Smartphone Platform Research Articles

Validity of smartphone-based postural control assessment for chronic ankle instability

Decreased postural control ability are commonly found in who suffer from chronic ankle instability. Identifying decreased postural control ability could help to make an appropriate rehabilitation plan and reduce the possibility of recurrent ankle sprain. With newly emerging technologies, utilizing the inherent sensors in smartphones may provide a method of easy-access and portable alternative for postural control assessment. The purpose of this study is to establish the level of validity of smartphone-based postural control assessment. Thirty-eight participants, with at least one ankle instable, were assessed using the smartphone application developed for recording built-in accelerometer data. Zenfone 3 smartphone was positioned at the middle of the shin. Participants completed 4 trails of single leg stance balance test each in eyes opened and eyes closed conditions, while simultaneously recording data from force platform, which was considered as the golden standard of postural sway assessment tool. Correlation between smartphone and force platform was evaluate using SPSS 20.0, and statistical significance was set as alpha < 0.05. Pearson's correlation coefficient of eyes opened condition in medial-lateral direction between smartphone-based assessment and force platform was 0.700 ( P < 0.005), and 0.759 ( P < 0.005) in anterior-posterior direction. Pearson's correlation coefficient of eyes closed condition in medial-lateral direction between smartphone-based assessment and force platform was 0.734 ( P < 0.005), and 0.803 ( P < 0.005) in anterior-posterior direction. Our results show that the smartphone assessment has good correlation compared to the force platform when recording the performance of single leg stance balance test. The smartphone-based assessment shows potential as an easy-use and accessible tool to assess postural control ability.

From smartphone to EHR: a case report on integrating patient-generated health data

Patient-generated health data (PGHD), collected from mobile apps and devices, represents an opportunity for remote patient monitoring and timely interventions to prevent acute exacerbations of chronic illness—if data are seen and shared by care teams. This case report describes the technical aspects of integrating data from a popular smartphone platform to a commonly used EHR vendor and explores the challenges and potential of this approach for disease management. Consented subjects using the Asthma Health app (built on Apple’s ResearchKit platform) were able to share data on inhaler usage and peak expiratory flow rate (PEFR) with a local pulmonologist who ordered this data on Epic’s EHR. For users who had installed and activated Epic’s patient portal (MyChart) on their iPhone and enabled sharing of health data between apps via HealthKit, the pulmonologist could review PGHD and, if necessary, make recommendations. Four patients agreed to share data with their pulmonologist, though only two patients submitted more than one data point across the 4.5-month trial period. One of these patients submitted 101 PEFR readings across 65 days; another submitted 24 PEFR and inhaler usage readings across 66 days. PEFR for both patients fell within predefined physiologic parameters, except once where a low threshold notification was sent to the pulmonologist, who responded with a telephone discussion and new e-prescription to address symptoms. This research describes the technical considerations and implementation challenges of using commonly available frameworks for sharing PGHD, for the purpose of remote monitoring to support timely care interventions.

Design of a Smartphone Platform Compact Optical System Operational Both in Visible and Near Infrared Spectral Regime

We report here the design of a low-cost and field portable smartphone-based compact optical system, which is suitable for applications in the visible (VIS)-near infrared (NIR) spectroscopic region. Using the universal serial bus-on the go protocol, the battery of the smartphone is used to power an external light-emitting diode, and its ambient light sensor (ALS) is used as a photo-detector. Using simple optical arrangements, a collimated light beam of a specific wavelength is allowed to pass through the sample solution, and the transmitted modulated light signal from the sample is received by the ALS of the smartphone. A custom built application “PhotoSense” has been developed, which configures the smartphone to measure intensity variation of the modulated signal into a readable form from the ALS sensor. Further using the same application, the field sensing data can be saved as a text file in the phone memory, and by using the communication facility, it can be shared anywhere in the world. The performance of the designed optical device has been evaluated for the VIS-NIR wavelength region of the incident light by measuring iron(II) and phosphate concentrations in water medium. The sensitivity of the device in measuring iron(II) and phosphate concentrations is found to be in terms of absorbance unit (AU) as 0.189 and 0.274 AU/(mg.L−1), respectively. The limit of detection of the proposed device is found to be 0.053 and 0.069 mg.L−1 for both the analytes.

