Mobile Health System Research Articles

Mobilities of the Community Health Work Practice: Mobile Health system Mediated Work

New technologies have been implicated in various forms of mobilities creating new realities and questioning normative categories and the order in contexts where they are applied. Our study argues that through understanding technology mobilities, we uniquely bring to light new forms of social phenomena that materialize with interactions between mHealth systems and the work of Community Health workers in Malawi. Through the analysis, we also elaborate the role of both human and non-human actants in work transformations. This is important in managing technological innovations and theorizing electronically supported work practices.

Mobile health architecture for obesity management using sensory and social data

Abstract One of the principal causes of several chronic diseases (e.g., diabetes, high cholesterol, and hypertension) is the obesity epidemic in high and middle income countries. Obesity also leads to an increasingly negative effect on public health resources. Therefore, obesity and overweight have to be monitored to mitigate and prevent the potential risks generated from the threat of related diseases and from reducing productivity experienced by businesses. A mobile-health monitoring system includes sensing, transmitting, storing, processing, and analyzing intensive, continuous, and heterogeneous medical data. However, current approaches are standalone mobile applications, augmented mobile applications, or mobile health systems. These approaches only consider simple activities (assess, detect, or control obesity) and rely on a mobile phone to perform complex processing operations on the collected data. Such complex operations need (1) efficient data mining techniques, (2) more memory consumption and processing time, and (3) long life mobile battery. In this work, we develop a new comprehensive mobile architecture for tackling the challenging issues of obesity control, monitoring, and prevention. We introduce a set of business requirements considering stakeholders, sensor devices, and architecture requirements to meet our architecture's objectives. Our architecture system can also help individuals track food intake, lifestyle, calories intake, calories consumption, and exercise activities. We analyze the data collected from continuous monitoring using non-invasive sensors, in addition to the data collected from social communities created to propagate awareness and share appropriate information about the obesity problem and its solution. We develop data mining algorithms and sentiment analysis algorithms and generate intelligent suggestions, warnings, and recommendations to control and mitigate the risk of obesity and its related diseases. We develop schemes for reducing data and saving energy, which minimize the amount of network traffic within the community of sensors. Moreover, we totally implement our architecture system as a collection of Web services organized by the model–view–controller design pattern to write, retrieve, and access data to and from the cloud storage firebase. We finally evaluate the efficacy and scalability of the implemented system using a comprehensive cloud database including entered data, calculated data, sensory data, and social data of 50 underweight, overweight, normal, and obese volunteer subjects. The obtained results show our architecture's objectives are fulfilled.

An intelligent method of cancer prediction based on mobile cloud computing

In recent years, mobile medical services have gradually become the common focus of the communications and healthcare industries. People can get medical information and services efficiently and conveniently anytime, anywhere. However, due to the limitations of the mobile terminal’s own computing and storage capabilities, mobile therapy is greatly challenged. Therefore, we propose a mobile medical health system based on cloud computing. Firstly, principal component analysis was used to obtain representative features. Then, a simplified feature subset was applied to support vector machine (SVM) based on Sigmoid kernel function. The data set was categorized by SVM as cancer patient and normal object experimental results show that the method is improved in accuracy, sensitivity, and specificity.

Mobile Health Intervention to Increase Oral Cancer Therapy Adherence in Patients With Chronic Myeloid Leukemia (The REMIND System): Clinical Feasibility and Acceptability Assessment.

