Android Smartphone App Research Articles

Measurement of concrete crack feature with android smartphone APP based on digital image processing techniques

Detection and analysis of concrete cracks feature are important aspects of concrete crack research, and non-contact measurement of concrete cracks is an important research direction. In this paper, measurement and analysis of concrete crack feature based on smartphone APP of digital image processing techniques (SADIPT) in android system was investigated. The results showed that the size of single pixel point (SSPP, η) has a good linear relationship with the shooting distance in basic lens under no amplification. The relations between all kinds zoom lens of smartphone and the shooting distance followed the exponential function law. The SSPP of zoom lens (η') can be calculated with an exponential function, and it was determined by smartphone’s camera’s CMOS (complementary metal oxide semiconductor) performance, and the magnification of zoom lens can effectively improve the measurement accuracy. The η' function curves of the same maximum magnification ratio with same basic pixel were slightly different for different smartphone camera’s CMOS while the influence of basic pixel of smartphone zoom lens on η' was significant. The SSPP η' under non-amplification mode decreased as the base pixel increased, but it’s not linear. The results showed that the relations between SSPP η' of all zoom lens and amplification ratio followed the exponential function law at same shooting distance. The accuracy of measuring concrete cracks with smartphone zoom lens or shortening the shooting distance can meet the requirements of engineering detection.

Improving Linkage to and Retention in Care in Newly Diagnosed HIV-Positive Patients Using Smartphones in South Africa: Randomized Controlled Trial.

BackgroundSouth Africa provides free antiretroviral therapy for almost 5 million people living with HIV, but only 71% of the eligible people are on treatment, representing a shortfall in the care cascade, especially among men and youth. Many developing countries have expanded access to smartphones; success in health apps raises the possibility of improving this cascade.ObjectiveSmartLink is a health app for Android smartphones providing HIV-related laboratory results, information, support, and appointment reminders to engage and link patients to care. This study aimed to evaluate the ability of SmartLink to improve linkage to care for HIV-positive smartphone owners.MethodsThis study was a multisite randomized controlled trial in Johannesburg. The intervention arm received the app (along with referral to a treatment site) and the control arm received the standard of care (referral alone). Linkage to care was confirmed by an HIV-related blood test reported on the National Health Laboratory Service database between 2 weeks and 8 months after initiation.ResultsA total of 345 participants were recruited into the study; 64.9% (224/345) of the participants were female and 44.1% (152/345) were aged less than 30 years. In addition, 46.7% (161/345) were employed full time, 95.9% (331/345) had at least secondary school education, and 35.9% (124/345) were from Zimbabwe. Linkage to care between 2 weeks and 8 months was 48.6% (88/181) in the intervention arm versus 45.1% (74/164) in the control (P=.52) and increased to 64.1% (116/181) and 61.0% (100/164) (P=.55), respectively, after the initial 8-month period. Moreover, youth aged 18 to 30-years showed a statistically significant 20% increase in linkage to care for the intervention group.ConclusionsYouth aged less than 30 years have been historically difficult to reach with traditional interventions, and the SmartLink app provides a proof of concept that this population reacts to mobile health interventions that engage patients in HIV care.Trial RegistrationClinicalTrials.gov NCT02756949; https://clinicaltrials.gov/ct2/show/NCT02756949 (Archived by WebCite at http://www.webcitation.org/6z1GTJCNW)

IntensityCheck - The light measuring app for microscope performance checks and consistent fluorescence imaging.

Quantitative fluorescence imaging is an essential tool in biomedical research. It requires consistent and repeatable conditions such as constant sample illumination. Even on a confocal microscope this can usually only be achieved by using an external laser power meter. By combining low-cost wireless Arduino based light sensors with an easy to use Android smartphone app we provide microscope users with a simple but powerful tool to maintain sample illumination for quantitative imaging, for tracking the intensity, stability and alignment of the light sources and for comparing microscope performance.

Design, Development, and Evaluation of an Injury Surveillance App for Cricket: Protocol and Qualitative Study.

