Narrow Results

Wearable devices are increasingly gaining more attentions in healthcare and fitness industry due to their potentials to measure valuable physiological signals on the move. There are many researchers who have proposed different types of designs that embed biosensors into miniature wearable devices. In this paper, we present a wearable companion that monitors the cardiac activities of a wearer with smartphone. The device makes use of a single, integrated biosensor that is designed with a unique analog front-end circuitry and a dedicated signal processing pipeline. In order to meet the requirements of possible but different user scenarios, three types of product forms are presented. The experimental results show that electrocardiogram (ECG) signals collected are valid and consistent through the systems. Future topics include adding extra algorithms to remove motion artifacts in order to achieve better signal quality in various settings and include wireless communication through 4G.

Objective: This research aims to survey the efforts of researchers in response to the new and disruptive technology of skin cancer apps, map the research landscape from the literature onto coherent taxonomy, and determine the basic characteristics of this emerging field. In addition, this research looks at the motivation behind using Smartphone apps in the diagnosis of skin cancer and in health care and the open challenges that impede the utility of this technology. This study offers valuable recommendations to improve the acceptance and use of medical apps in the literature. Methods: We conducted a comprehensive survey using the keywords “skin cancer,” “apps,” and “Smartphone” or “m-Health” in different variations to find all the relevant articles in three major databases: Web of Science, Science Direct, and IEEE Xplore. These databases broadly cover medical and technical literature. Results: We found 110 articles after a comprehensive survey of the literature. Out of the 110 articles, 46 present actual attempts to develop and design medical apps or share certain experiences of doing so. Twenty-eight articles consist of analytical studies on the incidence of skin cancer, the classification of malignant cancer or benign cancer, and the methods of prevention and diagnosis. Twenty-two articles comprise studies that range from the evaluative or comparative study of apps to the exploration of the desired features for skin cancer detection. Fourteen articles consist of reviews and surveys that refer to actual apps or the literature to describe medical apps for a specific specialty, disease, or skin cancer and provide a general overview of the technology. New research direction: With the exception of the 110 papers reviewed earlier in results section, the new directions of this research were described. In state-of-the-art, no particular study presenting watermarking and stenography approaches for any type of skin cancer images based on Smartphone apps is available. Discussion: Researchers have attempted to develop and improve skin cancer apps in several ways since 2011. However, several areas or aspects require further attention. All the articles, regardless of their research focus, attempt to address the challenges that impede the full utility of skin cancer apps and offer recommendations to mitigate their drawbacks. Conclusions: Research on skin cancer apps is active and efficient. This study contributes to this area of research by providing a detailed review of the available options and problems to allow other researchers and participants to further develop skin cancer apps, and the new directions of this research were described.

When a Phone is more than a SmartPhone

ViiV Healthcare and Desano Pharmaceuticals’ Manufacturing Agreement Will Allow Competitive Supply of Dolutegravir in China and Several Developing Countries

New Implant Device for the Heart: World’s First ProMRI Quadripolar CRT-D Now Available in Japan

The patellar tendon reflex response provides fundamental means of assessing a subject’s neurological health. Dysfunction regarding the characteristics of the reflex response may warrant the escalation to more advanced diagnostic techniques. Current strategies involve the manual elicitation of the patellar tendon reflex by a highly skilled clinician with subsequent interpretation according to an ordinal scale. The reliability of the ordinal scale approach is a topic of contention. Highly skilled clinicians have been in disagreement regarding even the observation of asymmetric reflex pairs. An alternative strategy incorporated the ubiquitous smartphone with a software application to function as a wireless gyroscope platform for quantifying the reflex response. Each gyroscope signal recording of the reflex response can be conveyed wirelessly through Internet connectivity as an email attachment. The reflex response is evoked through a potential energy impact pendulum that enables prescribed targeting and potential energy level. The smartphone functioning as a wireless gyroscope platform reveals an observationally representative gyroscope signal of the reflex response. Three notably distinguishable attributes of the reflex response are incorporated into a feature set for machine learning: maximum angular rate of rotation, minimum angular rate of rotation, and time disparity between maximum and minimum angular rate of rotation. Four machine learning platforms such as the J48 decision tree, K-nearest neighbors, logistic regression, and support vector machine, were applied to the patellar tendon reflex response feature set incorporating a hemiplegic patellar tendon reflex pair. The J48 decision tree attained 98% classification accuracy, and the K-nearest neighbors, logistic regression, and support vector machine achieved perfect classification accuracy for distinguishing between a hemiplegic affected leg and unaffected leg patellar tendon reflex pair. The research findings reveal the potential of machine learning for enabling advanced diagnostic acuity respective of the gyroscope signal of the patellar tendon reflex response.

