Mobile Healthcare Applications Research Articles

Privacy, security and resilience in mobile healthcare applications

ABSTRACT With the advent of mobile applications in health service systems, concerns such as security, privacy, usability, and resilience have been raised. We developed a system view of the concepts of security, privacy, resilience along with their relationship, and proposed a set of principles for designing a mobile application linking the resilience and security in privacy protection. Such study was not found in literature before. This system's view of privacy, security, and resilience has laid a foundation to develop a more effective service system. A case study is presented to illustrate how the proposed principles work in a mobile healthcare application.

Long-term effectiveness of an mHealth-tailored physical activity intervention in youth with congenital heart disease: A randomized controlled trial.

To evaluate the long-term effectiveness of the Care & Organize Our Lifestyle (COOL) programme, a self-regulation theory-based mHealth programme, on improving disease knowledge and physical activity in youth with congenital heart disease (CHD). A three-arm parallel-group randomized controlled trial. A total 143 participants with simple and moderate CHD aged 15-24years were recruited from June 2016 to February 2018. The 12-month programme compared two active intervention groups to a standard-care control group (n=47). Participants in one active intervention group (n=49) were provided with COOL Passport, a mobile healthcare application. Those in the other group (n=47) were provided with access to the Health Promotion Cloud system and use of game-based interactive platforms along with COOL Passport. Outcomes were the Leuven Knowledge Questionnaire for Congenital Heart Disease and the International Physical Activity Questionnaire-Taiwan Show-Card Version. After 12months, 103 participants remained; the overall attrition rate was 28%. No significant differences were observed between the groups in any domain of disease knowledge after 6months or 1year. Neither active group exhibited significantly greater physical activity intensity than the standard-care control group in any month during the 1year. The mHealth-tailored intervention of the COOL programme did not improve disease knowledge or physical activity in young adults with CHD. The application of the COOL Passport and Health Promotion Cloud system and use of game-based interactive platforms must be modified and verified in future studies and may have clinical potential. The registry of clinical trials was ClinicalTrials.gov: NCT04264650.

HOME CARE MOBILE APPLICATIONS: SURVEY

Recently, with Coronavirus, mobile applications are becoming more important especially these days because all people stay at home and they couldn't visit the hospital, and the clinic outside becomes a danger. So the use of mobile phone technologies is becoming more and more beneficial for patient care. Mobile technology has the potential to affect health care. The increasing number of people suffering from chronic diseases is putting pressure on the healthcare sector. Population aging is now a major health care concern in many countries of the world. Elderly patients need more healthcare efforts that imply higher healthcare costs, because of that a set of applications have been developed that help care for patients from their homes. In this paper, many mobile healthcare applications are discussedin order to be identified and used to build a new system that helps care for patients from home.

An observational study of a cross platform risk assessment mobile application in a forensic inpatient setting

Consumer-focused healthcare mobile applications have seen widespread adoption in recent years. Enterprise mobile applications in hospital settings have been slower to gain traction. In this study we examine the Dynamic Appraisal of Situational Aggression: Inpatient version (DASA), a short-term risk assessment tool which is well validated and widely used in the prediction of violent incidents, within an inpatient forensic setting. The application was piloted over a period of three months, collecting 847 total DASA scores on 21 different patients. Time stamping allowed for accurate correlation between risk assessment scoring and the violent risk incidents. The internal validity of the app was measured using Cronbach's alpha and was calculated at 0.798 indicating good internal validity. Using violent incidents as the dependent factor and the total DASA score as the independent factor, predictive validity of the app was calculated at 0.85, p = 0.007. The use of this application in a forensic setting was successful with good internal and predictive validity. A major benefit of this form of data collection was the electronic time stamping so that the correlation between risk estimation and events could be more closely correlated. Deployment of such an application in a general hospital setting would bring its own challenges but would be useful in other types of risk assessment and screening tools.

