Usability Study on Mobile Processes Enabling Remote Therapeutic Interventions

Many studies have revealed that therapeutic homework is beneficial for the efficacy of therapies. Interestingly, the latter have been less supported by IT systems so far and, hence, therapeutic opportunities have been neglected. For example, mobile devices can be used to notify patients about assigned homework and help them to accomplish it in a timely manner. In general, the use of mobile devices as well as their sensors seem to be promising for the support of remote therapeutic interventions. In the Albatros project, we have been developing a framework that enables domain experts to flexibly define the homework required in the context of a remote therapeutic intervention. More precisely, the various tasks of a homework can be specified as a mobile process, which is then run on the mobile device of the respective patient. To realize this vision, a configurator component using a model-driven approach was developed. In particular, the Albatros configurator shall relieve domain experts from complex technical issues when defining a homework. The study presented in this paper investigates whether domain experts are actually able to use the configurator component. In particular, the study revealed three insights. First, basic interventions can be easily defined with an acceptable number of errors. Second, for defining complex interventions (e.g., using a sensor when performing an exercise) several issues could be identified that will contribute to improve the Albatros configurator. Third, additional studies are needed to evaluate the overall mental effort of domain experts when using the configurator. Altogether, the Albatros framework may be a reasonable alley to empower domain experts in creating homework in the context of remote therapeutic interventions

Towards Flexible Remote Therapeutic Interventions

In the context of therapeutic interventions, smart mobile devices are becoming increasingly important. First, they can properly assist patients in performing their homework – a support required for more efficient therapeutic interven-tions. Second, mobile applications enable therapists to monitor homework outcomes. From a technical perspective, frequently required changes of the mobile applications supporting ther-apeutic interventions constitute a major challenge. To tackle the latter for a multitude of remote therapeutic interventions, e.g., in psychotherapy or physiotherapy, we deploy process management technology to smart mobile devices. This paper discusses flexibility issues addressed by the mobile processes. Particularly, the achieved flexibility, in turn, increases the practical benefits of smart mobile devices in the context of remote therapeutic interventions

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

A Reflection on Virtual Reality Design for Psychological, Cognitive & Behavioral Interventions: Design Needs, Opportunities & Challenges

Despite the substantial research interest in using Virtual Reality (VR) in healthcare in general and in Psychological, Cognitive, and Behavioral (PC&B) interventions in specific, as well as emerging research supporting the efficacy of VR in healthcare, the design process of translating therapies into VR to meet the needs of critical stakeholders such as users and clinicians is rarely addressed. In this paper, we aim to shed light onto the design needs, opportunities and challenges in designing efficient and effective PC&B-VR interventions. Through analyzing the co-design processes of four user-centered PC&B-VR interventions, we examined how therapies were adapted into VR to meet stakeholders’ requirements, explored design elements for meaningful experiences, and investigated how the understanding of healthcare contexts contribute to the VR intervention design. This paper presents the HCI research community with design opportunities and challenges as well as future directions for PC&B-VR intervention design

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ATOPE+: An mHealth System to Support Personalized Therapeutic Exercise Interventions in Patients With Cancer

The authors express their gratitude to the patients and experts for their participation in the evaluation of ATOPEC. They also express their gratitude to the anonymous reviewers for the instructive criticism of an earlier version of this article.The introduction of mobile technologies in therapeutic exercise interventions has permitted the collection of fine-grained objective quantified information about patients' health. However, exercise interventions generally fail to leverage these data when personalizing the exercise needs of patients individually. Interventions that include technology-driven personalization strategies typically rely on the use of expensive laboratory equipment with expert supervision, or in the self-management of patients to meet the prescribed exercise levels by an activity tracker. These methods often do not perform better than non technology-driven methods, therefore more sophisticated strategies are required to improve the personalization process. In this paper we present ATOPE+, an mHealth system to support personalized exercise interventions in patients with cancer based on workload-recovery ratio estimation. ATOPE+ enables the remote assessment of workload-recovery ratio to provide optimal exercise dosage by means of a knowledge-based system and by combining physiological data from heterogeneous data sources in a multilevel architecture. The results show that ATOPE+ is a system ready to be used in the context of a clinical trial after being tested with patients with breast cancer and conducting an usability evaluation by clinical experts.Spanish Ministry of Science, Innovation, and Universities (MICINN) PGC2018-098813-B-C31 RTI2018-101674-B-I00Health Research Funds of the Carlos III Health Institute PI18/01840German Research Foundation (DFG) FPU16/04201 FPU17/0093

Supporting remote therapeutic interventions with voice assistant technology

Nowadays, digital personal assistants are incorporated in many devices. Smart TVs, smartphones and stand-alone voice assistants like Amazon Alexa allow owners to control their smart home systems, play music on command or lookup information on the internet via voice queries. Using custom skills from various third-party vendors, almost any company can have a skill supporting the needs of their customers or control their devices. Furthermore, therapeutic interventions represent a vital part of most therapies, but there are some underlying struggles during therapies for which therapists can utilize the support of smart mobile devices. As an extension of an already existing system called Albatros, its features have been converted into an custom Alexa skill called remote interventions. But voice assistants can do more than improving everyday life, like helping people during medical therapies. A vital part of such therapies are therapeutic interventions, but therapists often face struggles when monitoring a patients progress and results. To overcome this problem, an existing system called Albatros allows a therapist to review the patients status. As an extension to the existing Albatros system, its features have been incorporated into a custom Alexa skill called remote interventions. Aiming to contribute to the proof of concept, the objective of this thesis is to demonstrate the development process of a custom Alexa skill which implements the features of retrieving exercises, allowing patients to record feedback via a smart speaker which can then be accessed by the therapist. With the addition of a notification feature the system also supports patients in remembering how and when to do their exercises properly. Due to the proof of concept nature of the project, apart from the actual development process, an analysis of whether or not the ideas and features translate well into a voice driven platform is performed

Co-designing an eHealth Intervention to Support the Self-Management of Fibromyalgia

Fibromyalgia is a rheumatic pathology that causes a wide range of symptoms that can appear individually, or in sets, such as fatigue, sleep disorders, attention, and concentration deficit, also having connection with musculoskeletal, psychological, cardiovascular, gastrointestinal disorders. This pathology has a greater predominance in women and, in Portugal, for every man there are six women with the diagnosis and a total of approximately two hundred thousand people (2.1% of the population). The non-pharmaceutical way to mitigate these symptoms is through physical therapy. Considering the pandemic moment in which we live, there have been many difficulties in having physical therapy sessions because of the fear of infection through contact with their physical therapists. There are also people who live in more isolated areas and with little access to healthcare, who often must travel to larger urban centers to get the care they need. Moreover, these people have difficulties in self-managing their illness, where depending on the day their symptoms can get worse, and they do not know how to deal with them. Currently, there is no specialized solution for people with this diagnosis that solves these problems, so this dissertation aims to study and design a solution that allows people diagnosed with fibromyalgia to self-manage their pathology, as well as have a closer contact with their physical therapist, by being able to perform their sessions in a hybrid way, i.e., in person or remotely. This solution was designed using a Co-Design approach, following the Design Thinking methodology, where the community (people with the diagnosis, physiotherapists, researchers and academics) were involved in all stages of the process, from problem identification and idealization of their solutions, to prototyping and its validation. This solution involved the development of a mobile application, having several important components, such as self management, telerehabilitation, motivation, community and communication. In order to evaluate the whole process and the usability of the solution, tests were performed with end users who had not yet participated in the design of the solution