A Nanozyme- and Ambient Light-Based Smartphone Platform for Simultaneous Detection of Dual Biomarkers from Exposure to Organophosphorus Pesticides.

A transparent, lateral-flow test strip coupled with a smartphone-based ambient light sensor was first proposed for detecting enzymatic inhibition and phosphorylation. The principle of the platform is based on the simultaneous measurement of the total amount of the enzyme and enzyme activity to biomonitor exposure to organophosphorus (OP) pesticides. In this study, butyrylcholinesterase (BChE) was adopted as the model enzyme and ethyl paraoxon was chosen as an analyte representing OP pesticides. The total amount of BChE was quantified by a sensitive colorimetric signal originating from a sandwich immunochromatographic assay utilizing PtPd nanoparticles as a colorimetric probe, which exhibited excellent catalytic activity for phenols. In the sandwich immunoassay, only one antibody against BChE was simultaneously utilized as the recognition antibody and the labeling antibody due to the tetrameric structure of native BChE. The BChE activity was estimated by another colorimetric signal using the Ellman assay. Both colorimetric signals on two separated test strips were detected by the smartphone-based ambient light sensor. The proposed sensor operated with an LED in a 3D-printed substrate, which emitted excitation light and transmitted it through a transparent, lateral-flow test strip. With the increase in the colorimetric signal in the test line of the test strip, the intensity of the transmitted light decreased. The smartphone-based sensor showed excellent linear responses for assaying the total amount of BChE and active BChE ranging from 0.05 to 6.4 nM and from 0.1 to 6.4 nM, respectively. A high portability and low detection limit were simultaneously realized in the common smartphone-based device. This low-cost, portable, easy-operation, and sensitive immunoassay strategy shows great potential for online detection of OP exposure and monitoring other disease biomarkers.

Single-Image-Referenced Colorimetric Water Quality Detection Using a Smartphone.

In this paper, we present a smartphone platform for colorimetric water quality detection based on the use of built-in camera for capturing a single-use reference image. A custom-developed app processes this image for training and creates a reference model to be used later in real experimental conditions to calculate the concentration of the unknown solution. This platform has been tested on four different water quality colorimetric assays with various concentration levels, and results show that the presented platform provides approximately 100% accuracy for colorimetric assays with noticeable color difference. This portable, cost-effective, and user-friendly platform is promising for application in water quality monitoring.

Mobile Hybrid Application Sebagai Solusi Dalam Pelaporan Bencana Menggunakan Framework Cordova

Mobile devices are now almost used by all walks of life. Various platforms available on smartphones like Android, iOS, Windows Mobile provide great opportunities and become a challenge for app developers. The problem is that app developers need to be able to match the needs of the available platform. The solution to this problem is the mobile hybrid application technology, which enables application developers to bridge every different smartphone platform using the cordova framework. The Cordova framework allows application developers to build mobile applications using HTML5, CSS, and javascript (JS). In this research more focused on testing the technology of mobile hybrid application to build mobile application of disaster reporting at Regional Disaster Management Agency (BPBD) South Sumatera. Test results in the form of android and windows phone applications through several tests, among others, ease in the process of building applications, publishing, and configuration. It is expected that this hybrid mobile application software can help disaster management agencies in southern Sumatra region in disaster preparedness in the community.

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.

