Enhancing Gait Therapy with Artificial Intelligence: Current Trends and Future Prospects

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About this Research Topic

This Research Topic is still accepting articles.

Background

Gait rehabilitation is a crucial intervention aimed at enhancing or restoring walking abilities in those suffering from injuries, surgeries, neurological disorders, or chronic conditions. These conditions typically result in muscle weakness, spasticity, and other challenges that complicate mobility and daily life. In addition to restoring normal walking patterns, effective gait therapy enhances balance, prevents falls, and improves overall functionality, significantly boosting the patient's quality of life. Recent advancements have seen artificial intelligence (AI) reshape this field with sophisticated algorithms that personalize and optimize therapeutic interventions through precise analysis and real-time feedback, utilizing data from wearable sensors and various monitoring devices.

This Research Topic seeks to delve into the transformative impact of AI on gait rehabilitation with the objective of advancing therapeutic outcomes. It aims to explore how AI-enabled technologies can dynamically adjust rehabilitation plans to improve balance, restore normal walking patterns, prevent future falls, and enhance the overall functional capability of individuals facing mobility restrictions.

Investigations will focus on the incorporation and effectiveness of AI within gait rehabilitation regimes. We invite contributions that cover, but are not limited to, the following themes:
- Development and application of wearable sensors for real-time gait monitoring.
- Predictive modelling for rehabilitation outcomes and patient progress.
- Personalized AI-driven rehabilitation protocols.
- AI-enhanced robotic aids such as exoskeletons and prosthetics.
- Adaptive control systems for personalized gait assistance.
- Virtual and augmented reality solutions for immersive rehabilitation experiences.
- AI-based tele-rehabilitation platforms for distant monitoring and intervention.
- Practical implementations in diverse clinical environments.
- Ethical considerations in the deployment of AI technologies in rehabilitation, focusing on patient privacy and data security.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

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  • Clinical Trial
  • Community Case Study
  • Conceptual Analysis
  • Data Report
  • Editorial
  • FAIR² Data
  • FAIR² DATA Direct Submission
  • General Commentary

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Keywords: Gait Analysis, Machine Learning, Biomechanics, Robotic Therapy, Rehabilitation Robotics

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Manuscripts can be submitted to this Research Topic via the main journal or any other participating journal.

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