Individualised Responsible Artificial Intelligence for Home-Based Rehabilitation

Telerehabilitation: lessons from the COVID-19 pandemic and future perspectives

The coronavirus disease 2019 (COVID-19) pandemic has had an enormous effect on healthcare, notably rehabilitation for neurological, rheumatological, musculoskeletal, and cognitive diseases. Telerehabilitation provides rehabilitation services via multiple modalities, such as real-time chats, computerized consultations, and distant evaluations, emphasizing assessment, diagnosis, and intervention. While the use of telerehabilitation had restrictions before COVID-19, regulatory changes have accelerated its adoption, broadening therapy provision beyond traditional healthcare settings. Telerehabilitation has been examined for its effectiveness in a variety of health concerns, including stroke, traumatic brain injury, Parkinson's disease, musculoskeletal disorders, and rheumatic diseases. Despite the constraints of the COVID-19 environment, telerehabilitation settings, which include patient and therapist aspects, have emerged to ensure optimal treatment delivery. Key themes include home-based rehabilitation initiatives, wearable gadgets, and the integration of analytics and artificial intelligence. The growing acceptance of telehealth and telerehabilitation is expected to drive further progress in this discipline.

Technologies in Home-Based Digital Rehabilitation: Scoping Review

BACKGROUND

Due to growing pressure on the health care system, a shift in rehabilitation to home settings is essential. However, efficient support for home-based rehabilitation is lacking. The COVID-19 pandemic has further exacerbated these challenges and has affected individuals and health care professionals during rehabilitation. Digital rehabilitation (DR) could support home-based rehabilitation. To develop and implement DR solutions that meet clients' needs and ease the growing pressure on the health care system, it is necessary to provide an overview of existing, relevant, and future solutions shaping the constantly evolving market of technologies for home-based DR.

OBJECTIVE

In this scoping review, we aimed to identify digital technologies for home-based DR, predict new or emerging DR trends, and report on the influences of the COVID-19 pandemic on DR.

METHODS

The scoping review followed the framework of Arksey and O'Malley, with improvements made by Levac et al. A literature search was performed in PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library. The search spanned January 2015 to January 2022. A bibliometric analysis was performed to provide an overview of the included references, and a co-occurrence analysis identified the technologies for home-based DR. A full-text analysis of all included reviews filtered the trends for home-based DR. A gray literature search supplemented the results of the review analysis and revealed the influences of the COVID-19 pandemic on the development of DR.

RESULTS

A total of 2437 records were included in the bibliometric analysis and 95 in the full-text analysis, and 40 records were included as a result of the gray literature search. Sensors, robotic devices, gamification, virtual and augmented reality, and digital and mobile apps are already used in home-based DR; however, artificial intelligence and machine learning, exoskeletons, and digital and mobile apps represent new and emerging trends. Advantages and disadvantages were displayed for all technologies. The COVID-19 pandemic has led to an increased use of digital technologies as remote approaches but has not led to the development of new technologies.

CONCLUSIONS

Multiple tools are available and implemented for home-based DR; however, some technologies face limitations in the application of home-based rehabilitation. However, artificial intelligence and machine learning could be instrumental in redesigning rehabilitation and addressing future challenges of the health care system, and the rehabilitation sector in particular. The results show the need for feasible and effective approaches to implement DR that meet clients' needs and adhere to framework conditions, regardless of exceptional situations such as the COVID-19 pandemic.

Artificial Intelligence in Musculoskeletal Conditions

Artificial intelligence (AI) refers to computer capabilities that resemble human intelligence. AI implies the ability to learn and perform tasks that have not been specifically programmed. Moreover, it is an iterative process involving the ability of computerized systems to capture information, transform it into knowledge, and process it to produce adaptive changes in the environment. A large labeled database is needed to train the AI system and generate a robust algorithm. Otherwise, the algorithm cannot be applied in a generalized way. AI can facilitate the interpretation and acquisition of radiological images. In addition, it can facilitate the detection of trauma injuries and assist in orthopedic and rehabilitative processes. The applications of AI in musculoskeletal conditions are promising and are likely to have a significant impact on the future management of these patients.

Lost in translation? Conceptions of privacy and independence in the technical development of AI-based AAL

AAL encompasses smart home technologies that are installed in the personal living environment in order to support older, disabled, as well as chronically ill people with the goal of delaying or reducing their need for nursing care in a care facility. Artificial intelligence (AI) is seen as an important tool for assisting the target group in their daily lives. A literature search and qualitative content analysis of 255 articles from computer science and engineering was conducted to explore the usage of ethical concepts. From an ethical point of view, the concept of independence and self-determination on the one hand and the possible loss of privacy on the other hand are widely discussed in the context of AAL. These concepts are adopted by the technical discourse in the sense that independence, self-determination and privacy are recognized as important values. Nevertheless, our research shows that these concepts have different usages and meanings in the ethical and the technical discourses. In the paper, we aim to map the different meanings of independence, self-determination and privacy as they can be found in the context of technological research on AI-based AAL systems. It investigates the interpretation of these ethical and social concepts which technicians try to build into AAL systems. In a second step, these interpretations are contextualized with concepts from the ethical discourse on AI-based assistive technologies.

Rehabilitation in long COVID-19: A mini-review

We have been experiencing multiple waves of the coronavirus disease 2019 (COVID-19) pandemic. With these unprecedented waves, we have entered into an era of ‘new normal’. This pandemic has enforced us to rethink the very basics of childhood learning: Habits, health etiquette, and hygiene. Rehabilitation has immense importance during this pandemic considering a few aspects. Multidisciplinary COVID-19 rehabilitation clinics are essential to address the demand. The equitable distribution of COVID-19 rehabilitation services for differently-abled individuals during the pandemic is an important aspect. Rehabilitation needs identification and further studies on various rehabilitation interventions are among the key unmet future research needs.