The utility of the smartphone, such as the iPhone, constitutes considerable potential for the advancement of the biomedical and healthcare industry. A notable feature of the iPhone is the capacity to combine the internal accelerometer sensor with a software application to enable the functionality of a wireless accelerometer platform. Preliminary research has demonstrated the iPhone’s ability to quantify features of healthy gait. The research applies a single iPhone mounted proximal to the lateral malleolus of the affected leg and subsequently the unaffected leg to ascertain quantified disparity of hemiplegic gait from an engineering proof of concept perspective. In order to maintain a consistent gait velocity, a constant velocity treadmill is incorporated into the research endeavor. Post-processing of the gait acceleration waveform is greatly facilitated through the use of a software automation program using Matlab that emphasizes on the rhythmicity of gait. Two gait parameters were obtained: stance-to-stance temporal disparity and stance-to-stance time-averaged acceleration, and demonstrated considerable accuracy, consistency, and reliability. As noted per the constant treadmill velocity, stance-to-stance temporal disparity for the affected and unaffected legs was established as not statistically significant. A statistical significance was determined for the stance-to-stance time-averaged acceleration regarding the affected and unaffected legs. The iPhone application represents a wireless accelerometer platform capable of identifying statistically significant and quantified disparity of hemiplegic gait features through automated post-processing in a functionally autonomous environment.

This paper aims to develop an algorithm to detect heart diseases through ordinary smartphones without additional equipment for cost accessibility. Among various vital signs emitted by organs, sounds can be easily observed and carry ample information. However, these sounds are small and noisy. Detecting anomalies involves great challenges in signal processing. This study presents a novel method that overcomes noises to estimate cardiovascular health. We use time-scale techniques in time series analysis to extract disease traits and suppress excessive ambient noises. Using datasets from PhysioNet, our model achieved a nearly 100% accuracy in heart disease diagnosis. Our approach also performs well under excessive noises for diseases producing heart murmurs. With heavy noise contaminated signals, training accuracy still closed to 100%, and the testing accuracy still remained around 84%.

Since smartphones have become the most prevalent communication tool in the world, a wide variety of low-end to high-end smartphone products are currently available on the market. Choosing a suitable product becomes a challenge due to the problem of feature fatigue. This study developed a smartphone selection procedure for prospective users by incorporating ELECTRE-III method with Kano two-dimensional quality model. An empirical example of 15 smartphones from three different categories, namely, flagship, screen size and price, demonstrated that the credibility matrix of the revised ELECTRE-III had fewer extreme values (0 and 1) than its original counterpart. It was able to clearly distinguish the relative satisfaction of each option in the respective group, particularly for the tied products which could not be discerned by the original ELECTRE-III.

The long use of a system causes its degradation. Hence, the maintenance activity is required in order to keep and improve the efficiency in the system. With the rapid development in networking technology, a need appears to change the manufacturing strategies. These new technologies improve the maintenance process, and establish remote maintenance (tele-maintenance, e-maintenance and m-maintenance). These kinds of maintenance try to provide personnel maintenance with the right information at the suitable time, which makes information available, anywhere and anytime. Our proposition is the use of mobile agent technology to reduce the maintenance costs and solve the problem of the unavailability of an expert in all phases of condition-based maintenance (CBM) strategy. The mobile agent technology overcomes a lot of problems and there is not much work that has used this technology. We have also used the web services (WS) to insure interoperability between machines and to support interaction over the network. Our approach gives great support to the maintenance engineer as it facilitates the access to decision-making support, work order, etc. which are available in the device like smartphone. This paper presents the development of a mobile maintenance support system based on mobile agent technology. The proposed system, the web and agent technology as well as remote communication were tested successfully.

