Abstract
Understanding the main factors that can compromise or improve the efficacy of home-based rehabilitation on the perspective of technology requires the review of the features of the equipment used in this area, both in terms of hardware and software. The purpose of this paper is to summarize the most recent technologies implemented into home-based rehabilitation scenario, namely wearable devices, robotic end-effectors, exoskeletons, and the role of artificial intelligence amongst these fields. Evidence is presented to better understand the present state of art of home-based rehabilitation systems, facilitating the exploration of hypothetical healthcare uses for these systems or their possible future upgrades.
TopIntroduction
Home-based rehabilitation has been described as an alternative or complementary approach to care-unit based therapy, by promoting patients’ independence in different health conditions and/or by helping patients to fully or partially recover the ability to perform their previous tasks and return to a normal lifestyle (Gelaw et al. 2020). Several benefits can be achieved with home-based rehabilitation, for both patients and healthcare organizations, namely: monetary costs, by reducing hospital stay and bed occupation (Chen et al. 2019), and facilitating the migration from an inpatient to an outpatient approach (Stenberg et al. 2018); reduction of time spent traveling; and appointment scheduling and therapist’s quickness to give feedback (Chen et al. 2019). High-quality healthcare is directly associated with the probability of attaining an expected positive outcome, being dependent not only on the professional’s skills and knowledge, but also on available medical devices (Sfantou et al. 2017). In recent years, the transition of some medical devices and services from the hospital to the home environment, and the rising of new ones has been possible due to advances in e-health, remote monitoring technologies, and encouragement of self-management (Bitterman 2011). The provision of high-quality healthcare in home-based rehabilitation scenarios can be facilitated by the combination of multiple technologies that complement one another with distinct functionalities (Chae et al. 2020). Figure 1 summarizes the types of medical devices and technologies addressed in this article and their respective subtypes.
Figure 1. Different technologies used in home-based rehabilitation
This chapter aims to provide insight into recent literature regarding the technologies used in home-based rehabilitation, ranging from wearable devices to exoskeletons and assistant robots, passing throw some of the most used Artificial Intelligence (AI) algorithms and their main healthcare-related goals. By doing so, a deeper understanding can be reached, regarding the impact and paradigm shifts that these technologies can potentially have in the present and future of society. To address this purpose, this chapter is organized into 6 sections. After the “Introduction”, the “Background” section presents the problem statement. The “Home-Based Rehabilitation Systems” section presents the state of the art regarding the different technologies mentioned in Figure 1. Specifically, this section is divided into 2 subsections, one dedicated to the wearable devices and the other to the various AI branches, facilitating the search for specific information regarding the features of the home-based rehabilitation systems, as well support future research. The “Future Research Directions” section presents some of the author’s perspectives concerning the future developments of home-based therapy and its associated technologies. Lastly, in the “Conclusion” section are presented the main considerations that can be gathered from the subjects presented in this chapter.
Key Terms in this Chapter
End-Effectors: Robots or robotic parts that interact with the environment.
Healthcare: Efforts performed by skilled and certified experts to maintain or restore physical, mental, or emotional well-being.
Physical Rehabilitation: therapy for the conservation, improvement, or restoration of movements and physical functions of an individual weakened by a disease, injury, or disability.
Machine Learning: The application and development of computer systems that can learn and adapt themselves by analyzing and drawing inferences from data patterns, utilizing algorithms and statistical models, without explicit human instructions.
Wearable Devices: electrical components and software-controlled goods that can be incorporated into garments or worn on the body as accessories to extract biological and/or environmental data.
Exoskeletons: Mechanical devices attached to a person’s body for either physical strength augmentation or motion support.
Internet of Things: Interconnection between electronic devices used on a daily basis, enabling them to send and receive data through the internet.
Deep Learning: A subgroup of machine learning, essentially composed of algorithms that use a neural network with three or more layers together with large amounts of data, attempting to simulate the learning capabilities of the human brain.