Background and Aim: Preeclampsia is one of the most prominent cases of pregnancy related diseases that threatens health at global level, especially in developing countries. In Iran, with 14% of outbreak, it is the second most common cause of maternal mortality. The main goal of this study was to identify the information requirements of the Android-based preeclampsia self-Management application. Materials & Methods: This was a descriptive study that was done in 2018 in Amir_Almomenin Hospital affiliated to Semnan University of Medical Sciences in two stages of reviewing the sources and the need for data elements. In the review phase, after studying the articles and study, the data requirements and factors which affecting the prevalence of preeclampsia were identified and a survey of qualified physicians was done by designing a researcher-made questionnaire. Results: This research results indicate that 63. 9% of the respondents assigned to the elements mentioned in the demographic findings. 75. 9% of them identified health information elements as very important. Also, 77. 85% of the research community considered the elements in the lifestyle sector to be of the highest importance. All Received: Jun 2018 Accepted: Oct 2018 participants recognized that reminder in the program was necessary. Approximately 33. 33% of them reconsidered sport education to be at the lowest level, while 45. 24% rated it as being of the highest importance. Conclusion: The information requirements of this program were determined in 6 groups of health history, educational tips, lifestyle, referral alarms, and reporting. This program can help pregnant mothers with preeclampsia to control their disease to minimize complications by observing proper nutrition and principles of treatment.

Background: Neonatal jaundice resulting from raised blood bilirubin levels is one of the most common clinical conditions that needs medical attention. To initiate appropriate management that can both prevent and treat severe neonatal jaundice, screening methods that measure bilirubin level are warranted. Methods: In this study, we present an Android OS-based application for detecting neonatal jaundice. We used the application to detect jaundice in 113 neonates. Our smartphone-based estimation of bilirubin levels depends on a smartphone, a color calibration card, and a 100X zoom microscope clip. Our application was designed to acquire images of the newborn’ s forehead skin in a standardized manner, estimate the average R, G, B scores of the images that have been taken from the forehead skin and calibration card, and then convert them to hue, saturation, intensity (HSI) parameters. All these are performed offline; in this application, we used offline machine learning and regression techniques for analysis Results: Our smartphone-based estimation of bilirubin levels had a sensitivity of 68% and specificity of 92. 3% for estimating the bilirubin levels of less than 10 mg/dL and sensitivity of 82. 1% and specificity of 100% for estimating the bilirubin levels of less than 15 mg/dL. Our application-based estimation of bilirubin levels had the correlation of 0. 479 with the total serum bilirubin values. Conclusions: Our results suggest that our smartphone-based application can serve as a promising screening tool for neonatal jaundice, and it can aid in determining neonates requiring a blood draw for measuring total serum bilirubin level.

Background: Electromyography (EMG) signal processing and Muscle Onset Latency (MOL) are widely used in rehabilitation sciences and nerve conduction studies. The majority of existing software packages provided for estimating MOL via analyzing EMG signal are computerized, desktop based and not portable; therefore, experiments and signal analyzes using them should be completed locally. Moreover, a desktop or laptop is required to complete experiments using these packages, which costs. Objective: Develop a non-expensive and portable Android application (app) for estimating MOL via analyzing surface EMG. Material and Methods: A multi-layer architecture model was designed for implementing the MOL estimation app. Several Android-based algorithms for analyzing a recorded EMG signal and estimating MOL was implemented. A graphical user interface (GUI) that simplifies analyzing a given EMG signal using the presented app was developed too. Results: Evaluation results of the developed app using 10 EMG signals showed promising performance; the MOL values estimated using the presented app are statistically equal to those estimated using a commercial Windows-based surface EMG analysis software (MegaWin 3. 0). For the majority of cases relative error <10%. MOL values estimated by these two systems are linearly related, the correlation coefficient value ~ 0. 93. These evaluations revealed that the presented app performed as well as MegaWin 3. 0 software in estimating MOL. Conclusion: Recent advances in smart portable devices such as mobile phones have shown the great capability of facilitating and decreasing the cost of analyzing biomedical signals, particularly in academic environments. Here, we developed an Android app for estimating MOL via analyzing the surface EMG signal. Performance is promising to use the app for teaching or research purposes.

Education via smart mobile phone and mobile health applications is a key element in e-learning. For the first time and in cooperation with occupational therapists and Health Information management specialists, an applied educational smart phone-based program was designed and implemented for mothering handling of children with cerebral palsy (CP) by caregivers. For this purpose, InteliJIDe application version 13 for Android was used. This application includes sections of acquaintance with children with CP, principles of motor development in children with CP, feeding, dressing, toileting, bathing, sleeping, lifting and carrying, playing, anticonvulsant drugs, and about us. It is free and can be installed on smart mobile phones and Android tablets via Bluetooth. This application is an important step in easy, fast, and free access of families of children with CP to daily care information. It is hoped that this software resolve some of these families’ problems.