This paper examines the adoption of Smartphones in Saudi Arabia. A theoretical research model is developed based on the unified theory of acceptance and use of technology. A web-based survey has been used to gather data from randomly selected Smartphone users in Saudi Arabia. For data analysis, SEM approach was followed, SPSS and AMOS were utilized for analyzing data. The results indicate that performance expectancy, effort expectancy, brand influence, perceived enjoyment, and design constructs have a positive and significant relationship with users’ behavioral intention to adopt and use Smartphones in Saudi Arabia.

The ubiquitous application of smartphones and their advanced development have created an opportunity for using them as coding platforms. In this study, we compared between the use of personal computers (PCs) and smartphones to investigate the factors affecting the use of smartphones in programing. The behavioral intentions of smartphone end-users are inspired by the ease of use perception, enjoyment perception, programing anxiety, perception of external control, and smartphone design aesthetics. Although the $R^2$ value of the smartphone model was lower than that of the PC model, the end-users’ adoption decisions could have shifted toward accepting the use of smartphones for programing had their decisions been free of enforcement. In this study, design aesthetics and programing anxiety were introduced to Technology Acceptance Model 3 in an Arabic environment. Additionally, the model was creatively applied for guiding practitioners in two situations. First, when organizations are in the quest for emerging technology to replace the legacy technology, they might apply the presented side-by-side comparison of the use of PCs with that of smartphones in programing. Second, at a time when decision makers analyze what might hinder the adoption of a recently introduced technology, the model can be a successful hand tool guiding the top management in identifying technology acceptance interventions, an approach this research revealed. Furthermore, in this paper, the research implications and recommendations are presented for technology practitioners and designers.

Usability is an emerging subject for smartphone design and service, which results in the overall quality and achievement of a product and allows users to perform various tasks. In this context, this study aims to propose an integrated smartphone usability framework for higher service level and user experience with a causal analytic approach. Involving tested relationships with theoretical concerns a conceptual usability assessment model is proposed including design, customer focus, quality, innovation, usability, and user perception variables. The provided model is developed using the Bayesian neural networks based universal structure modeling (USM) method. The reliability and validity are empirically tested for the questionnaire data collected from 1068 smartphone users. The results and findings showed that design, customer focus, quality, and innovation explain usability, and user perception as an ultimate variable is interpreted by usability. Also, strategic, and valuable information for smartphone designers and marketing people to understand user perceptions for smartphone usability is provided.

The number of smartphone users is growing dramatically. Using the smartphone frequently forces the users to adopt an awkward posture leading to an increased risk of musculoskeletal disorders and pain. The objective of this study is to conduct a systematic review of studies that assess the effect of smartphone use on musculoskeletal disorders and pain. A systematic literature search of AMED, CINAHL, PubMed, Proquest, ScienceDirect using specific keywords relating to smartphone, musculoskeletal disorders and pain was conducted. Reference lists of related papers were searched for additional studies. Methodological quality was assessed by two independent reviewers using the modified Downs and Black checklist. From 639 reports identified from electronic databases, 11 were eligible to include in the review. One paper was found from the list of references and added to the review. The quality scores were rated as moderate. The results show that muscle activity of upper trapezius, erector spinae and the neck extensor muscles are increased as well as head flexion angle, head tilt angle and forward head shifting which increased during the smartphone use. Also, smartphone use in a sitting position seems to cause more shift in head–neck angle than in a standing position. Smartphone usage may contribute to musculoskeletal disorders. The findings of the included papers should be interpreted carefully in light of the issues highlighted by the moderate-quality assessment scores.