Evaluation of the Mawid mobile healthcare application in delivering services during the COVID-19 pandemic in Saudi Arabia.

PurposeThe purpose of this study is to evaluate MAWID mobile application developed by the Ministry of Health, Saudi Arabia, which is used for primary care hospitals appointments management and for tracking and tracing COVID-19.Participants and MethodsAn online questionnaire-based survey was used for collecting data related to three major factors including Ease of Use, Satisfaction, and Benefits of MAWID application among its users. Out of total 2542 participants, 345 participants completed only a part of the survey, and 204 participants did not use the application. After removing, 549 invalid responses, a final sample of 1993 was included for the data analysis.Results82.1% of the participants referred MAWID as easy to use application, 79.8% were highly satisfied with the application, and majority of the participants reflected potential benefits of using the application. T-test results have revealed that significant differences existed between males and females, and young and older participants in relation to the Ease of Use and Satisfaction levels associated with MAWID application.ConclusionMobile applications can be very effective in delivering the healthcare services during pandemics. However, there is a need for regular evaluation and assessment to trach the change in users′ needs and update the app according to the changing requirements.

Short-term and Long-term Efficacy of Oropharyngolaryngeal Strengthening Training on Voice Using a Mobile Healthcare Application in Elderly Women

ë°°ê²½ 및 ëª©ì  ë ¸í™”ë¡œ 인한 음성 기능의 ì €í•˜ëŠ” 의사소통과 일상생활을 방해하며 삶의 질에 ë¶€ì •ì  영향을 미치므로 ë ¸ì¸ì„± ìŒì„±ìž¥ì• ì— 대한 중재가 필요하다. 치료 효과를 최대화하기 위해서는 치료 순응이 í•„ìˆ˜ì ì´ë©° 모바일 헬스케어는 순응도를 높이는 데 íš¨ê³¼ì ì¼ 수 있다. 이 연구에서는 ì• í”Œë¦¬ì¼€ì´ì ˜ì„ 이용한 구강 및 인후두 ê·¼ë ¥ 강화 í›ˆë ¨ì´ ë ¸ë „ì¸µì˜ 음성에 미치는 효과를 í™•ì¸í•˜ê³ ìž 한다. 방법 11ëª ì˜ ë ¸ì¸ì„ 대상으로 8주 동안 ê°€ì •ì—ì„œ ì• í”Œë¦¬ì¼€ì´ì ˜ì„ 이용하여 ASSET (A Successful Swallowing with Effortful Training)을 실시하게 하였다. 이 중 í”„ë¡œí† ì½œì„ ì í•©í•˜ê²Œ 수행한 7ëª (여성 7ëª , í‰ê· ì—°ë ¹ 74.6±5.7세)을 대상으로 치료 효과를 확인하였으며 효과 성 ì¸¡ì •ì€ 음성 기능 평가와 음성 ê´€ë ¨ 설문평가를 통해 이루어졌다. ê²°ê³¼ 음성 기능 평가 ê²°ê³¼, í›ˆë ¨ 직후 MPT, F0, CPPs가 ìœ ì˜í•˜ê²Œ ì¦ê°€í•˜ì˜€ê³ Jitter, Shimmer, NHR이 ìœ ì˜í•˜ê²Œ 감소하였으며 NHR의 ê°œì„ ì´ í›ˆë ¨ ì¢ ë£Œ 12주 후에도 ìœ ì§€ë˜ê³ ìžˆì—ˆë‹¤. 음성 ê´€ë ¨ 설문평가 ê²°ê³¼, í›ˆë ¨ 직후 VHI-10 ì´ì ì´ ìœ ì˜í•˜ê²Œ 감소하였다. ë ¼ì˜ 및 ê²°ë¡ ì• í”Œë¦¬ì¼€ì´ì ˜ì„ 이용한 구강 및 인후두 ê·¼ë ¥ 강화 í›ˆë ¨ 후 ë ¸ë „ 여성의 음성 기능 및 음성 ê´€ë ¨ 삶의 질이 ê°œì„ ë˜ì—ˆìœ¼ë©° 음성 기능의 ê°œì„ ì´ ìž¥ê¸°ì ìœ¼ë¡œ ìœ ì§€ë˜ì—ˆë‹¤. 본 í›ˆë ¨ í”„ë¡œí† ì½œì€ ë ¸ì¸ì„± 음성 ìž¥ì• ì˜ íš¨ê³¼ì ì¸ 음성치료로 ì‚¬ìš©ë ìˆ˜ 있을 것이다. Keywords: ë ¸í™”, ë ¸ì¸ì„± ìŒì„±ìž¥ì• , 구강 및 인후두 ê·¼ë ¥ 강화 í›ˆë ¨, 모바일 헬스케어

