TY - JOUR
T1 - Technologies in Home-Based Digital Rehabilitation
T2 - Scoping Review
AU - Arntz, Angela
AU - Weber, Franziska
AU - Handgraaf, Marietta
AU - Lällä, Kaisa
AU - Korniloff, Katariina
AU - Murtonen, Kari Pekka
AU - Chichaeva, Julija
AU - Kidritsch, Anita
AU - Heller, Mario
AU - Sakellari, Evanthia
AU - Athanasopoulou, Christina
AU - Lagiou, Areti
AU - Tzonichaki, Ioanna
AU - Salinas, Iosune
AU - Martínez-Bueso, Pau
AU - Velasco-Roldán, Olga
AU - Schulz, Ralf Joachim
AU - Grüneberg, Christian
N1 - Publisher Copyright:
© Angela Arntz, Franziska Weber, Marietta Handgraaf, Kaisa Lällä, Katariina Korniloff, Kari-Pekka Murtonen, Julija Chichaeva, Anita Kidritsch, Mario Heller, Evanthia Sakellari, Christina Athanasopoulou, Areti Lagiou, Ioanna Tzonichaki, Iosune Salinas-Bueno, Pau Martínez-Bueso, Olga Velasco-Roldán, Ralf-Joachim Schulz, Christian Grüneberg.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - AI
KW - artificial intelligence
KW - COVID-19 pandemic
KW - digital health intervention
KW - digital rehabilitation
KW - digital technologies
KW - home-based rehabilitation
KW - machine learning
KW - mobile app
KW - mobile phone
KW - remote health
KW - scoping review
UR - http://www.scopus.com/inward/record.url?scp=85167728182&partnerID=8YFLogxK
U2 - 10.2196/43615
DO - 10.2196/43615
M3 - Article
AN - SCOPUS:85167728182
VL - 10
JO - JMIR Rehabilitation and Assistive Technologies
JF - JMIR Rehabilitation and Assistive Technologies
M1 - e43615
ER -