Smartphone Based Microanalytical Device for Immunoassay of 2,4-D Determination

Onsite rapid detection of herbicide and herbicide residuals in environmental and biological specimens is important for agriculture, environment, food safety, and health care.1-2 Traditional method for herbicide detection requires expensive laboratory equipment and a long turn-round time.3-5 In this work, we developed a single-stripe microtiter plate smartphone colorimetric device for rapid and low-cost in-field test (Figure). This portable smartphone platform is capable of screening 8 samples in a microplate single-stripe. The device was validated with good sensitivity. Reliable linear relationship for detection were obtained comparing with microplate reader. This optosensing device were put into practical application for 2,4-D detection. Different concentration of 2,4-D from 80 ng/mL to 1 ng/mL were detected by the smartphone device, good linear relationship was obtained. The detection limit is down to 1 ng/mL which is lower than ELIASA reader. For real ground water sample and blood sample, it gives a good recovery rate and good linear relationship. It validated that the smartphone optical sensing platform is eligible for onsite rapid and low-cost detection of herbicide in practical samples for environmental evaluation and biological monitoring. Figure . (a) Three-dimensional structure of the smartphone based single stripe microplate reader. (b) Linear analysis of 2,4-D under the best experiment condition. References： McDuffie, H. H.; Pahwa, P.; McLaughlin, J. R.; Spinelli, J. J.; Fincham, S.; Dosman, J. A.; Robson, D.; Skinnider, L. F.; Choi, N. W. Cancer Epidemiol. Prev. Biomark. 2001, 10 (11), 1155–1163.Takashima-Uebelhoer, B. B.; Barber, L. G.; Zagarins, S. E.; Procter-Gray, E.; Gollenberg, A. L.; Moore, A. S.; Bertone-Johnson, E. R. Environ. Res. 2012, 112, 171–176.Hughes, D. L.; Ritter, D. J.; Wilson, R. D. J. Environ. Sci. Health Part B 2001, 36 (6), 755–764Jia, J.-L.; Xu, H.-H.; Zhang, G.-R.; Hu, Z.; Xu, B.-Q. Nanotechnology 2012, 23 (49), 495710.Wang, X.; Yu, J.; Wu, X.; Fu, J.; Kang, Q.; Shen, D.; Li, J.; Chen, L. Biosens. Bioelectron. 2016, 81, 438–444. Figure 1

The Development of Wireless Body Area Network for Motion Sensing Application

The information era has driven the society into the digitally-controlled lifestyle. Wireless body area networks (WBAN) as the specific scope of wireless sensor networks (WSN) is consistently growing into bigger applications. Currently, people are able to monitor their medical parameters by simply using small electronics devices attached to their body and connected to the authorities. On top of that, this time, smart phones are typically equipped with sensors such as accelerometer, gyroscope, barometric pressure, heart rate monitor, etc. It means that the sensing yet the signal processing can be performed by a single device. Moreover, Android opens lot wider opportunities for new applications as the most popular open-sourced smart phone platform. This paper is intended to show the development of motion sensing application which focused on analysing data from accelerometer and gyroscope. Beside reads the sensors, this application also has the ability to convert the sensors’ numerical value into graphs.

Sleeping with the frenemy: How restricting ‘bedroom use’ of smartphones impacts happiness and wellbeing

Smartphone technology has dramatically changed the way people interact with the physical and online world. Research shows both positive and negative impacts of smartphone and social platform use. Positive outcomes relate to social capital and engagement, while negative impacts result from compulsive usage, negative comparisons and the stress of being ‘always on’. Little evidence is available regarding wellbeing impacts of smartphone use at particular times of day. This study measures the impact of overnight smartphone use on wellbeing. Experimental group participants abstained from smartphone use in the bedroom for one week. The Subjective Happiness Scale, Quality of Life Scale, Smartphone Addiction Scale and Intensity & Time Affect Survey were issued at the beginning and end of the week. Paired sample T-Tests compared pre and post intervention participant surveys scores. It was hypothesised that subjective wellbeing would increase. In three out of four measures (SAS-SV, SHS and QOLS) the hypothesis was upheld, although impacts were relatively small. 93.6% of experimental group participants said they “might’ or “would” consider self-imposing intervention conditions moving forward, suggesting that participants experienced greater benefits not measurable through the questionnaires selected. Some qualitative analysis supports exploration of findings. Further research to explore other wellbeing impacts is encouraged.

