship with participants' lifestyle dementia risk factors.ResultsParticipants found the app 'easy to use', 'quick to complete' and 'enjoyable'. The cognitive tests showed normal or near-to-normal distributions, variable test-retest reliabilities and age-related effects. Only tests of verbal ability showed gender and education effects. The cognitive tests did not correlate with lifestyle dementia risk scores.ConclusionsThe Five Lives assessment demonstrates high usability and reliability among older adults. These findings highlight the potential of digital assessments in dementia research and clinical practice, enabling improved accessibility and better monitoring of cognitive health on a larger scale than traditional in-person assessments.
| S-EPMC11443166 | biostudies-literature
Project description:BackgroundRural-urban disparities in access to health services and the burden of diet-related noncommunicable diseases are exacerbated among Mexican immigrant farmworkers due to work demands, social and geographical isolation, literacy issues, and limited access to culturally and language-competent health services. Although mobile health (mHealth) tools have the potential to overcome structural barriers to health services access, efficacious mHealth interventions to promote healthy eating have not considered issues of low literacy and health literacy, and food preferences and norms in the Mexican immigrant farmworker population. To address this critical gap, we conducted a series of preliminary studies among Mexican immigrant farmworkers with the long-term goal of developing a culture- and literacy-specific smartphone app integrating dietary assessment through food photography, diet analyses, and a non-text-based dietary intervention.ObjectiveThis study aimed to report adherence and reactivity to a 14-day food photography dietary assessment protocol, in which Mexican immigrant farmworker women were instructed to take photos of all foods and beverages consumed.MethodsWe developed a secure mobile app with an intuitive graphical user interface to collect food images. Adult Mexican immigrant farmworker women were recruited and oriented to the photography protocol. Adherence and reactivity were examined by calculating the mean number of food photos per day over time, differences between the first and second week, and differences between weekdays and weekends. The type of foods and meals photographed were compared with reported intake in three 24-hour dietary recalls.ResultsIn total, 16 Mexican farmworker women took a total of 1475 photos in 14 days, with a mean of 6.6 (SD 2.3) photos per day per participant. On average, participants took 1 fewer photo per day in week 2 compared with week 1 (mean 7.1, SD 2.5 in week 1 vs mean 6.1, SD 2.6 in week 2; P=.03), and there was a decrease of 0.6 photos on weekdays versus weekends (mean 6.4, SD 2.5 on weekdays vs mean 7, SD 2.7 on weekends; P=.50). Of individual food items, 71% (352/495) of foods in the photos matched foods in the recalls. Of all missing food items (n=138) and meals (n=36) in the photos, beverages (74/138, 54%), tortillas (15/138, 11%), snacks 16/36, 44%), and dinners (10/36, 28%) were the most frequently missed. Most of the meals not photographed (27/36, 75%) were in the second week of the protocol.ConclusionsDietary assessment through food photography is feasible among Mexican immigrant farmworker women. For future protocols, substantive adjustments will be introduced to reduce the frequency of missing foods and meals. Our preliminary studies are a step in the right direction to extend the benefits of mHealth technologies to a hard-to-reach group and contribute to the prevention and control of diet-related noncommunicable diseases.
| S-EPMC11681282 | biostudies-literature
Project description:BackgroundPatients with colorectal cancer who undergo surgery face many postoperative problems. These problems include the risk of relapse, side effects, and long-term complications.ObjectiveThis study sought to design and develop a remote monitoring system as a technological solution for the postdischarge care of these patients.MethodsThis research was conducted in 3 main steps: system feature extraction, system design, and evaluation. After feature extraction from a systematic review, the necessary features were defined by 18 clinical experts in Iran. In the next step, the architecture of the system was designed based on the requirements; the software and hardware parts of the system were embedded in the architecture, then the software system components were drawn using the unified modeling language diagrams, and the details of software system implementation were identified. Regarding the hardware design, different accessible hardware modules were evaluated, and suitable ones were selected. Finally, the usability of the system was evaluated by demonstrating it over a Skype virtual meeting session and using Nilsen's usability principles.ResultsA total of 21 mandatory features in 5 main categories, including patient information registration, periodic monitoring of health parameters, education, reminders, and assessments, were defined and validated for the system. The software was developed using an ASP.Net core backend, a Microsoft SQL Server database, and an Ionic frontend alongside the Angular framework, to build an Android app. The user roles of the system included 3 roles: physicians, patients, and the system administrator. The hardware was designed to contain an Esp8266 as the Internet of Things module, an MLX90614 infrared temperature sensor, and the Maxim Integrated MAX30101 sensor for sensing the heartbeat. The hardware was designed in the shape of a wristband device using SolidWorks 2020 and printed using a 3D printer. The firmware of the hardware was developed in Arduino with the capability of firmware over the air. In evaluating the software system from the perspective of usability, the system received an average score of 3.8 out of 5 from 4 evaluators.ConclusionsSensor-based telemonitoring systems for patients with colorectal cancer after surgery are possible solutions that can make the process automatic for patients and caregivers. The apps for remote colorectal patient monitoring could be designed to be useful; however, more research regarding the developed system's implementation in clinic settings and hospitals is required to understand the probable barriers and limitations.
