mHealth and Human-Centered Design Towards Enhanced Health, Care, and Well-being

The increasing availability of digital technologies in healthcare provides the means for increased participation of patients in their care path. This increased empowerment is becoming more widespread day by day. Nevertheless, still little or no inclusion in the design process is part of the common practice during the mHealth medical device design. This chapter proposes an approach based on the indications of international standards for medical device design and manufacturing to foster the adoption of co-design techniques and the inclusion of end-users in the decisional process. The adoption of the proposed method, in particular, is suitable with processes based on international standards for medical device management as per a compliant quality management system (ISO 13485), usability evaluation (IEC 62366) and risk management (ISO 14971), which are the methods used by manufacturers to prove compliance with the requirements of the European Regulations. Such a method ensures a high level of protection for all stakeholders while fostering innovation and participation.

In recent years, there has been a growing interest towards the potential hybridisation of digital and physical spaces, an emerging technology paradigm also known as “phygital”. Enabled by the convergence of virtual/augmented/mixed/extended reality, mobile tools, Internet of Things and artificial intelligence, the growing symbiosis between human spaces and computers is leading to the emergence of mixed physical and digital ecosystems, which will have a transformational impact on people's lives. However, the potential role that phygital systems could play in enhancing mental health and well-being is still under investigation. In this chapter, we introduce the concept of phygital interaction for mental health and present some scenarios of how this emerging paradigm can be used to enhance the prevention, promotion and treatment of mental conditions.

In an era in which aging people have to avoid unnecessary travel to the hospital and risky situations, the medical and healthcare sector are facing more and more of the challenges brought by the digital transformation. A considerable change is taking place in the m-Health sector, since mobile devices, e.g., tablets and smartphones, are increasingly used by citizens. Starting from the need for social contact, through remote monitoring, up to homecare assistance, this chapter will focus on the design and development of m-Health applications that provide coaching services related to physical and cognitive exercise, social relationships and nutrition, to aging people and their formal and informal caregivers. When sensors and medical devices are integrated with m-Health technologies, the services’ development grows exponentially, including early detection and prevention, behavioral monitoring, coaching, etc. In this context, the eco-system becomes more complex since the sensors’ integration generates the acquisition of a large amount of data that requires the application of complex data analysis strategies, e.g., Artificial Intelligence (AI). At this point, the m-Health services to be provided to the final users, i.e., aging people and their caregivers, are based on a measurement process characterized by data acquisition, data analysis, and final service with increasing levels of uncertainty in all the steps of the measurement process. Human-centered design is here proposed as a methodological approach to provide the developers with an interpretation reference defined by the users’ needs, limitations and capabilities and a mean to challenge uncertainty based on user requirements and information needs. Coaching scenarios are data-driven flexible descriptions that require a representation of actions, events, or situations able to explain evidence-based user journeys and to trigger future behaviors, investigating its possible performance, the usage opportunities, the technical weaknesses and validating the design and development hypothesis before actual fulfillment.

Digital Twins constitute a class of innovative data-intensive network-based computing solutions based on real-time interactive simulations of physical systems—Physical Twins—in multiple domains, representing and predicting the states of complex systems (from bacteria to cities). However, the variety of Digital Twins proposed in literature makes it difficult to shape a general definition for this class of computational tools (possibly merging with phygital systems). On the other hand, this is a sign of the versatility of Digital Twins, in both their own capability to solve heterogeneous problems in real world and to inspire novel approaches to handle the uncertainty in complex systems. Such advantages are also explored in fields like healthcare, especially considering domains of Digital Health and mHealth. Indeed, major efforts in research are pushing the methodological and technological boundaries of biomedical sciences, translational research, and precision medicine. Such efforts should be pursued for implementing Digital Twins helping, for instance, the human-centric optimization of the resources allocation in healthcare settings (hospitals, homes, and cities). This chapter will present the opportunity and the ethical issues of using these systems for foreseeing the future states of a person or a population (a need that certainly was highlighted during the COVID-19 pandemic) or a system including a medical device and its user.

Medical and public health practices supported by mobile devices are a new class of solutions/services called as mHealth. Mobile devices with their ubiquity, computing abilities, sensors, and immersive experiences present a compelling value proposition as channels to deliver health services. Specifically, mental health and well-being have very specific issues that need to be addressed. Most significant is the lack of access to treatment due to shortage of mental health professionals. Another reason for treatment gaps is the stigma associated with mental health issues. mHealth solutions can scale (addresses workforce shortage), are accessible (eliminates location constraints), and can provide treatment in a privacy-protected manner (addresses the stigma issue). We present two mHealth case studies, first one being a mobile stress management solution and the second one being a mobile and wearable-based cognitive analysis solution. We also discuss key concerns/challenges in creating mHealth solutions for mental health and well-being, namely, sensing and assessment, design and engagement, intervention discovery and operationalization, data privacy and security, ethics and safety, data management platforms, validation and trials, and the resulting long cycle time and adoption by the practitioner community.

