Over the last decade, many studies have proposed and tested a variety of robot-assisted therapeutic interventions. A shared motivation behind these approaches is providing effective and low-cost functional recovery after a neurological impairment. However, the reported results are highly variable, indicating that, among other factors, there is a need for a more in-depth understanding and quantification of the neuromechanical processes involved in robot-mediated therapy. Motor performance can now be assessed in a variety of levels, from the kinematic and dynamic behavior of movement to the evaluation of neurophysiological biomarkers. Recent breakthroughs in electromyography (EMG) signal processing techniques, such as the introduction of high-density EMG, have broken new ground in our understanding of motor control all the way down to the motor unit level. While there is still room for improvement, further development of these techniques could be useful in terms of increasing knowledge on human behavior and in developing more advanced human-inspired assistive technologies. The evaluation of the performance of robot-assisted rehabilitation is a critical tool to adapt the therapy to the particular conditions and needs of the patient. Time is ripe for the combination of computational and sensing technologies to lead to the identification of new neuromechanical biomarkers that will help develop safer and standard rehabilitation therapies, track their effectiveness and enable researchers to gain a deeper understanding of the robot-assisted rehabilitation process as a whole.
This Research Topic aims to address the application of neuromechanical biomarkers for evaluation of motor function recovery during robot-assisted therapies and their use as a tool to readapt motor rehabilitation therapy to increase its effectiveness.
Authors are encouraged to submit innovative research articles that cover topics ranging from the application of electrophysiological and neuromechanical analysis of motor function to the evaluation of robot-assisted approaches to rehabilitation. Research that considers assessment techniques in clinical rehabilitation is particularly encouraged. Review articles that describe the current state of the art are also welcome.
Potential topics include but are not limited to the following:
? (High-density) EMG approaches for the extraction of biomarkers in robot-assisted rehabilitation
? Modeling of robot actuation from neuromechanical biomarkers
? Musculoskeletal modeling of human motion applied to robot-assisted rehabilitation
? Electrophysiology of motor learning and motor recovery during robot-assisted rehabilitation
? Robot performance metrics in robot-assisted rehabilitation activities
? Human performance metrics in robot-assisted rehabilitation activities
? Application of biomarkers to readapt rehabilitation therapies
? Correlation between biomarkers and conventional clinical metrics
? Bioinspired robotic devices applied to motor rehabilitation
Over the last decade, many studies have proposed and tested a variety of robot-assisted therapeutic interventions. A shared motivation behind these approaches is providing effective and low-cost functional recovery after a neurological impairment. However, the reported results are highly variable, indicating that, among other factors, there is a need for a more in-depth understanding and quantification of the neuromechanical processes involved in robot-mediated therapy. Motor performance can now be assessed in a variety of levels, from the kinematic and dynamic behavior of movement to the evaluation of neurophysiological biomarkers. Recent breakthroughs in electromyography (EMG) signal processing techniques, such as the introduction of high-density EMG, have broken new ground in our understanding of motor control all the way down to the motor unit level. While there is still room for improvement, further development of these techniques could be useful in terms of increasing knowledge on human behavior and in developing more advanced human-inspired assistive technologies. The evaluation of the performance of robot-assisted rehabilitation is a critical tool to adapt the therapy to the particular conditions and needs of the patient. Time is ripe for the combination of computational and sensing technologies to lead to the identification of new neuromechanical biomarkers that will help develop safer and standard rehabilitation therapies, track their effectiveness and enable researchers to gain a deeper understanding of the robot-assisted rehabilitation process as a whole.
This Research Topic aims to address the application of neuromechanical biomarkers for evaluation of motor function recovery during robot-assisted therapies and their use as a tool to readapt motor rehabilitation therapy to increase its effectiveness.
Authors are encouraged to submit innovative research articles that cover topics ranging from the application of electrophysiological and neuromechanical analysis of motor function to the evaluation of robot-assisted approaches to rehabilitation. Research that considers assessment techniques in clinical rehabilitation is particularly encouraged. Review articles that describe the current state of the art are also welcome.
Potential topics include but are not limited to the following:
? (High-density) EMG approaches for the extraction of biomarkers in robot-assisted rehabilitation
? Modeling of robot actuation from neuromechanical biomarkers
? Musculoskeletal modeling of human motion applied to robot-assisted rehabilitation
? Electrophysiology of motor learning and motor recovery during robot-assisted rehabilitation
? Robot performance metrics in robot-assisted rehabilitation activities
? Human performance metrics in robot-assisted rehabilitation activities
? Application of biomarkers to readapt rehabilitation therapies
? Correlation between biomarkers and conventional clinical metrics
? Bioinspired robotic devices applied to motor rehabilitation