Validation of a satellite-based solar UV-A radiation dosimeter for mobile healthcare applications

Solar UV-A radiation causes photocarcinogenesis and skin photoageing, but it could also benefit cardiovascular health and protection from autoimmunity.In this study, a method for the near real-time monitoring of UV-A solar radiation dose based on Earth Observation satellites imagery is proposed. The calculated satellite-derived radiant dose has been compared to ground measurements provided by Public Health England solar monitoring network at eight locations in the UK and Republic of Ireland in April–October 2015. The statistical analysis showed a good correlation between satellite-derived exposure doses and direct ground measurements under all weather conditions, significantly improved for clear skies. The proposed method may be considered for the integration into digital mobile apps for healthcare, assisting users to balance risks and benefits of sun exposure in an accessible way.

Texture maps and chaotic maps framework for secure medical image transmission

Telemedicine has evolved significantly for detection and diagnosis of diseases remotely, which means more frequent transmission of medical images over the network. The security of any medical image can be characterized as its integrity, confidentiality and authentication. It is these security vulnerabilities that limit the development of mobile healthcare applications, which intend to improve the efficiency of medical image communication. To address the vulnerabilities associated with medical images, we propose a texture edge map and multilevel chaotic map driven encryption framework for medical images. This technique utilizes texture maps generated by utilizing a bank of gabor filters along with multiple chaotic maps viz.: Sine, Cubic and Logistic maps for enhancing the key space, robustness and security of medical images over an insecure channel. The security, speed and reliability of the proposed technique for medical images are illustrated via experiments for key sensitivity, statistical and performance analysis. The proposed technique offers a large key space, pixel diffusion at an acceptable speed. Security analysis shows a high sensitive dependence of the encryption and decryption techniques to any subtle change in the secret key, the plain medical image and the encrypted image. Also, the proposed technique has a large enough key space to see off brute force attacks. Therefore, the proposed technique is a potential candidate for addressing security vulnerabilities of medical images over the communication networks.

Determinants of behavioral intentions to use mobile healthcare applications in Jordan

The purpose of this study is to examine the determinants of behavioral intentions to use of mobile health (m-Health) applications in Jordan through examining the mediating role of perceived trust and its influence on the behavioral intention to use such applications. A conceptual model was developed based on the extant literature. A questionnaire survey was administered to a convenient sample of 318. Data was analyzed using smart PLS 3. The findings suggest that patients’ behavioral intentions to use m-Health applications are positively affected by perceived ease of use, perceived security, social influence and perceived trust of these applications. Perceived Trust was also found to mediate the relationship between these factors and the behavioral intention. Discussion, conclusions, implications, research limitations and areas for future research are also provided.