BackgroundInjury surveillance and workload monitoring are important aspects of professional sports, including cricket. However, at the community level, there is a dearth of accessible and intelligent surveillance tools. Mobile apps are an accessible tool for monitoring cricket-related injuries at all levels.ObjectiveThe objective of this paper is to share the novel methods associated with the development of the free TeamDoc app and provide evidence from an evaluation of the user experience and perception of the app regarding its functionality, utility, and design.MethodsTeamDoc mobile app for Android and Apple smartphones was developed using 3 languages: C++, Qt Modeling Language, and JavaScript. For the server-side connectivity, Hypertext Preprocessor (PHP) was used as it is a commonly used cross-platform language. PHP includes components that interact with popular database management systems, allowing for secure interaction with databases on a server level. The app was evaluated by administrating a modified user version of the Mobile App Rating Scale (uMARS; maximum score: 5).ResultsTeamDoc is the first complementary, standalone mobile app that records cricket injuries through a smartphone. It can also record cricketing workloads, which is a known risk factor for injury. The app can be used without the need for supplementary computer devices for synchronization. The uMARS scores showed user satisfaction (overall mean score 3.6 [SD 0.5]), which demonstrates its acceptability by cricketers.ConclusionsElectronic injury surveillance systems have been shown to improve data collection during competitive sports. Therefore, TeamDoc may assist in improving injury reporting and may also act as a monitoring system for coaching staff to adjust individual training workloads. The methods described in this paper provide a template for researchers to develop similar apps for other sports.

Self-Monitoring and Self-Efficacy Increase with a Smartphone Application: A Technical Approach to Treating Bipolar Disorder?-Study Protocol for a Clinical Validation Trial

Background: Bipolar disorder (BD) is characterized by mood fluctuations, which are often recognized late by those who are affected. Symptom monitoring via smartphone seems to be an inexpensive and feasible method to detect these fluctuations earlier. The aim of an application (app) for smartphones is to record individual activity patterns (e.g. physical activity, sleep-wake rhythm, digital communication) as characteristic for mood swings in individuals with BD. Methods: We developed the UP! app for Android smartphones, which collects subjective mood daily and continuous data about movement, exercise, sleep duration and intensity of digital communication via GPS and sensors. This pilot trial will include 24 individuals with BD and 24 healthy controls (HC) without a mental disorder. The main aim of this study is to assess the app’s validity to detect mood fluctuations and illness episodes in comparison to a clinical psychiatric interview, validated questionnaires and a fitness tracker. A second aim is to determine whether changes in activity patterns, measured with the app, can detect early warning symptoms of depressive and/or manic episodes. The third aim is the evaluation of users’ acceptance of the app. The recruitment of participants (planned n=48) is ongoing. Discussion: Behavior patterns recognition via smartphone could present an innovative, technological tool for the early detection of BD episodes and could be valuable for long-term research. Registration Details: The trial is approved by the ethics committee of the Medical University Graz, Austria (29-290 ex 16/17). The trial is registered at ClinicalTrials.gov as NCT03275714.

Aurora: Mobile application for analysis of spatial variability of thermal comfort indexes of animals and people, using IDW interpolation

This application note introduces an app for Android smartphones to create maps of the spatial variability of thermal comfort indexes and meteorological parameters. The application was developed through the Java object-oriented programming language, using the integrated Android Studio development environment. The interpolator method employed was the Inverse Distance Weighted (IDW), adopting p = 2. The validations demonstrated that the algorithm is in accordance with the IDW interpolator equation and presented results showed that the maps created by the application can be useful in obtaining diagnoses of the thermal conditions of environments, especially in animal production sheds.

Behavior Change for Youth Drivers: Design and Development of a Smartphone-Based App (BackPocketDriver).

