Deadline Date: 15 February 2022. 

Please submit your research article, review article or position paper through manuscript central and select the “Wearable Ultrasound Sensors for Robotic Prosthesis and Exoskeletons” special issue.

Wearable Ultrasound Sensors for Robotic Prosthesis and Exoskeletons

Assistive robots such as powered exoskeletons and robotic prosthesis have enabled new possibilities for function restoration among people with spinal cord injury, stroke, amputation, and other neurological conditions that cause gait disorders. Yet, the assistive robots amiss a symbiotic interaction between the exoskeleton and a human. Due to technical challenges with popular sensing methods such as electromyography, sensors that accurately measure human intent through muscle state monitoring are needed. Ultrasound due to its ability to directly visualize muscle activity is an emerging sensing technology for assistive robotic control. Recent studies showed its potential to control a robotic prosthesis, functional electrical stimulation, and an exoskeleton. Ultrasound-based sensors would enable high performance robotic prostheses and exoskeletons that coordinate their actions with the human user and maintain harmonious and stable human-robot interaction. Despite its potential, challenges remain to translate the ultrasound technology to clinics. These challenges include design and fabrication of wearable ultrasound sensors, development of real-time algorithms for processing ultrasound-derived data and closing the loop with ultrasound sensors.

We welcome contributions on the following topics

• Deploying novel ultrasound sensing/imaging technologies during control of functional electrical stimulation, prosthesis, or exoskeleton
• Wearable ultrasound sensors/transducers for monitoring muscle state and measure human effort
• Design, fabrication, and characterization of wearable ultrasound sensors/transducers
• Machine learning algorithms for classifying ultrasound-derived signals
• Real-time processing of ultrasound radio frequency data
• Merging/fusing ultrasound imaging-derived signals with electromyography, kinematic sensors, etc.
• Integration of wearable ultrasound sensors in closed loop algorithms

Guest Editors

Nitin Sharma, Associate Professor, North Carolina State University (USA)

Xiaoning Jiang, Dean F. Duncan Distinguished Professor, North Carolina State University (USA)

Siddhartha Sikdar, Professor, George Mason University (USA)

Yuu Ono, Associate Professor, Carleton University (Canada)

Honghai Liu, Professor, University of Portsmouth (UK)