BackgroundOptimal dosing of oral tyrosine kinase inhibitor therapy is critical to treatment success and survival of patients with chronic myeloid leukemia (CML). Drug intolerance secondary to toxicities and nonadherence are significant factors in treatment failure.ObjectiveThe objective of this study was to develop and pilot-test the clinical feasibility and acceptability of a mobile health system (REMIND) to increase oral drug adherence and patient symptom self-management among people with CML (chronic phase).MethodsA multifaceted intervention was iteratively developed using the intervention development framework by Schofield and Chambers, consisting of defining the patient problem and iteratively refining the intervention. The clinical feasibility and acceptability were examined via patient and intervention nurse interviews, which were audiotaped, transcribed, and deductively content analyzed.ResultsThe intervention comprised 2 synergistically operating elements: (1) daily medication reminders and routine assessment of side effects with evidence-based self-care advice delivered in real time and (2) question prompt list (QPL) questions and routinely collected individual patient adherence and side effect profile data used to shape nurses’ consultations, which employed motivational interviewing to support adoption of self-management behaviors. A total of 4 consultations and daily alerts and advice were delivered over 10 weeks. In total, 58% (10/17) of patients and 2 nurses participated in the pilot study. Patients reported several benefits of the intervention: help in establishing medication routines, resolution of symptom uncertainty, increased awareness of self-care, and informed decision making. Nurses also endorsed the intervention: it assisted in establishing pill-taking routines and patients developing effective solutions to adherence challenges.ConclusionsThe REMIND system with nurse support was usable and acceptable to both patients and nurses. It has the potential to improve adherence and side-effect management and should be further evaluated.

Fuzzy optimization to improve mobile health and wellness recommendation systems

In this article, we focus on mobile wellness and health-related applications from the perspective of the level of imprecision present in the data used in the recommendation systems. We propose a general fuzzy optimization model based on chanced constrained optimization to design recommendation systems that can take into consideration (i) the imprecision in the data and (ii) the imprecision by which one can estimate the effect of a recommendation on the user of the system. Our proposal is one of the first to use fuzzy optimization models in health-related decision making problems and the first to define a chance constrained optimization problem for interval-valued fuzzy numbers. The proposed approach identifies a set of actions to be taken by the users in order to optimize general health-related and/or wellness condition of the user from various perspectives. The model is illustrated through the example of walking speed optimization, with an additional numerical experiment offering a comparison with traditional methods.

An Innovative Mobile Health System to Improve and Standardize Antenatal Care Among Underserved Communities: A Feasibility Study in an Italian Hosting Center for Asylum Seekers.

Innovative migrant-friendly tools are needed to assist health personnel manage the high number of pregnancies within reception centers. This study tests functionality and acceptability of a new mHealth system in providing antenatal care amongst migrants. The study, carried out between 2014 and 2016, involved 150 pregnant women residing in the largest European migrant reception center in Sicily. A ticket tracking system assessed the system's functionality and a questionnaire assessed women's acceptability. The system facilitated the collection of clinical data, enabling the creation of electronic patient records and identifying 10% of pregnancies as high-risk. The application's digital format increased health providers' adherence to antenatal-care recommendations, while the graphic interface facilitated women's engagement and retention of the health education modules. The study recorded a 91.9% patient satisfaction rate. The system was efficient in providing comprehensive and high-quality antenatal care amongst migrants, facilitating the continuity of care for a population undergoing frequent relocations.

A review of privacy and usability issues in mobile health systems: Role of external factors.

The increased penetration of mobile devices has created opportunities in the health sector and led to emerging of mobile health systems. As much as the mobile health systems have registered tremendous progress, they have been faced with privacy and usability issues. Due to the sensitivity of health information, there is an ethical need to equip mobile health systems with adequate privacy measures. However, these systems should also be useable by the intended users. Even though many researchers are working on solutions, the issues still persist. External factors such as cultural differences have also contributed to the issues, yet they have been under researched. In this article, we conduct a systematic literature review of 22 articles, categorize and present privacy and usability issues and possible solutions. We then discuss the relevance and implications of external factors to the findings on privacy and usability. We end with recommendations to address these external factors.

