Deep learning for robotics examples using OpenDR

Kirtas, Manos; Tsampazis, Konstantinos; Tosidis, Pavlos; Passalis, Nikolaos; Tefas, Anastasios

doi:10.1016/b978-0-32-385787-1.00026-9

Cited by 1 publication

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…47 Neural networks used by DL are trained end-to-end to make the challenges easier to solve, but sometimes, such techniques are not considered user-friendly due to their steep learning curves. 48 Additionally, several domain-specific restrictions are hindering the widespread adoption of deep learning in various industries.…”

Section: Preliminary To Artificial Intelligencementioning

confidence: 99%

Impact of AI-Powered Solutions in Rehabilitation Process: Recent Improvements and Future Trends

Khalid,

Naeem,

Stasolla

et al. 2024

IJGM

View full text Add to dashboard Cite

Rehabilitation is an important and necessary part of local and global healthcare services along with treatment and palliative care, prevention of disease, and promotion of good health. The rehabilitation process helps older and young adults even children to become as independent as possible in activities of daily life and enables participation in useful living activities, recreation, work, and education. The technology of Artificial Intelligence (AI) has evolved significantly in recent years. Many activities related to rehabilitation have been getting benefits from using AI techniques. The objective of this review study is to explore the advantages of AI for rehabilitation and how AI is impacting the rehabilitation process. This study aims at the most critical aspects of the rehabilitation process that could potentially take advantage of AI techniques including personalized rehabilitation apps, rehabilitation through assistance, rehabilitation for neurological disorders, rehabilitation for developmental disorders, virtual reality rehabilitation, rehabilitation of neurodegenerative diseases and Telerehabilitation of Cardiovascular. We presented a survey on the newest empirical studies available in the literature including the AI-based technology helpful in the Rehabilitation process. The novelty feature included but was not limited to an overview of the technological solutions useful in rehabilitation. Seven different categories were identified. Illustrative examples of practical applications were detailed. Implications of the findings for both research and practice were critically discussed. Most of the AI applications in these rehabilitation types are in their infancy and continue to grow while exploring new opportunities. Therefore, we investigate the role of AI technology in rehabilitation processes. In addition, we do statistical analysis of the selected studies to highlight the significance of this review work. In the end, we also present a discussion on some challenges, and future research directions.

show abstract

Section: Preliminary To Artificial Intelligencementioning

confidence: 99%