Efficient Eye-Blinking Detection on Smartphones: A Hybrid Approach Based on Deep Learning

We propose an efficient method that can be used for eye-blinking detection or eye tracking on smartphone platforms in this paper. Eye-blinking detection or eye-tracking algorithms have various applications in mobile environments, for example, a countermeasure against spoofing in face recognition systems. In resource limited smartphone environments, one of the key issues of the eye-blinking detection problem is its computational efficiency. To tackle the problem, we take a hybrid approach combining two machine learning techniques: SVM (support vector machine) and CNN (convolutional neural network) such that the eye-blinking detection can be performed efficiently and reliably on resource-limited smartphones. Experimental results on commodity smartphones show that our approach achieves a precision of 94.4% and a processing rate of 22 frames per second.

Evaluating gender's mental model patterns for user interface design: Mobile shopping apps

Mobile applications (apps) development has experienced unprecedented growth, particularly in smartphone platforms. However, some mobile App. have been seen declining in popularity due to the unattractive user interface and bad user interaction with the users. This study adopted user's mental model pattern is crucial in human computer interaction. A guideline has been proposed for user interface design of mobile shopping App. based on female and male mental model patterns. The proposed guideline has been used in this research to redesign an existing popular mobile shopping App., Lazada and user interaction with the adapted user interface has been evaluated through simulation tool, namely AZ Screen Recorder. This research demonstrates an adapted interface design with guideline of user's mental model pattern is more efficient compared to interface design without adapted guideline.

DESIGN AND IMPLEMENTATION OF SMART HOME MODEL

Urgency of the research. The expansion of smart home systems is slower than was expected. One of the biggest obstacles to the mass expansion of smart homes is the high price of devices commonly available on the market. Home automation is not sufficiently widespread among people, not only for the high price, but also because the available systems do not meet users' perceptions of how they should work and also due to users' fear of security risks. For these reasons, when designing a new smart home system, it is a good idea to perform the initial testing on the model. Target setting. Our goal was to design a model of the original low-cost smart home system, which would allow testing, tuning, and refinement of the home automation system before it is put into use. Such a model could also be used in the learning process, while students can test the proposed smart home systems on the model. Actual scientific researches and issues analysis. When designing the model and preparing this paper, we took into ac-count both current sources – publications and papers dealing with the current state of smart home systems as well as existing smart home solutions, which are widely available on the market. Uninvestigated parts of general matters defining. The implementation of the proposed model into real-life operation was not realized during the research for this paper. The research objective. The goal of the research was to model a low-cost, reliable, smart home system. The statement of basic materials. For effective research and solution of the task of smart home system is important to create adequate model, which copies a real smart home. For our solution we used a tiny and affordable computer Raspberry Pi3, which was connected through GPIO to external sensors for light, temperature etc., operation was performed in the Python programming language and for the creation of user interface was used Cayenne platform for Android-operated smartphones. Conclusions. Our solution implemented the Raspberry Pi microcomputer, which was connected with the external hard-ware. The outputs also included the creation of a physical model of the smart home system. Designed model can meet the savings, comfort and safety requirements of every household. The stability and functionality of the system designed for the model has been verified in a long-term testing. No errors in stability have been demonstrated.

The Design of Multi-Motor Synchronous Monitoring System Based on IOT

In order to improve the quality of network monitoring, the monitoring design of the multi-motor synchronization control system based on IOT was present. In the paper IOT technology was adopted. The server part was completed on PC. And the client system was implemented on Android smart phone platform. And the motor control parameters were saved in text mode. Various parameters of multi motor synchronous system were monitored in text and graphics on Android smart phone. The parameter changes of the master motor speed and the tension were monitored on-line and shown in data curve mode. Users could browse in real time by mobile phone. Users could use manual / automatic two control methods to implement real-time control on the system. The communication parameters were stored in SQLite database. Socket network communication based on message notification was used in the system. More and more experiments showed that: The monitoring system was cost-effective, and good real-time performance. And the same time the system was quickly, low demand on the network, and easy to use.