A new colorimetric method for the detection of chemotherapeutic drug 6-mercaptopurine (6-MP) is developed based on controlling localized surface plasmon resonance (LSPR) of triangular silver nanoplates (AgNPs). The triangular AgNPs can be etched by trace amount of Cl⁻ and transformed to a disc-like shape, accompanied by a blueshift of the corresponding LSPR absorption band. With the protective effect of 6-MP, the AgNPs are hardly or partly to be etched by Cl⁻, resulting in a reversed shift of LSPR. Based on a linear relationship between LSPR wavelength change and the concentration of 6-MP, a fast, visual and selective method for 6-MP assay is established. This method has been successfully applied to the detection of 6-MP in tablets.

This work demonstrates a smartphone-based automated fluorescence analysis system (SAFAS) for point-of-care testing (POCT) of Hg(II). This system consists of three modules. The smartphone module is used to provide an excitation light source, and to collect and analyze fluorescent images. The dark box module is applied to integrate the desired optical elements and offers a dark environment. The cost of the integrated dark box mainly includes the upper cover, box body, lower bottom, fixture and some optical elements which is about $109. The chip module is used for fluorescence sensing, which is composed of an upper plate, bottom plate and cloth-based chip. Due to the integration of multiple smartphone functions, the SAFAS eliminates the need for additional power sources, light sources and analysis systems. The dark box and upper and bottom plates are made by 3D printer. The cloth-based chip (about $0.005 for each chip) is fabricated using the wax screen-printing technique, with no need for expensive and complex fabrication equipments. To our knowledge, the cloth-based microfluidic fluorescence detection method combined with smartphone functions is first reported. By using optimal conditions, the designed system can realize the quantitative detection of Hg(II), which has a linear range of 0.001–100$\mu$gmL${}^{-1}$ and a detection limit of 0.5ngmL${}^{-1}$. Additionally, the SAFAS has been successfully applied for detecting Hg(II) in actual water samples, with recoveries of 100.1%–111%, RSDs of 3.88%–9.74%, and fast detection time of about 1 min. Obviously, the proposed SAFAS has the advantages of high sensitivity, wide dynamic range, acceptable reproducibility, good stability and low cost. Therefore, it is believed that the presented SAFAS has great potential to perform the POCT of Hg(II) in different water samples.

Background: The rehabilitation after wrist surgery is extremely important. An instructed therapy in hospital is widely practiced. However, a dependent aging society and rush life style in younger generation have precluded patients to access to the frequent formal therapy. With the advancement in telecommunication technology, we have invented an application for smartphone for home-based wrist motion rehabilitation.

Methods: Twenty participants were included in four-week wrist motion rehabilitation programme after wrist surgery. Participants were instructed to use the application by physical therapist and informed details of home-based wrist rehabilitation. The feasibility of application was evaluated by satisfaction level in various aspects and the adherence to the therapy was monitored by function provided in the application. The degrees of motion were compared at the end of prescribed programme.

Results: Patient satisfaction was consistently high in every aspects. Also, the adherence to the therapy was high (90.42%). Ranges of motion significantly gained in every plane of wrist motion ($p<0.05$).

Conclusions: This novel smartphone application seems to be a promising and convenient alternative for patients who need to gain wrist motion without formal rehabilitation in the hospital. Adherence to the therapy is also easily traced with this application.

Background: The purpose of this study was to compare the diagnostic accuracy of a smartphone flashlight to a conventional penlight with regards to transillumination of simulated soft tissue masses of the hand and wrist.

Methods: Eight participants performed transillumination assessments in a fresh frozen cadaver upper extremity model. Spheres measuring 9.5 mm were used to simulate fluid-filled or solid soft tissue masses. Two spheres were placed on the volar aspect and two on the dorsal aspect of the wrist. These were then evaluated with either a smartphone flashlight or penlight. Participants noted whether each sphere did or did not transilluminate. Each participant performed two evaluations at an interval of 3 weeks.

Results: The overall sensitivity, specificity and accuracy of the smartphone were 100%, 44% and 72%, respectively. The overall sensitivity, specificity and accuracy of the penlight were 100%, 75% and 88%, respectively. The difference in accuracy between the smartphone group and penlight group was statistically significant (p = 0.029). The kappa value, indicating intra-observer agreement, for the smartphone group and penlight group was 0.76 and 0.76, respectively.