Background and Aim: Preeclampsia is one of the most serious cases of high-risk pregnancies that endanger women’, s health worldwide, especially in developing countries. Preeclampsia is a specific pregnancy syndrome with a prevalence of about 7-14%, which is one of the three leading causes of death in pregnant women. Preeclampsia is the second most common cause of maternal mortality in Iran and accounts for 14% of maternal mortality. The present study was conducted to design, create and evaluate mobile-based preeclampsia self-care application. Materials and Methods: This study was conducted in four stages to assess the needs of information elements, design, create and evaluate preeclampsia self-care application. In needs assessment step, 42 specialists, assistants and personnel related to the subject working in the Amir Al-Momenin (AS) Educational, Research and Treatment Center affiliated to Semnan University of Medical Sciences participated. The program was then initially evaluated by 7 physicians, and finally the suggestions provided by users in the design of the program were applied and the final version of the program was completed. The application was designed in the Android Studio environment and then its usability was evaluated using the opinions of 20 mothers and the QUIS tool. Results: The information elements and functional capabilities required by the program were determined. In addition, the program established communication between the patient and the provider, also created the possibility of care management and control of the disease process. The performance of the program was evaluated by physicians and experts and then evaluated by pregnant mothers in terms of usability. The findings showed that users were satisfied with the application. Conclusion: The use of mobile-based applications is a useful way to increase knowledge and promote the health of pregnant mothers and facilitate their access to medical information and acquire the necessary skills in their disease. This program helps pregnant mothers with preeclampsia to control their disease by observing proper nutrition and treatment principles to minimize the complications of their disease.

Background: Monitoring the adherence of pregnant women to taking iron supplements indicates controlling the appropriateness of taking a certain number of supplements. This increases the odds of effective iron absorption; a process that occurs by consuming at least 30 iron pills a month to prevent gestational anemia. This study aimed to determine the effects of monitoring pregnant women’ s compliance in taking up iron supplements through an Android application in Jambi City, Indonesia. Methods: This was a quasi-experimental single group study with a pre-test-post-test design. The study subjects included 50 pregnant women in their third trimester referring to 3 maternity Hospitals in Jambi City, Indonesia, in 2020. Initial data were obtained through Hemoglobin (Hb) measurements before being given a monitoring application and subsequent Hb level checks after giving the application. The obtained data were analyzed by t-test and Mann-Whitney U test in SPSS v. 16. A significance level of 5% was considered. Results: The results obtained in the initial examination indicated that the minimum Hb level was equal to 7. 3 g/dL and the maximum level was measured as 11. 2 g/dL. After the intervention, the Hb level increased to a minimum of 7. 6 g/dL and a maximum of 12. 2 g/dL. The Mann-Whitney U test data suggested a significant difference in the degree of compliance of pregnant women with iron supplementation (P=0. 010). Conclusion: Monitoring through the Android application increased pregnant women’ s compliance with taking iron supplements and presented a linear impact on increasing their Hb level.

2Background and Aim: Despite the continuous progress in medicine, COPD (Chronic Obstructive Pulmonary Disease) is still a progressive, incurable and chronic respiratory condition that limits the patients’ functions in various dimensions, and significantly reduce their quality of life. In this way, self-care of patients and the use of related tools have a significant effect in disease control and treatment. The purpose of this research was design and development of an Android-based application for COPD. Materials and Methods: This research was a descriptive developmental type with a practical approach. Initially, based on the study of library resources, guidelines, and the examination of the medical records of COPD inpatients in Firouzabadi Hospital, a questionnaire was designed to identify the information requirements, data items and features of the application. Then it was reviewed and finalized by a sample of 10 (randomized and convenience sampling) internal and lung specialist doctors in Firouzabadi and Hazrat Rasool hospitals affiliated to Iran University of Medical Sciences. The data was analyzed using descriptive statistics, and then scenario tables and UML diagrams were illustrated to show the overall flow of the application. The application was designed and developed using the Java programming language in the Android Studio 2021 platform. After installing the application on the mobile phones of ten COPD patients of the internal and pulmonary clinic of Firouzabadi Shahre Rey Hospital, and using it for a week, the opinions of the patients about the usability of the application were collected through the QUIS questionnaire, and analyzed.   Results: application sections were determined following experts’ survey, personal information items, clinical information, disease management, reporting, and training points, which were provided to patients after design for use and evaluation. At the end of the research, the results of the evaluation of the usability and satisfaction level of the application showed that from the patients’ point of view, the application is at a good level with an average score of 1. 8 (out of 10 points). Conclusion: The developed self-care application can be used to increase awareness, help to manage the disease, increase the level of quality of life, and reduce the complications and disease burden for patients with COPD

There are hundreds of ventilator modes on different ventilators. Despite different names, many are similar in functions and options. Educational institutions only teach a limited collection of ventilator modes of a few numbers of models; therefore, graduates may have substantial difficulties encountering new ventilator models with unfamiliar mode names on them. In this article, an Android application for finding similar modes on different ventilators is presented. The aim is to help an intensive care practitioner to easily find a familiar mode on a new ventilator.