The Effect of UI Usability of Mobile Healthcare Applications on Technostress and Continuous Use Intention: Focusing on Elderly Users

The Effect of UI Usability of Mobile Healthcare Applications on Technostress and Continuous Use Intention: Focusing on Elderly Users

Design and Development of Mobile Healthcare Application for “Ayurvedic” based Clinical Documents

In the modern world, people need immediate remedies for their health problems. Without considering the future effects of the heavy dose medicines, people intake those medicines to get immediate relief. As a result, they forget the natural and side effects free home remedies. And there is no awareness among the current generation youngsters and kids. To overcome this problem, we are developing a mobile application in dart language using flutter framework [2]. It uses KMP Algorithm [4] to recommends the medicine based on their allergic conditions matching. By this our system recommends the natural homemade medicines for their temporary health issues. This will increase the acceptance of these homemade medicines among the people.

The Design and Implementation of a Mobile Healthcare Application For Pregnants

The Design and Implementation of a Mobile Healthcare Application For Pregnants

COVID-19 knowledge-based system for diagnosis in Iraq using IoT environment

<p><span>The importance and benefits of healthcare mobile applications is increasing rapidly, especially when such applications are connected to the internet of things (IoT). This paper d<a name="_Hlk39949144"></a>escribes a smart knowledge-based system (KBS) that helps patients showing symptoms of Influenza verify being infected with Coronavirus, commonly known as COVID-19. In addition to the systems’ diagnostic functionality, it helps these patients get medical assistance fast by notifying medical authorities using the IoT. This system displays patient’s location, phone number, date and time of examination. During the applications’ development, the developers used Twilio, short message service (SMS), WhatsApp, and Google map applications.</span></p>

A formally verified authentication protocol in secure framework for mobile healthcare during COVID-19-like pandemic

Existing schemes in the realm of mobile healthcare (also, e-Healthcare) based on cloud and IoMT (Internet of Medical Things) do not ensure end-to-end security and are not compliant with HIPAA (Health Insurance Portability and Accountability Act). It is also very difficult often for these schemes to obtain evidence from the cloud in case of security breaches. In addition to these issues, mobile healthcare applications are prone to various types of attacks and formal proof is often unavailable. In this work, we propose our community cloud framework in an IoMT setting that ensures end-to-end security and circumvents many of the existing negative aspects using the Trusted Platform Module (TPM). We provide necessary proofs using BAN logic and Scyther tool. Also, we show that the energy consumption and the costs of communication and computation for our proposed protocol are far less than that of the existing protocols. We have implemented our protocol using Kotlin language in Android Studio ensuring all the required security properties.

MOBİL SAĞLIK UYGULAMALARI VE SAĞLIK DAVRANIŞI DEĞİŞİKLİĞİ

Mobil sağlık uygulamalarının sağlık bakım hizmetlerinde kullanımı ve bireylerin sağlık davranış değişikliği üzerine etkilerinin incelenmesi ile bu alanda geliştirilecek uygulamalara ışık tutulması amaçlanmıştır. Çalışmanın verileri Ekim 2017-Temmuz 2018 tarihinde Sağlık Bilimleri Üniversitesi elektronik veri tabanları, ULAKBİM Ulusal Veri Tabanı, Ulusal Tez Merkezi, Türk Tıp Dizini, Google Akademik, PubMed, Web of Science, kongre web siteleri taranarak elde edilmiştir. İncelemede “cep telefonu”, “sağlık davranışı” ve “mobil uygulama” anahtar kelimeleriyle yayın yılları 1998-2018 olan ve yayın dili Türkçe ya da İngilizce tam metin makaleler seçilmiştir. Mobil sağlık uygulamaları ile sağlık davranışlarında değişikliği inceleyen, 25 çalışmanın 13 tanesi araştırma, 12 tanesi derleme makale şeklindedir. Yapılan incelemede, araştırmalara konu olan mobil uygulamanın adı, hitap ettiği sağlık alanının değişiklik gösterdiği saptanmıştır. Mobil uygulamalarının çoğunlukla olumlu davranış değişikliklerine yol açtığı ve daha fazla alanda mobil sağlık uygulamalarının olması gerektiği vurgulanmıştır. Mobil sağlık uygulamalarının daha etkili hastalık önleme ve yönetim desteği sağlayarak, sağlık bakımındaki küresel yükü azaltmak için önemli bir araç olabileceği saptanmıştır. Türkiye’de mobil sağlık uygulamalarına ilişkin çalışmaların sınırlı sayıda olduğu ve bu konuyla ilgili daha fazla çalışmanın yapılmasına gereksinim duyulduğu saptanmıştır.