BackgroundThe over-representation of youth in road crash injury and fatality rates is a major public health issue globally. In New Zealand, youth drivers are most vulnerable in the restricted license period when they can drive without the requirement for supervision by an experienced adult. Behavioral change interventions delivered using mobile phone technology to young drivers could serve as a useful mechanism to develop safe driving skills, but this potential remains to be fully explored.ObjectiveThis study aimed to apply behavioral change principles to design and develop a smartphone-based intervention with the aim of helping youth drivers to develop and hone safe driving skills.MethodsAn iterative process was used to support development of the smartphone intervention. We reviewed behavioral change literature, identifying fundamental principles and exploring use of behavior change techniques (BCTs) in other areas of public health. We engaged with key stakeholders, including young drivers, government agencies, and relevant organizations. We also took into account technology adoption considerations when designing the app.ResultsWe developed BackPocketDriver (BPD), an Android smartphone app that uses in-built sensors to monitor and infer driver behavior. The app implements features that were identified during the design process and are traceable to BCTs and theory. A key feature is messaging, which is used to instruct, motivate, educate, and relay feedback to participants. In addition, messaging addresses attitudes and beliefs. Other features include journey feedback summaries, goal setting, achievements, and leaderboards.ConclusionsBPD’s design rests on a sound foundation of theory and evidence. With explicit links between theory and features, the app aims to be an effective intervention to change and improve youth driver behavior. The next phase of this study is to run a small pilot study to assess BPD’s effectiveness.

MHealth Supportive Care Intervention for Parents of Children With Acute Lymphoblastic Leukemia: Quasi-Experimental Pre- and Postdesign Study.

BackgroundAcute lymphoblastic leukemia (ALL) is the most common childhood malignancy. Caring for children with ALL is challenging for parents. A mobile health (mHealth) supportive care intervention was developed to meet parents’ needs.ObjectiveThis study aims to evaluate the potential effectiveness of this mHealth supportive care intervention on emotional distress, social support, care burden, uncertainty in illness, quality of life, and knowledge.MethodsWe conducted a quasi-experimental pre- and postdesign study from June 2015 to January 2016. In total, 101 parents were enrolled in the study, with 50 in the observation group and 51 in the intervention group. Parents in the observation group received the standard health education and were observed for 3 months. Parents in the intervention group received the mHealth supportive care intervention, in addition to the standard health education. The intervention consisted of 2 parts—an Android smartphone app “Care Assistant (CA)” and a WeChat Official Account. The CA with 8 modules (Personal Information, Treatment Tracking, Family Care, Financial and Social Assistance, Knowledge Center, Self- Assessment Questionnaires, Interactive Platform, and Reminders) was the main intervention tool, whereas the WeChat Official Account was supplementary to update information and realize interaction between parents and health care providers. Data of parents’ social support, anxiety, depression, care burden, uncertainty in illness, quality of life, their existing knowledge of ALL and care, and knowledge need were collected before and after the 3-month study period in both groups. For the intervention group, parents’ experience of receiving the intervention was also collected through individual interviews.ResultsOverall, 43 parents in the observation group and 49 in the intervention group completed the study. Results found that the intervention reduced parents’ anxiety (Dint(Post-Pre)=−7.0 [SD 13.1], Dobs(Post-Pre)=−0.4 [SD 15.8], t90=−2.200, P=.03) and uncertainty in illness (Dint(Post-Pre)=−25.0 [SD 8.2], Dobs(Post-Pre)=−19.8 [SD 10.1], t90=−2.761, P=.01), improved parents’ social function (Dint(Post-Pre)=9.0 [SD 32.8], Dobs(Post-Pre)=−7.5 [SD 30.3], t90=2.494, P=.01), increased parents’ knowledge of ALL and care (Dint(Post-Pre)=28.4 [SD 12.4], Dobs(Post-Pre)=17.2 [SD 11.9], t90=4.407, P<.001), and decreased their need for knowledge (Dint(Post-Pre)=−9.9 [SD 11.6], Dobs(Post-Pre)=−1.9 [SD 6.4], t90=−4.112, P<.001). Qualitative results showed that parents were satisfied with the intervention and their role in the caregiving process.ConclusionsThe mHealth intervention in supporting parents of children with ALL is effective. This study is informative for other future studies on providing mHealth supportive care for parents of children with cancer.