Integrated mobile health systems: Role of socio-cultural factors and the socio-technical systems approach

This paper discusses the role of socio-cultural factors in strengthening integrated mobile health systems. Emphasis is placed on the importance that any initiative in mobile health should consider the analysis of socio-cultural factors during the process of the development and implementation of programs and research interventions. The socio-cultural and socio-technical approach also consider the human factor and considers the conditions of the environment and the context beyond the technological resources of the mobile health system and the infrastructure that supports it. Methodologies such as observational studies, focus groups, and in-depth interviews should be included ideally in any mobile health study. We also present a case study in the north area of Lima (Peru), adapting the Community-Based Participatory Research platform that is based on a socio-technical approach and evaluates the socio-cultural approach with the objective to optimize the diagnosis process of tuberculosis using mobile health.

Lightweight Sharable and Traceable Secure Mobile Health System

Mobile health (mHealth) has emerged as a new patient centric model which allows real-time collection of patient data via wearable sensors, aggregation and encryption of these data at mobile devices, and then uploading the encrypted data to the cloud for storage and access by healthcare staff and researchers. However, efficient and scalable sharing of encrypted data has been a very challenging problem. In this paper, we propose a Lightweight Sharable and Traceable (LiST) secure mobile health system in which patient data are encrypted end-to-end from a patient's mobile device to data users. LiST enables efficient keyword search and fine-grained access control of encrypted data, supports tracing of traitors who sell their search and access privileges for monetary gain, and allows on-demand user revocation. LiST is lightweight in the sense that it offloads most of the heavy cryptographic computations to the cloud while only lightweight operations are performed at the end user devices. We formally define the security of LiST and prove that it is secure without random oracle. We also conduct extensive experiments to access the system's performance.

A User-Centered Approach: Understanding Client and Caregiver Needs and Preferences in the Development of mHealth Apps for Self-Management.

BackgroundMany adolescents and young adults with chronic illness or disability often fail to develop the self-management skills necessary to independently handle medical and self-management routines. In light of these needs, we are developing iMHere 2.0 (Interactive Mobile Health and Rehabilitation), a mobile health (mHealth) system to support a self-management program.ObjectiveOur objective was to gather data from persons with brain and spinal cord anomalies (BSA) and their caregivers to better understand how mHealth would be most helpful in supporting them to proactively manage daily self-care routines and to access medical care as needed. The specific purpose was not only to gather feedback and to gain increased insight into the design of the new version of iMHere, but also to gather perspectives of new groups, namely adolescents as young as 12 years and their parents and/or caregivers.MethodsOur project employed focus group sessions and surveys to collect data from participants with BSA, as well as their caregivers. A total of six focus group sessions were conducted on four separate occasions until the data gathered reached saturation. The objectives of our focus group sessions were to better understand ways to develop mHealth systems to support self-management, to promote independence, to motivate long-term system use, and to prevent medical problems that lead to hospitalizations and emergency room visits for youth and young adults with BSA.ResultsA total of 16 youth and young adults with BSA and 11 caregivers participated in the sessions. Within and among our groups, the following five overarching themes emerged from the data: (1) make it easy, (2) engage, (3) educate and prepare, (4) motivate and support, and (5) personalize. Participants shared their perspectives and detailed information about mHealth apps that would be important for independence in self-care and self-management.ConclusionsOur findings suggest that most individuals keep their mobile phones with them at all times and typically use a mobile phone for social media, music, photos, and texting. Our qualitative analysis indicates that youth and young adults with BSA, as well as their caregivers, acknowledge the importance of being actively engaged in developing and using mHealth apps that monitor and manage their health care needs. Information gleaned from these focus group sessions and surveys have provided data to refine the iMHere 2.0 mHealth prototype platform that we have developed.

Lessons from the Deployment of the SPIRIT App to Support Collaborative Care for Rural Patients with Complex Psychiatric Conditions.

We report the design and deployment of a mobile health system for patients receiving primary care-based mental health services (Collaborative Care) for post-traumatic stress disorder and/or bipolar disorder in rural health centers. Here we describe the clinical model, our participatory approach to designing and deploying the mobile system, and describe the final system. We focus on the integration of the system into providers' clinical workflow and patient registry system. We present lessons learned about the technical and training requirements for integration into practice that can inform future efforts to incorporate health technologies to improve care for patients with psychiatric conditions.