Stochastic Error Modeling of Smartphone Inertial Sensors for Navigation in Varying Dynamic Conditions

This paper aims at investigating and analyzing the behavior of Micro-Electromechanical Systems (MEMS) inertial sensors stochastic errors in both static and varying dynamic conditions using two MEMSbased Inertial Measurement Units (IMUs) of two different smartphones. The corresponding stochastic error processes were estimated using two different methods, the Allan Variance (AV) and the Generalized Method of Wavelets Moments (GMWM). The developed model parameters related to laboratory dynamic environment are compared to those obtained under static conditions. A contamination test was applied to all data sets to distinguish between clean and corrupted ones using a Confidence Interval (CI) investigation approach. A detailed analysis is presented to define the link between the error model parameters and the augmented dynamics of the tested smartphone platform. The paper proposes a new dynamically dependent integrated navigation algorithm which is capable of switching between different stochastic error parameters values according to the platform dynamics to eliminate dynamics-dependent effects. Finally, the performance of different stochastic models based on AV and GMWM were analyzed using simulated Inertial Navigation System (INS)/Global Positioning System (GPS) data with induced GPS signal outages through the new proposed dynamically dependent algorithm. The results showed that the obtained position accuracy is improved when using dynamic-dependent stochastic error models, through the adaptive integrated algorithm, instead of the commonly used static one, through the non-adaptive integrated one. The results also show that the stochastic error models from GMWM-based model structure offer better performance than those estimated from the AV-based model.

The Emerging Wireless Body Area Network on Android Smartphones: A Review

Our society now has driven us into an era where almost everything can be digitally monitored and controlled including the human body. The growth of wireless body area network (WBAN), as a specific scope of sensor networks which mounted or attached to human body also developing rapidly. It allows people to monitor their health and several daily activities. This study is intended to review the trend of WBAN especially on Android, one of the most popular smartphone platforms. A systematic literature review is concerned to the following parameters: the purpose of the device and/or application, the type of sensors, the type of Android device, and its connectivity. Most of the studies were more concern to healthcare or medical monitoring systems: blood pressure, electro cardiograph, tremor detection, etc. On the other hand, the rest of them aimed for activity tracker, environment sensing, and epidemic control. After all, those studies shown that not only Android can be a powerful platform to process data from various sensors but also smartphones can be a good alternative to develop WBANs for medical and other daily applications.

AR-KIO: Augmented Reality-based Application as Instructional Media on Input and Output Device Component.

The rapid technology development can be utilized in various fields, especially in education. For example, is augmented reality-based learning media. The learning media can be applied to all the subject matter, including the subject of input and output component devices. Based on the observations that already made, there are some problems such as there is no interactive learning media and limited props in the laboratory. Though the subject of input and output component devices require three-dimensional visualization, especially input output components that are difficult to find in the school environment. The purpose of this study is to determine the feasibility of instructional media applications that have been developed. The research method used is research development method. The tests conducted by media experts, content experts, users and smartphone devices with different specifications. Media expert testing using instruments that refer to aspects of the functionality of ISO 9126 with the percentage acquisition of 100%. Content expert testing using the instrument that refers aspects of learning design with the acquisition percentage of 88%. Meanwhile, user testing uses an instrument that refers to the usability aspect of ISO 9126 with a percentage gain of 83.4%. In addition, there are testing the software with android smartphone platform that has different specifications. The advantages of this application can run on a smartphone with minimum 512 MB RAM specs, Android OS Jelly Bean 4.3 and qHD screen resolution.