Conclusion: In conclusion, transillumination with a penlight is a viable adjunct to the examination of soft tissue masses of the hand and wrist. The use of a smartphone flashlight, while convenient, is less accurate than a penlight and can lead the examiners to misinterpret the composition of soft tissue masses.

Level of Evidence: Level IV (Diagnostic)

Photoplethysmography (PPG) is a technique based on photonics related to the volumetric changes in blood vessels during circulation. PPG has been widely applied in monitoring respiration, hypervolemia and other circulatory diseases. The smartphone becomes more popular nowadays. As the smartphone is usually equipped with light-emitting diode (LED) and camera, the imaging function in smartphone is proposed for PPG signal detection. An algorithm termed as the autoregressive (AR) decomposition is presented to extract the respiratory rate and pulse rate of the subject buried in the PPG measurement. The extracted information is verified by those derived from commercial equipments and the derived results agree well. The proposed algorithm is not complex and can be implemented in a smartphone as an application program. For its convenience in usage, the proposed strategy may be potential in telemedicine, preventive medicine and home care usage.

Photoplethysmography (PPG) is an optical technique which measures blood volume changes in the arterial blood using red and IR LEDs of wavelengths 660nm and 940nm, respectively. This paper proposes a methodology to measure the pulse rate from the video signal obtained using an LETV-LE MAX 2 mobile phone’s camera and also to evaluate hypertension. The Android smartphone records the intensity of light reflected from the index finger. The recorded video is separated into red, green and blue frames. Since the red video frames returned useful plethysmographic information, they are filtered using Butterworth band-pass filter and power spectral density analysis was performed on them. The immediate peak gives the pulse rate of the respective subject. Fifteen features of pulse waveform are extracted and by performing the feature selection process, seven features are selected and they undergo classification process using a neural network. The feature selection process is performed by using the eigenvalues of the principal component analysis method. The eigenvalues obtained from this method show the degree of variation present in the data. The eigenvalue that is near or close to zero gives the principal components. The features that are selected by the feature selection process of principal component analysis method are peak interval, settling time, rise time, normalized PPG, peak-to-peak amplitude, first derivative and second derivative. While performing the classification process using a neural network, the accuracy of prediction was calculated for both the normal and hypertensive subjects.

Advancement of wireless technologies and high penetration of Smartphone led to the emergence of m-Commerce. In order to develop a useful m-Commerce system, user need must be considered. In addition, m-Commerce adoption must be assessed among users before the final development of the system. In order to use m-Commerce a set of skills and knowledge is required among Smartphone users. For this reason, a Five Dimensions m-Commerce Literacy (5DmCL) Model is developed in this study first. Then a survey is conducted to discover how m-Commerce Literacy can affect Smartphone users’ attitude towards using m-Commerce. e-Torch, a mobile commerce location-based promotion system was used as a case study for conducting the survey. The survey was conducted among 124 Smartphone users in Penang, Malaysia using questionnaire. To analyse the collected data, a theoretical framework called the Model of m-Commerce Literacy on Attitude (mCLoA) is proposed in order to understand the Smartphone users’ attitude towards using e-Torch for enhancing the quality of m-Commerce services. Partial Least Squares (PLS) is utilized to analyse the proposed measurement model. For this reason, validity and the structural equation modelling (SEM) technique is utilized in order to assess the proposed model. The results indicated that respondents with more m-Commerce Literacy show positive attitude towards using e-Torch and they trust on this kind of m-Commerce system. Moreover, they believe that e-Torch is useful and easy to use for advertisement services and it can improve the quality of m-Commerce.

Nowadays, smartphones are available at cheaper rates and are widely used across the world. Smartphones are not only used for making phone calls and sending messages but also for storing personal data, Internet browsing, online banking, etc. Hence, smartphones have become a potential target for cyberattack. Malware attacks in the smartphones have been growing at an alarming rate and the cybercriminals are targeting smartphones to spread malware for stealing money and confidential data stored in the phones. Therefore, it is essential to ensure security in mobile platforms. In this chapter, we discuss the current malware detection mechanisms in smartphones and their drawbacks.