Biomechanics, Sensing and Bio-inspired Control in Rehabilitation and Assistive Robotics, Volume II

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About this Research Topic

Submission deadlines

  1. Manuscript Submission Deadline 31 January 2025

  2. This Research Topic is still accepting articles.

Background

This Research Topic is Volume II of a series. The previous volume, which has attracted over 22k views can be found here: Biomechanics, Sensing and Bio-inspired Control in Rehabilitation and Wearable Robotics

The research on rehabilitation and assistive devices has several key challenges such as limited applicability, lack of user feedback, and the absence of effective health monitoring. Biomechanics, sensing, and bio-inspired control are interdisciplinary fields that have made significant advances in recent years in the area of rehabilitation and assistive robotics. They integrate principles from biology, mechanics, and engineering to develop robotic systems that can assist or rehabilitate individuals with disabilities or those recovering from injuries. Biomechanics focuses on understanding the mechanical characteristics of how the human body interacts with the environment. Sensing technologies are integrated into these systems to provide real-time feedback and adaptation. These technologies enable the robots to "sense" the user's movements and respond accordingly. Bio-inspired control strategies draw inspiration from how biological systems operate, incorporating concepts such as adaptability, learning, and self-regulation into robotic control systems. These strategies aim to make rehabilitation and assistive robots more autonomous and capable of interacting seamlessly with humans.

Biomechanics, Sensing, and Bio-inspired Control in Rehabilitation and Assistive Robotics is a multidisciplinary topic focused on enhancing the functionality and user experience of rehabilitation and assistive technologies through integrating biology and robotics. This topic aims to provide tailored support for individuals with disabilities or during rehabilitation, promoting faster recovery and improved motor function. By utilizing biosensors to gather real-time data on user movements and physiological states, these robotic systems can dynamically adjust to the user's needs, enhance operational efficiency, and ensure safety. The incorporation of bio-inspired control enables the robots to replicate natural movements and adapt to user preferences. The ultimate goal of the research topic is to advance the development of more responsive, personalized, and effective rehabilitation and assistive devices, thereby improving the overall quality of life for individuals with disabilities or health conditions.

Submitted manuscripts on this topic should be original research on theories, methodologies, or clinical applications in bioengineering and biotechnology that contribute to the development of rehabilitation and assistive robotics. The scope of the topic includes, but is not limited to:
1. Biomechanical studies in rehabilitation and assistive robotics.
2. Advanced design or application of biosensors.
3. Acquisition, processing, or analysis of bioinformation in rehabilitation and assistive robotics.
4. Theoretical research or applications of bioinformation in rehabilitation outcomes, user health monitoring, and intention recognition.
5. Human-machine interaction in rehabilitation and assistive robotics.
6. Applications of machine learning and artificial intelligence in rehabilitation and assistive technologies.
7. Case studies demonstrating the impact of biomechanics and sensing in rehabilitation and assistive technologies.

Article types and fees

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

  • Brief Research Report
  • Case Report
  • Data Report
  • Editorial
  • General Commentary
  • Hypothesis and Theory
  • Methods
  • Mini Review
  • Opinion

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Keywords: biomechanics, biosensors, intelligent sensing, human-machine interaction, intention recognition, biologically inspired robots, assistance devices, rehabilitation robots

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