Paradigm shift: Efficient and cost effective real-time nutritional assessment technique

For several decades, nutritional anthropometry has been used in the assessment of nutritional status and growth monitoring for individuals and at population level. Techniques, equipment and standardization procedures endorsed by The United Nations Children’s Fund (UNICEF) and The World Health Organization (WHO) for measurements of body size are extensively used, have evolved and advanced in precision. However, new challenges are emerging with each new equipment and technique for data collection, including; difficulty in calibrating and durability of equipment, frequent observational errors, delays in generating nutritional data, relatively high cost of data collection in the field, and scarcity of nutritional experts to manage assessments and analyse data. Moreover, some health facilities collect selective nutritional data (weight and age) required for drug prescriptions only and often lack a repository for the raw data, making it difficult to assess nutritional trends for individual patients and compare nutritional status of populations over time. In the last one decade, there has been a shift towards the use of high technology in data collection for social studies, which is faster, more accurate and reliable when compared to conventional methods. Advancement in technology has seen the development of high precision digital clinical scales for measuring weight and height/length for individuals and populations with readily installed software for calculating nutritional indices and interfaces, such as, Bluetooth, USB or Wi-Fi, for transmitting data. In the proposed real-time nutritional assessment system, we combine GPS-Coordinates, anthropometric data from high precision digital clinical scales; fingerprint coded data, with indicators derived from food security, water, sanitation, maternal and child health data in the smartphone platform. Through the cellular network, the combined data is transmitted to a specialised designed web-based visualisation interface where it is analysed and presented on a dashboard in a form of interactive dynamic graphs and charts. After deriving the nutritional indices, the system superimposes colour coded anthropometric results for study subjects to display their immediate nutritional status. Subsequently, these assessment results are simultaneously transmitted through live-web to the desktops of assessment supervisors, programmers, and developing partners who actively interact as results trickle in and can make intervention decisions in real time. This efficient and cost-effective nutrition assessment system is proposed because it generates nutritional data that provides the most current nutritional status of an individual and target population; monitors trends of nutritional status; identifies priority individuals and areas for immediate nutritional interventions; and evaluates the effectiveness of nutrition and health intervention programmes. Keywords: Nutrition assessments, Anthropometric, Mobile data collection, Real-time, Data Visualization

Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform.

In this study, a portable electronic nose (E-nose) was self-developed to identify rice wines with different marked ages—all the operations of the E-nose were controlled by a special Smartphone Application. The sensor array of the E-nose was comprised of 12 MOS sensors and the obtained response values were transmitted to the Smartphone thorough a wireless communication module. Then, Aliyun worked as a cloud storage platform for the storage of responses and identification models. The measurement of the E-nose was composed of the taste information obtained phase (TIOP) and the aftertaste information obtained phase (AIOP). The area feature data obtained from the TIOP and the feature data obtained from the TIOP-AIOP were applied to identify rice wines by using pattern recognition methods. Principal component analysis (PCA), locally linear embedding (LLE) and linear discriminant analysis (LDA) were applied for the classification of those wine samples. LDA based on the area feature data obtained from the TIOP-AIOP proved a powerful tool and showed the best classification results. Partial least-squares regression (PLSR) and support vector machine (SVM) were applied for the predictions of marked ages and SVM (R2 = 0.9942) worked much better than PLSR.

Recent Progress in Optical Biosensors Based on Smartphone Platforms.

With a rapid improvement of smartphone hardware and software, especially complementary metal oxide semiconductor (CMOS) cameras, many optical biosensors based on smartphone platforms have been presented, which have pushed the development of the point-of-care testing (POCT). Imaging-based and spectrometry-based detection techniques have been widely explored via different approaches. Combined with the smartphone, imaging-based and spectrometry-based methods are currently used to investigate a wide range of molecular properties in chemical and biological science for biosensing and diagnostics. Imaging techniques based on smartphone-based microscopes are utilized to capture microscale analysts, while spectrometry-based techniques are used to probe reactions or changes of molecules. Here, we critically review the most recent progress in imaging-based and spectrometry-based smartphone-integrated platforms that have been developed for chemical experiments and biological diagnosis. We focus on the analytical performance and the complexity for implementation of the platforms.