Fast analysis of ketamine using a colorimetric immunosorbent assay on a paper-based analytical device

In this study, we designed a rapid colorimetric sensing system using competitive ELISA test on a microfluidic paper-based analytical device for the detection of ketamine, a frequently abused drug. Oral fluid was selected for the test to facilitate the collection of samples based on its advantages of low infection risk, noninvasiveness of sample collection, and decreased chance of sample adulteration. After optimization of the operation parameters, including reaction temperature, vibration washing time, reaction time, and antibody concentration, the resulting assay can be completed in as little as 6 min with a detection limit of 0.03 ng/mL. Moreover, we developed an Android smartphone app to analyze and measure the results of the test, further enhancing the test’s portability, and image recording and data transmission capabilities. In order to test the feasibility and performance of the optimized colorimetric assay, 90 oral fluid samples from drug abuse patients were tested. The paper-based platform features 90% sensitivity (confidence interval (CI): 76.34–97.21%) and 92% specificity (CI: 80.77–97.78%) for ketamine analysis. This competitive paper-based ELISA sensing system provides a rapid, convenient, sensitive, and high-throughput approach for drug monitoring.

A mobile computer aided system for optic nerve head detection

Background and objectiveThe detection of optic nerve head (ONH) in retinal fundus images plays a key role in identifying Diabetic Retinopathy (DR) as well as other abnormal conditions in eye examinations. This paper presents a method and its associated software towards the development of an Android smartphone app based on a previously developed ONH detection algorithm. The development of this app and the use of the d-Eye lens which can be snapped onto a smartphone provide a mobile and cost-effective computer-aided diagnosis (CAD) system in ophthalmology. In particular, this CAD system would allow eye examination to be conducted in remote locations with limited access to clinical facilities. MethodsA pre-processing step is first carried out to enable the ONH detection on the smartphone platform. Then, the optimization steps taken to run the algorithm in a computationally and memory efficient manner on the smartphone platform is discussed. ResultsThe smartphone code of the ONH detection algorithm was applied to the STARE and DRIVE databases resulting in about 96% and 100% detection rates, respectively, with an average execution time of about 2 s and 1.3 s. In addition, two other databases captured by the d-Eye and iExaminer snap-on lenses for smartphones were considered resulting in about 93% and 91% detection rates, respectively, with an average execution time of about 2.7 s and 2.2 s, respectively.

A Smartphone App for Improvement of Colonoscopy Preparation (ColoprAPP): Development and Feasibility Study.

BackgroundOptimal bowel preparation is one of the major cornerstones for quality of colonoscopy. But poor bowel preparation still occurs in 10% to 25% of all patients. To optimize patient guidance, we developed a new smartphone app (ColoprAPP) for Android smartphones which guides and accompanies the patient starting 4 days before colonoscopy throughout the whole colonoscopy preparation procedure.ObjectiveThe objective of this study was to assess the function of a newly developed smartphone app for supporting colonoscopy preparation.MethodsWe carried out a prospective feasibility study including 25 patients undergoing outpatient colonoscopy at our hospital. As a control, we retrieved the data of 25 patients undergoing outpatient colonoscopy matching in age, sex, and indication for colonoscopy from our colonoscopy database. Patients were asked to download the smartphone app, ColoprAPP, in addition to being given the regular colonoscopy preparation leaflet. All colonoscopies were performed in the morning after using a split-dose preparation containing a polyethlene glycol–based purgative. The study was designed to test feasibility of the prototype, evaluate grade of bowel cleanliness (Boston bowel preparation scale [BBPS]), and assess patient satisfaction with the app.ResultsThe smartphone app use was feasible in all patients. BBPS count as a marker for grade of bowel preparation was significantly higher in the smartphone app–supported group (mean 8.1 [SD 0.3] vs 7.1 [SD 0.4], P=.02). Left (mean 2.8 [SD 0.1] vs 2.4 [SD 0.11], P=.02) and transverse colon (mean 2.8 [SD 0.07] vs 2.4 [SD 0.11], P<.001) revealed significantly higher BBPS counts in the smartphone app–supported group than in controls. Patient satisfaction with a smartphone app–supported colonoscopy preparation was high with an average numeric rating scale score for usefulness of 8.2 (visual analog scale 1-10).ConclusionsA novel developed smartphone app for reinforced education of bowel cleansing was feasible and led to high BBPS scores and patient satisfaction.Trial registrationClinicalTrials.gov NCT02512328; https://clinicaltrials.gov/ct2/show/NCT02512328 (Archived by WebCite at http://www.webcitation.org/6sz3Kk26z)