User-Centered Evaluations with Older Adults: Testing the Usability of a Mobile Health System for Heart Failure Self-Management.

Many older adults living with heart failure struggle to follow recommended self-management routines. To help older adults with heart failure more effectively and efficiently self-manage their disease, we developed Engage, a mobile health application promoting the performance, logging, and sharing of routine self-management behaviors. This paper reports on the usability evaluation of the Engage system with 15 older adults with heart failure and informal caregivers. In two phases, participants used Engage during a task-based usability test (n=5) and a scenario-based usability test (n=10). Usability and performance data were assessed through video-recorded observation and the administration of the system usability scale (SUS) and NASA Task Load Index (TLX). We found that task-based testing was useful in quickly identifying problems within our application, but scenario-based testing elicited more valuable feedback from older adults. A comparison of the different evaluation methods used and the discussion of the challenges encountered provide multiple implications for the practice of usability testing of mobile health products with older adults.

Design of Mobile Health Tools to Promote Goal Achievement in Self-Management Tasks.

BackgroundGoal-setting within rehabilitation is a common practice ultimately geared toward helping patients make functional progress.ObjectiveThe purposes of this study were to (1) qualitatively analyze data from a wellness program for patients with spina bifida (SB) and spinal cord injury (SCI) in order to generate software requirements for a goal-setting module to support their complex goal-setting routines, (2) design a prototype of a goal-setting module within an existing mobile health (mHealth) system, and (3) identify what educational content might be necessary to integrate into the system.MethodsA total of 750 goals were analyzed from patients with SB and SCI enrolled in a wellness program. These goals were qualitatively analyzed in order to operationalize a set of software requirements for an mHealth goal-setting module and identify important educational content.ResultsThose of male sex (P=.02) and with SCI diagnosis (P<.001) were more likely to achieve goals than females or those with SB. Temporality (P<.001) and type (P<.001) of goal were associated with likelihood that the goal would be achieved. Nearly all (210/213; 98.6%) of the fact-finding goals were achieved. There was no significant difference in achievement based on goal theme. Checklists, data tracking, and fact-finding tools were identified as three functionalities that could support goal-setting and achievement in an mHealth system. Based on the qualitative analysis, a list of software requirements for a goal-setting module was generated, and a prototype was developed. Targets for educational content were also generated.ConclusionsInnovative mHealth tools can be developed to support commonly set goals by individuals with disabilities.

New algorithms for processing time-series big EEG data within mobile health monitoring systems

Background and objectivesRecent advances in miniature biomedical sensors, mobile smartphones, wireless communications, and distributed computing technologies provide promising techniques for developing mobile health systems. Such systems are capable of monitoring epileptic seizures reliably, which are classified as chronic diseases. Three challenging issues raised in this context with regard to the transformation, compression, storage, and visualization of big data, which results from a continuous recording of epileptic seizures using mobile devices. MethodsIn this paper, we address the above challenges by developing three new algorithms to process and analyze big electroencephalography data in a rigorous and efficient manner. The first algorithm is responsible for transforming the standard European Data Format (EDF) into the standard JavaScript Object Notation (JSON) and compressing the transformed JSON data to decrease the size and time through the transfer process and to increase the network transfer rate. The second algorithm focuses on collecting and storing the compressed files generated by the transformation and compression algorithm. The collection process is performed with respect to the on-the-fly technique after decompressing files. The third algorithm provides relevant real-time interaction with signal data by prospective users. It particularly features the following capabilities: visualization of single or multiple signal channels on a smartphone device and query data segments. ResultsWe tested and evaluated the effectiveness of our approach through a software architecture model implementing a mobile health system to monitor epileptic seizures. The experimental findings from 45 experiments are promising and efficiently satisfy the approach's objectives in a price of linearity. Moreover, the size of compressed JSON files and transfer times are reduced by 10% and 20%, respectively, while the average total time is remarkably reduced by 67% through all performed experiments. ConclusionsOur approach successfully develops efficient algorithms in terms of processing time, memory usage, and energy consumption while maintaining a high scalability of the proposed solution. Our approach efficiently supports data partitioning and parallelism relying on the MapReduce platform, which can help in monitoring and automatic detection of epileptic seizures.