WITHDRAWN: Disease prediction and diagnosis system in cloud based IoT: A review on deep learning techniques

Abstract In recent years, the Internet of Things (IoT) -based mobile healthcare applications have highlighted multi-dimensional events and organizations in real-time. These apps provide a platform for millions of people to continuously receive health updates for a more beneficial lifestyle. Since the launch of IoT devices in the healthcare industry, the core components of these applications have been refined to this point. IoT devices generate huge amounts of data in healthcare. Innovation in cloud computing is used to manage large amounts of data and usability. In this scenario, cloud-based applications play an important role in this rapidly changing world. Experts in this field have sought to robotize the pathway to identify and diagnose diseases that could potentially exploit IT innovation. As a result, various tests have proposed a cloud-based IoT prediction and diagnostic framework for diseases that use a secure and different machine learning algorithm. Extensive studies were undertaken to obtain a variety of research articles from all disciplines of heart disease and to examine important commitments and their focal points. Here, the complete twelve papers are divided. In addition, this survey provides a detailed reflection on the disease prognosis and diagnostic system.

The effectiveness of a monetary reimbursement model for weight reduction via a smartphone application: a preliminary retrospective study

Weight loss for obese populations has been a challenging subject. There are numerous mobile applications to address weight loss, but the low retention rate is a barrier for the intervention. This is a retrospective study, aiming to investigate the effectiveness of financial incentives to achieve weight loss via a monetary reimbursement model on a smartphone application. Participants voluntarily purchased a 16-week mobile weight loss application program, and those who logged food intake three times a day received monetary reimbursement up to the full amount they initially paid. We analyzed health-related information and logged in-app activities from participants (N = 2,803) including age, sex, weight, food intake, and physical activity on their mobile healthcare application called Noom from January 2017 to April 2019. Analysis of covariance (ANCOVA) was used to compare differences between groups who succeeded and failed at food logging, controlling for baseline BMI. The ANCOVA found that participants who completed the food logging successfully for 16 weeks (N = 1,565) lost significantly more weight than those who failed food logging (N = 1,238, F = 56.0, p < 0.001). In addition, participants who were able to log their food intake successfully exercised more (F = 41.5, p < 0.001), read more in-app articles (F = 120.7, p < 0.001), and consumed more quantity of healthy foods (F = 12.8, p < 0.001). Monetary reimbursement is an effective tool for weight reduction by encouraging participants to monitor their health-related behaviors regularly.

Wearable Physiological Monitoring System Based on Electrocardiography and Electromyography for Upper Limb Rehabilitation Training.

Secondary injuries are common during upper limb rehabilitation training because of uncontrollable physical force and overexciting activities, and long-time training may cause fatigue and reduce the training effect. This study proposes a wearable monitoring device for upper limb rehabilitation by integrating electrocardiogram and electromyogram (ECG/EMG) sensors and using data acquisition boards to obtain accurate signals during robotic glove assisting training. The collected ECG/EMG signals were filtered, amplified, digitized, and then transmitted to a remote receiver (smart phone or laptop) via a low-energy Bluetooth module. A software platform was developed for data analysis to visualize ECG/EMG information, and integrated into the robotic glove control module. In the training progress, various hand activities (i.e., hand closing, forearm pronation, finger flexion, and wrist extension) were monitored by the EMG sensor, and the changes in the physiological status of people (from excited to fatigue) were monitored by the ECG sensor. The functionality and feasibility of the developed physiological monitoring system was demonstrated by the assisting robotic glove with an adaptive strategy for upper limb rehabilitation training improvement. The feasible results provided a novel technique to monitor individual ECG and EMG information holistically and practically, and a technical reference to improve upper limb rehabilitation according to specific treatment conditions and the users’ demands. On the basis of this wearable monitoring system prototype for upper limb rehabilitation, many ECG-/EMG-based mobile healthcare applications could be built avoiding some complicated implementation issues such as sensors management and feature extraction.