| S-EPMC9978953 | biostudies-literature
Project description:Background:Obesity is a global epidemic. Behavior change monitoring using a smartphone application (app) can support weight management in obese patients. These apps must undergo usability testing, which is an important step in mobile healthcare app development. The current study aimed to develop a mobile app for behavioral monitoring and to test its usability including technical effectiveness, user efficiency, and user satisfaction for obese adults. Methods:Development of the Dr. Youth app components included information on behavioral monitoring indicators and their obesity subtypes. The usability of the app was tested with 50 obese adults in a university hospital. Participants were asked to complete eight tasks for evaluating the technical effectiveness of the app. The time to complete each task was measured to test user efficiency. To explore user satisfaction, each participant completed the System Usability Scale (SUS). Descriptive statistics were used to examine the mean user efficiency and SUS scores. Results:Fifty adults (14 men and 36 women, aged 20-59 years) who are obese (body mass index ?25 kg/m2) were recruited. The mean age of participants was 42.6 years (standard deviation [SD], 10.8 years); their mean body mass index was 29.6 kg/m2 (SD, 5.7 kg/m2). The tasks were completed with a 99% success rate. The overall mean SUS score was 76.65 (SD, 15.43). Conclusion:The Dr. Youth app shows acceptable technical effectiveness, user efficiency, and user satisfaction. Future study is warranted to establish the app's clinical efficacy.
| S-EPMC6774444 | biostudies-literature
Project description:The present study tests the feasibility, acceptability, and utility of the novel smartphone application-Time2Feel-to monitor family members' emotional experiences, at the experiential and physiological level, and their context. To our knowledge, Time2Feel is the first of its kind, having the capability to monitor multiple members' emotional experiences simultaneously and survey users' emotional experiences when experiencing an increase in physiological arousal. In this study, a total of 44 parents and children used Time2Feel along with the Empatica E4 wrist-wearable device for 10 days. Engagement rates were within the acceptable range and consistent with previous work using experience sampling methods. Perceived ease of use and satisfaction fell mostly in the moderate range, with users reporting challenges with connectivity. We further discuss how addressing connectivity would increase acceptability. Finally, Time2Feel was successful at identifying physiological deviations in electrodermal activity for parents and children alike, and even though responses to those deviation-generated surveys were largely consistent with random survey responses, some differences were noted for mothers and fathers. We discuss the implications of using Time2Feel for understanding families' emotional and stressful experiences day-to-day.
| S-EPMC10708754 | biostudies-literature
Project description:BackgroundRepeated applications of short-term dietary assessment instruments are recommended for estimating usual dietary intake. For this purpose, NutriDiary, a smartphone app for collecting weighed dietary records (WDRs) in the German population, was developed.ObjectiveWe aim to describe NutriDiary and evaluate its usability and acceptability.MethodsNutriDiary was developed as a WDR, allowing users to enter food items via text search, barcode scanning, or free text entry. The sample for the evaluation study included 74 participants (n=51, 69% female, aged 18-64 years), including 27 (37.5%) experts and 47 (63.5%) laypersons (including n=22, 30%, nutrition students). Participants completed a 1-day WDR and entered a predefined sample meal (n=17 foods) the following day by using NutriDiary. An evaluation questionnaire was answered from which the system usability scale (SUS) score (0-100) was calculated. A backward selection procedure (PROC REG in SAS; SAS Institute) was used to identify potential predictors for the SUS score (age, sex, status [expert or laypersons], and operating system [iOS or Android]).ResultsThe median SUS score of 75 (IQR 63-88) indicated good usability. Age was the only characteristic identified as a potential predictor for a lower SUS score (P<.001). The median completion time for an individual WDR was 35 (IQR 19-52) minutes. Older participants took longer to enter the data than younger ones (18-30 y: median 1.5, IQR 1.1-2.0 min/item vs 45-64 y: median 1.8, IQR 1.3-2.3 min/item). Most participants expressed a preference for NutriDiary over the traditional paper-based method.ConclusionsGood usability and acceptability make NutriDiary promising for use in epidemiological studies.
| S-EPMC11833184 | biostudies-literature