Healthy living is one of the most significant things people want to achieve and sustain. There are people searching for methods and ways to pursue their lives in a healthy manner. Appreciatively, scientific and technological developments in this context bring about several notable improvements to let people live and manage their lives better regarding their health and well-being. Smartphones and smartwatches running relevant mobile health applications can be influential in this context. Well-designed and implemented mobile applications can make healthy living achievable and sustainable for most people. However, to ensure relevant accomplishment, there are numerous design considerations to be appreciated and followed. Initially, mobile health applications for various purposes and significant issues related to mobile health applications are examined in this chapter. Moreover, this chapter elaborates and discusses design considerations of mobile applications for healthy living. Particularly, a survey was applied to collect data from 245 people to conclude a number of design considerations. Accordingly, 13 key elements under three main themes are defined. Owing to that people’s views and expectations are one of the main drivers for the success of mobile health applications for intended purposes, concluded points are to be valuable for relevant product developers, people making pertinent policies, and other scholars. The main contribution of this chapter is to explore, examine, and emphasize the main elements of design considerations for mobile health applications.

Supporting adolescents’ and youths’ mental health has become a key priority, especially in Western countries. The pervasive adoption of mobile tools by the younger generations may provide a significant opportunity to increase access to services that promote mental health and well-being. Although, in recent years, several mobile applications were developed, there is limited information available about their psychological quality. In this contribution, we will review mental health apps for adolescents and young adults and assess their quality by utilizing the Evaluation Model Screener, which is a part of the American Psychiatric Association Comprehensive App Evaluation Model. Drawing on the results of this analysis, we will discuss the importance of user experience in developing mHealth tools and conclude with key considerations for the future developments of mHealth for adolescents and young adults.

Music plays a role in Tourette syndrome. In this chapter, an overview of this relationship between music, musicians, and Tourette Syndrome is presented mHealth and telehealth protocols using rhythmic auditory stimulation (RAS) are also discussed. These findings highlight the importance of studying and using music therapeutically in TS, and future research will look into this further.

Background: Despite the claimed benefits of social assistive robotics (SAR), the use of these technologies in real-life contexts to counteract older adults’ cognitive decline is still limited. In order to fill this gap, randomized controlled trials and pilot projects have recently been conducted in the field of information and communication technologies (ICT) to provide cognitive support at different stages of cognitive decline and to overcome barriers related to resource scarcity. The aim of this review is to examine the effectiveness of the newest applications in the field of social robotics in order to estimate the impact of these virtual agents to support the cognitive status. Methods: A systematic literature review was conducted, analyzing manuscripts published in the last 10 years from three databases. Results: It was shown that technology-integrated interventions can bring benefits to cognitive and psychological health when compared to usual care. Nevertheless, important questions were raised about how to maintain the benefits and durability of behavioral changes produced by short-term interventions. Social assistive robotics represents a potential solution to reduce costs, minimize the burden and training of therapists and broaden the range of clients who can benefit.

This contribution investigates the Human-Centered Design approach in the specific case of the design of the Holter Monitor device for elderly people.

After an introduction to the healthcare world and its related factors, the article illustrates all the phases involved in the research project. Starting with the analysis phase and following with the synthesis and testing steps a final concept is achieved. Results are discussed together with several reflections on the approach adopted and on elderly people.

Every year, more than one million people die from road accidents. Between 10 and 30% of these accidents are due to human factors, especially drowsiness, stress, and inattention. Determining the psychophysical condition of the driver is important to help prevent those accidents, limit damage to things and people, and even reduce the number of deaths. Today's technology is moving in the analysis of the physiological data necessary to determine these states. However, one of the major problems concerning data collection is conducting the tests in a real-world environment. For this reason, designing and employing a virtual environment that recreates a simulation of real-world’s conditions would enable researchers to obtain reliable and realistic data without putting users at risk. The paper describes the development and validation of a configurable and scalable virtual environment, conceived to help researchers to set up the environment freely according to their research needs. The in-depth analysis explored a normal and an altered environmental condition to investigate and assess the negative parameters responsible for increasing driving inattention. Finally, the outcomes have become the first experimentation to create an AI-based simulator for diagnosing the driver's state of health.