Outdoor GPS and Indoor Magnetic Field Positioning: combining survey technology and app development

This work tested a solution for outdoor and indoor positioning. In order to find a suitable solution for geo-applications like in caves and mines, we tested the GPS and Open Street Map cartography for outdoor and Magnetic Field positioning and Indoor Atlas technology for indoor in the Urbino University residences. The results of this work can be already used for university students and hosts in Urbino; moreover, these could be also easily applied to geotouristic sites by means of the development of an app for Android smartphones.

Adhesive RFID Sensor Patch for Monitoring of Sweat Electrolytes.

Wearable digital health devices are dominantly found in rigid form factors such as bracelets and pucks. An adhesive radio-frequency identification (RFID) sensor bandage (patch) is reported, which can be made completely intimate with human skin, a distinct advantage for chronological monitoring of biomarkers in sweat. In this demonstration, a commercial RFID chip is adapted with minimum components to allow potentiometric sensing of solutes in sweat, and surface temperature, as read by an Android smartphone app with 96% accuracy at 50 mM Na(+) (in vitro tests). All circuitry is solder-reflow integrated on a standard Cu/polyimide flexible-electronic layer including an antenna, but while also allowing electroplating for simple integration of exotic metals for sensing electrodes. Optional paper microfluidics wick sweat from a sweat porous adhesive allowing flow to the sensor, or the sensor can be directly contacted to the skin. The wearability of the patch has been demonstrated for up to seven days, and includes a protective textile which provides a feel and appearance similar to a standard Band-Aid. Applications include hydration monitoring, but the basic capability is extendable to other mM ionic solutes in sweat (Cl(-), K(+), Mg(2+), NH4(+), and Zn(2+)). The design and fabrication of the patch are provided in full detail, as the basic components could be useful in the design of other wearable sensors.

System-level design of an RFID sweat electrolyte sensor patch.

Wearable digital health devices are dominantly found in rigid form factors such as bracelets and pucks. An adhesive RFID sensor bandage (patch) is reported, which can be made completely intimate with human skin, a distinct advantage for chronological monitoring of biomarkers in sweat. In this demonstration, a commercial RFID chip is adapted with minimum components to allow potentiometric sensing of mM ionic solutes in sweat, and surface temperature, as read by an Android smart-phone app (in-vitro tests).

How smartphones are changing the face of mobile and participatory healthcare: an overview, with example from eCAALYX.

The latest generation of smartphones are increasingly viewed as handheld computers rather than as phones, due to their powerful on-board computing capability, capacious memories, large screens and open operating systems that encourage application development. This paper provides a brief state-of-the-art overview of health and healthcare smartphone apps (applications) on the market today, including emerging trends and market uptake. Platforms available today include Android, Apple iOS, RIM BlackBerry, Symbian, and Windows (Windows Mobile 6.x and the emerging Windows Phone 7 platform). The paper covers apps targeting both laypersons/patients and healthcare professionals in various scenarios, e.g., health, fitness and lifestyle education and management apps; ambient assisted living apps; continuing professional education tools; and apps for public health surveillance. Among the surveyed apps are those assisting in chronic disease management, whether as standalone apps or part of a BAN (Body Area Network) and remote server configuration. We describe in detail the development of a smartphone app within eCAALYX (Enhanced Complete Ambient Assisted Living Experiment, 2009-2012), an EU-funded project for older people with multiple chronic conditions. The eCAALYX Android smartphone app receives input from a BAN (a patient-wearable smart garment with wireless health sensors) and the GPS (Global Positioning System) location sensor in the smartphone, and communicates over the Internet with a remote server accessible by healthcare professionals who are in charge of the remote monitoring and management of the older patient with multiple chronic conditions. Finally, we briefly discuss barriers to adoption of health and healthcare smartphone apps (e.g., cost, network bandwidth and battery power efficiency, usability, privacy issues, etc.), as well as some workarounds to mitigate those barriers.