Smartphone Apps in the Context of Tinnitus: Systematic Review

Smartphones containing sophisticated high-end hardware and offering high computational capabilities at extremely manageable costs have become mainstream and an integral part of users' lives. Widespread adoption of smartphone devices has encouraged the development of many smartphone applications, resulting in a well-established ecosystem, which is easily discoverable and accessible via respective marketplaces of differing mobile platforms. These smartphone applications are no longer exclusively limited to entertainment purposes but are increasingly established in the scientific and medical field. In the context of tinnitus, the ringing in the ear, these smartphone apps range from relief, management, self-help, all the way to interfacing external sensors to better understand the phenomenon. In this paper, we aim to bring forth the smartphone applications in and around tinnitus. Based on the PRISMA guidelines, we systematically analyze and investigate the current state of smartphone apps, that are directly applied in the context of tinnitus. In particular, we explore Google Scholar, CiteSeerX, Microsoft Academics, Semantic Scholar for the identification of scientific contributions. Additionally, we search and explore Google’s Play and Apple's App Stores to identify relevant smartphone apps and their respective properties. This review work gives (1) an up-to-date overview of existing apps, and (2) lists and discusses scientific literature pertaining to the smartphone apps used within the context of tinnitus

Combining Mobile Crowdsensing and Ecological Momentary Assessments in the Healthcare Domain

The increasing prevalence of smart mobile devices (e.g., smartphones) enables the combined use of mobile crowdsensing (MCS) and ecological momentary assessments (EMA) in the healthcare domain. By correlating qualitative longitudinal and ecologically valid EMA assessment data sets with sensor measurements in mobile apps, new valuable insights about patients (e.g., humans who suffer from chronic diseases) can be gained. However, there are numerous conceptual, architectural and technical, as well as legal challenges when implementing a respective software solution. Therefore, the work at hand (1) identifies these challenges, (2) derives respective recommendations, and (3) proposes a reference architecture for a MCS-EMA-platform addressing the defined recommendations. The required insights to propose the reference architecture were gained in several large-scale mHealth crowdsensing studies running for many years and different healthcare questions. To mention only two examples, we are running crowdsensing studies on questions for the tinnitus chronic disorder or psychological stress. We consider the proposed reference architecture and the identified challenges and recommendations as a contribution in two respects. First, they enable other researchers to align our practical studies with a baseline setting that can satisfy the variously revealed insights. Second, they are a proper basis to better compare data that was gathered using MCS and EMA. In addition, the combined use of MCS and EMA increasingly requires suitable architectures and associated digital solutions for the healthcare domain

Design, concept and implementation for an electronic and mobile patient health record of tinnitus affected patients using the iOS platform

Tinnitus is increasingly affecting individuals who report that they hear a whistilng or other noise without any external sound source. Currently, there is no treatment that completely eliminates tinnitus. However, there are ways to allay this, for example by questionnaires or therapies. On the basis of auditory tests changes can be documented in the perception of tinnitus. Through observation of event triggers and amplifiers, appropriate actions can be taken. For all of these approaches, the TinnitusNavigator app has been developed which supports the patient in dealing with tinnitus and brings the patient closer to a relief of symptoms. Users will find an easy navigation since the iOS-ware Guidelines were considered in the design. Using the Core Data framework of Apple supported the realisation of the model from the Model View Controller pattern. At the end the outcome of this work is a working application

Requirements for a Flexible and Generic API Enabling Mobile Crowdsensing mHealth Applications

Presently, mHealth becomes increasingly important in supporting patients in their everyday life. For example, diabetes patients can monitor themselves by the use of their smartphones. On the other, clinicians as well as medical researchers try to exploit the advantages of mobile technology. More specifically, mHealth applications can gather data in everyday life and are able to easily collect sensor or context data (e.g., the current temperature). Compared to clinical trials, these advantages enable mHealth applications to gather more data in a rather short time. Besides, humans often behave atypically in a clinical environment and, hence, mHealth applications collect data in a setting that reflects the daily behavior more naturally. Hitherto, many technical solutions emerged to deal with such data collection settings. Mobile crowdsensing is one prominent example in this context. We utilize the latter technology in a multitude of large-scale projects to gather data of several chronic disorders. In the TrackYourTinnitus project, for example, we pursue the goal to reveal new medical insights to the tinnitus disorder. We learned in the realized projects that a sophisticated API must be provided to cope with the requirements of researchers from the medical domain. Notably, the API must be able to flexibly deal with requirement changes. The work at hand presents the elicited requirements and illustrate the pillars on which our flexible and generic API is built on. Although we identified that the maintenance of such an API is a challenging endeavor, new data evaluation opportunities arise that are promising in the context of chronic disorder management

Conception and Realization of a Mobile Crowdsensing Application for Support and Empowerment of Diabetes Patients

Diabetes is an increasingly common chronic disease. Not only in the Western World but across the globe. Statistics show, that 10.3% of men and 9.6% of women in the European Union aged 25 or older are forced to live with this disease, and the numbers are rising [1]. It is a chronic disorder of the metabolism, and a number of dangerous complications can arise if the medical treatment is not supervised carefully. These complications can be lethal, and severely reduce the quality of life of every individual patient. Thoroughly following the medical advices requires considerable discipline of the patient. This project aims to help the patients suffering diabetes, by providing a healthcare application to support them in their daily self-care. The application is called Track your Diabetes, and is designed to be a daily companion for the patient. Moreover, it is a mobile crowdsensing application and the collected data can empower researchers to improve the knowledge about the disease. Patient education, empowerment, and practical self-management to help deal with symptoms, is achieved by tracking diabetes related data such as the blood glucose level and weight. Depending on the data, the users can receive automated feedbacks, in order to improve their self-management. The application is questionnaire-based. This means, that the application only tracks data based on the questionnaires published. Patients can then share their data with their medical attendant who, in turn, can use it to improve their treatment methods. Designing this application, and providing prove for its feasibility by implementing it, is the central topic of this thesis. One major requirement was for the application to use the interface of a given RESTful API backend. This backend is planned to be a central database for the relevant data of all users. This work shows, how the application was designed and implemented for the operating system Android