Mobile applications for elderly healthcare: A systematic mapping.

ContextThe increase in the population aging has brought more significant concern about how proper care will be provided to the elderly in the future. Thus, the development of technological solutions for the health domain has gained more prominence. Joining this scenario to the growing use of mobile devices for daily activities, several mobile applications focused on the elderly healthcare have been developed with healthcare and software engineer professionals involved. However, there is no survey to help both professionals to take decisions on the target of application, elderly profile, empirical validation techniques, among others. Thus, the following question arises: how have mobile applications for elderly healthcare been addressed in the literature in the past years?ObjectiveTo identify the state of the art in the literature concerned with the development of mobile applications for elderly healthcare, considering healthcare and software Engineering viewpoints.MethodWe performed a systematic mapping conducted by health and software engineering researchers to provide an interdisciplinary investigation of the papers that address mobile applications for elderly healthcare, summarizing the data collected under the following classification: target of application, older adult profile, spatial-temporal distribution, techniques for empirical validation and type of software engineering research.ResultsWe found a total of 2533 papers and, after applying our eligibility criteria, we got 149. We observed aspects related to the digital health initiative type, using the classification proposed by the World Health Organization (WHO), the elderly profile prioritized by the application, the spatial-temporal distribution of the studies, the empirical validation type, and the research contribution of each analyzed paper to the software engineering area.ConclusionsRegarding the WHO classification, we noticed that two categories were more frequently found, Clients and Data Services, and that none of the mobile apps were classified in the Health System Manager category. The data extraction result also reveals that most of the applications found in the literature focused on the independent elderly. Moreover, we observed that most of the studies were proposals of solutions for elderly health and the validation process of these solutions generally consisted of controlled experiments and usability evaluations. At last, the research focused on mobile applications for elderly healthcare has been performed mostly by developed countries.

Predicting changes in performance due to cognitive fatigue: A multimodal approach based on speech motor coordination and electrodermal activity

Objective Military job and training activities place significant demands on service members’ (SMs’) cognitive resources, increasing risk of injury and degrading performance. Early detection of cognitive fatigue is essential to reduce risk and support optimal function. This paper describes a multimodal approach, based on changes in measures of speech motor coordination and electrodermal activity (EDA), for predicting changes in performance following sustained cognitive effort. Methods Twenty-nine active duty SMs completed computer-based cognitive tasks for 2 h (load period). Measures of speech derived from audio were acquired, along with concurrent measures of EDA, before and after the load period. Cognitive performance was assessed before and during the load period using the Automated Neuropsychological Assessment Metrics Military Battery (ANAM MIL). Subjective assessments of cognitive effort and alertness were obtained intermittently. Results Across the load period, participants’ ratings of cognitive workload increased, while alertness ratings declined. Cognitive performance declined significantly during the first half of the load period. Three speech and arousal features predicted cognitive performance changes during this period with statistically significant accuracy: EDA (r = 0.43, p = 0.01), articulator velocity coordination (r = 0.50, p = 0.00), and vocal creak (r = 0.35, p = 0.03). Fusing predictions from these features predicted performance changes with r = 0.68 (p = 0.00). Conclusions Results suggest that speech and arousal measures may be used to predict changes in performance associated with cognitive fatigue. This work supports ongoing efforts to develop reliable, unobtrusive measures for cognitive state assessment aimed at reducing injury risk, informing return to work decisions, and supporting diverse mobile healthcare applications in civilian and military settings.