Voter's Intention to Use Electronic Voting Systems

Although the need for comprehensive assessment of mobile health (mHealth) systems is critical, most existing research focuses solely on these systems' technical merits. The purpose of this study is to prioritize different aspects and indicators of assessing the quality of mHealth services and compare four popular Iranian mHealth systems using this framework. Statistical population of this research included experts who have more than three years of active experience in the field. Using Judgmental sampling method, statistical sample size included 28 persons who responded to questionnaires. Content validity was confirmed by an expert panel, and reliability was confirmed by an inconsistency rate of less than 0.1. The study findings show that results quality is the most important component of quality assessment for mHealth systems. It also shows that indicators of confidentiality, responsiveness and customer orientation are likewise important.

A novel smartphone camera-LED Communication for clinical signal transmission in mHealth-rehabilitation system.

In this paper, an implementation of mobile-Visible Light Communication (mVLC) technology for clinical data transmission in home-based mobile-health (mHealth) rehabilitation system is introduced. Mobile remote rehabilitation program is the solutions for improving the quality of care of the clinicians to the patients with chronic condition and disabilities. Typically, the program inquires routine exercise which obligate patients to wear wearable electronic sensors for hours in a specific range of time. Thus it motivate us to develop a novel harmless biomedical communicating system since most of the device's protocol was based on RF communication technology which risky for a human body in term of long term usage due to RF exposure and electromagnetic interference (EMI). The proposed system are designed to utilize a visible light as a medium for hazardless-communication between wearable sensors and a mobile interface device (smartphone). Multiple clinical data such as photoplethysmogram (PPG), electrocardiogram (ECG), and respiration signal are transmitted through LED and received by a smartphone camera. Furthermore, a smartphone also used for local interface and data analyzer henceforth sent the data to the cloud for further clinician's supervision.

Quality Assessment Framework for Mobile Health Systems

Web-based, online social networking has received much attention from researchers in a variety of academic disciplines, with interesting issues addressed from different perspectives. Although Internet technologies play an instrumental role in the provision of the connectivity and message exchange capabilities that are required for the member interactions, the impacts of extensive usage of online social networks often are often on the non-technological aspects. This research investigates the driving forces of website loyalty, an issue of interest to both the individuals using the service for socializing and for the businesses deploying social networks as a serious technological tool for business promotion purposes. Using Facebook as the target of observation, this study evaluates the effects of social presence and social capital on website loyalty. The analysis reveals a positive influence of social presence on all three (structural, relational and cognitive) dimensions of social capital. Further, both the relational and cognitive dimensions of social capital have positive influence on the website loyalty.

An m-Health system for education and motivation in cardiac rehabilitation: the experience of HeartCycle guided exercise

Introduction Home-based programmes for cardiac rehabilitation play a key role in the recovery of patients with coronary artery disease. However, their necessary educational and motivational components have been rarely implemented with the help of modern mobile technologies. We developed a mobile health system designed for motivating patients to adhere to their rehabilitation programme by providing exercise monitoring, guidance, motivational feedback, and educational content. Methods Our multi-disciplinary approach is based on mapping “desired behaviours” into specific system’s specifications, borrowing concepts from Fogg’s Persuasive Systems Design principles. A randomised controlled trial was conducted to compare mobile-based rehabilitation (55 patients) versus standard care (63 patients). Results Some technical issues related to connectivity, usability and exercise sessions interrupted by safety algorithms affected the trial. For those who completed the rehabilitation (19 of 55), results show high levels of both user acceptance and perceived usefulness. Adherence in terms of started exercise sessions was high, but not in terms of total time of performed exercise or drop-outs. Educational level about heart-related health improved more in the intervention group than the control. Exercise habits at 6 months follow-up also improved, although without statistical significance. Discussion Results indicate that the adopted design methodology is promising for creating applications that help improve education and foster better exercise habits, but further studies would be needed to confirm these indications.