Conceptualization and Realization of a Database Migration Path for an International and mHealth Tinnitus Database

The mobile crowdsensing platform TrackYourTinnitus (TYT) was created to monitor and visualize fluctuations of tinnitus perception by affected individuals using smart devices. The platform aims to gather data of tinnitus patients for research purposes and to help those affected to better understand the fluctuations of tinnitus perception. Users have to answer specific questionnaires to assess tinnitus perception and tinnitus-related parameters during their daily routine. The gathered data from the questionnaires are stored in the MariaDB database running on the back-end of the application. In the future, the data of TrackYourTinnitus will be merged with clinical databases to broaden the researches related to the tinnitus symptom. Consequently, the amount of data stored in the relational database will notably increase. Additionally, MRI scans will be joined to patients? data to allow a better overview of the tinnitus development for individuals. For this purpose, it is considered to look for an alternative system for hosting the TYT database, since the current database running on MariaDB does not deliver the performance required. This work attempts to transfer the TrackYourTinnitus database from MariaDB to SQL Server. The system migration aims to ensure smooth database operations when dealing with data on a large scale as well as to benefit from the advanced features of T-SQL, the query language used by SQL Server

A Model-Driven Framework for Enabling Flexible and Robust Mobile Data Collection Applications

In the light of the ubiquitous digital transformation, smart mobile technology has become a salient factor for enabling large-scale data collection scenarios. Structured instruments (e.g., questionnaires) are frequently used to collect data in various application domains, like healthcare, psychology, and social sciences. In current practice, instruments are usually distributed and filled out in a paper-based fashion (e.g., paper-and-pencil questionnaires). The widespread use of smart mobile devices, like smartphones or tablets, offers promising perspectives for the controlled collection of accurate data in high quality. The design, implementation and deployment of mobile data collection applications, however, is a challenging endeavor. First, various mobile operating systems need to be properly supported, taking their short release cycles into account. Second, domain-specific peculiarities need to be flexibly aligned with mobile application development. Third, domain-specific usability guidelines need to be obeyed. Altogether, these challenges turn both programming and maintaining of mobile data collection applications into a costly, time-consuming, and error-prone endeavor. The Ph.D. thesis at hand presents an advanced framework that shall enable domain experts to transform paper-based instruments to mobile data collection applications. The latter, in turn, can then be deployed to and executed on heterogeneous smart mobile devices. In particular, the framework shall empower domain experts (i.e., end-users) to flexibly design and create robust mobile data collection applications on their own; i.e., without need to involve IT experts or mobile application developers. As major benefit, the framework enables the development of sophisticated mobile data collection applications by orders of magnitude faster compared to current approaches, and relieves domain experts from manual tasks like, for example, digitizing and analyzing the collected data

Tinnitus Guidelines and Their Evidence Base

Evidence-based medicine (EBM) is generally accepted as the gold standard for high-quality medicine and, thus, for managing patients with tinnitus. EBM integrates the best available scientific information with clinical experience and patient values to guide decision-making about clinical management. To help health care providers and clinicians, the available evidence is commonly translated into medical or clinical guidelines based on a consensus. These involve a systematic review of the literature and meta-analytic aggregation of research findings followed by the formulation of clinical recommendations. However, this approach also has limitations, which include a lack of consideration of individual patient characteristics, the susceptibility of guideline recommendations to material and immaterial conflicts of interest of guideline authors and long latencies till new knowledge is implemented in guidelines. A further important aspect in interpreting the existing literature is that the absence of evidence is not evidence of absence. These circumstances could result in the decoupling of recommendations and their supporting evidence, which becomes evident when guidelines from different countries differ in their recommendations. This opinion paper will discuss how these weaknesses can be addressed in tinnitus

Understanding user reactions and interactions with an internet-based intervention for tinnitus self-management: mixed-methods process evaluation protocol

Background: Tinnitus is a common medical symptom that can affect an individual’s emotional and functional quality of life. Psychological therapies are acknowledged as beneficial to people with tinnitus; however, such therapies are not always readily accessible. With their global reach, automated Internet-based interventions have the potential to reduce the disparity in access to psychological support that people with tinnitus currently experience. However, the evidence on the acceptability and efficacy of these interventions is lacking. Process evaluations that develop an in-depth understanding of how users experience these interventions provide an essential first step when evaluating complex psychological interventions. Objective: To describe the protocol for a study that will explore past, current, and new users’ reactions to and interactions with the Tinnitus E-Programme, an Internet-based intervention for the self-management of tinnitus. Methods: Two parallel mixed-methods studies will be carried out with 2 different populations. Study 1 will use an online survey to gather past and current users’ views of the program. Study 2 will recruit new program users to take part in an interview and complete a relaxation log to explore how well they were able to implement the skills they learned during the program in their everyday lives. The findings from both studies will be triangulated to develop an in-depth understanding of the program’s mechanisms of impact and identify any implementation or contextual factors that strengthen or impede its delivery and functioning. Results: Study 1 is open for recruitment with a projected completion in June 2016 and Study 2 was completed November 2015. At the time of submission, 36 participants have been recruited to Study 1 and 12 participants have taken part in Study 2. Conclusions: Findings will inform the optimization of the Tinnitus E-Programme and guide future evaluation work to assess the program’s effectiveness as a therapy for people with tinnitus