Design and Usability of a Heart Failure mHealth System: A Pilot Study.

BackgroundDespite the advances in mobile health (mHealth) systems, little is known about patients’ and providers’ experiences using a new mHealth system design.ObjectiveThis study aimed to understand challenges and provide design considerations for a personalized mHealth system that could effectively support heart failure (HF) patients after they transition into the home environment.MethodsFollowing exploratory interviews with nurses and preventive care physicians, an mHealth system was developed. Patients were asked to measure their weight, blood pressure, and blood glucose (if they had diabetes). They were also instructed to enter symptoms, view notifications, and read messages on a mobile app that we developed. A Bluetooth-enabled weight scale, blood pressure monitor, glucometer, and mobile phone was provided after an introductory orientation and training session. HF nurses used a dashboard to view daily measurements for each patient and received text and email alerts when risk was indicated. Observations of usage, cases of deterioration, readmissions, and metrics related to system usability and quality of life outcomes were used to determine overall effectiveness of the system, whereas focus group sessions with patients were conducted to elicit participants’ feedback on the system’s design.ResultsA total of 8 patients with HF participated over a 6-month period. Overall, the mean users’ satisfaction with the system ranked 73%, which was above average. Quality of life improvement was 3.6. Patients and nurses used the system on a regular basis and were able to successfully identify and manage 8 health deteriorations, of which 5 were completely managed remotely. Focus groups revealed that, on one hand, the system was beneficial and helped patients with: recording and tracking readings; receiving encouragement and reassurance from nurses; spotting and solving problems; learning from past experiences; and communication. On the other hand, findings also highlighted design issues and recommendations for future systems such as the need to communicate via other media, personalize symptom questions and messages, integrate other health tracking technologies, and provide additional methods to analyze and visualize their data.ConclusionsUnderstanding users’ experiences provides important design considerations that could complement existing design recommendations from the literature, and, when combined with physician and nurse requirements, have the potential to yield a feasible telehealth system that is effective in supporting HF self-care. Future studies will include these guidelines and use a larger sample size to validate the outcomes.

Distributed in-network processing and resource optimization over mobile-health systems

Advances in wireless and mobile communication technologies has promoted the development of Mobile-health (m-health) systems to find new ways to acquire, process, transport, and secure the medical data. M-health systems provide the scalability needed to cope with the increasing number of elderly and chronic disease patients requiring constant monitoring. However, the design and operation of such systems with Body Area Sensor Networks (BASNs) is challenging in twofold. First, limited energy, computational and storage resources of the sensor nodes. Second, the need to guarantee application level Quality of Service (QoS). In this paper, we integrate wireless network components, and application-layer characteristics to provide sustainable, energy-efficient and high-quality services for m-health systems. In particular, we propose an Energy-Cost-Distortion solution, which exploits the benefits of in-network processing and medical data adaptation to optimize the transmission energy consumption and the cost of using network services. Moreover, we present a distributed cross-layer solution, which is suitable for heterogeneous wireless m-health systems with variable network size. Our scheme leverages Lagrangian duality theory to find efficient trade-off among energy consumption, network cost, and vital signs distortion, for delay sensitive transmission of medical data. Simulation results show that the proposed scheme achieves the optimal trade-off between energy efficiency and QoS requirements, while providing 15% savings in the objective function (i.e., energy-cost-distortion utility function), compared to solutions based on equal bandwidth allocation.