July 25, 2024

New Technology for Robotic Prosthetic Leg Control Developed by Research Team

A research team led by Professor Sang-hoon Lee at the Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST) has developed a groundbreaking imperceptive surface electromyography (sEMG) sensor. This sensor plays a crucial role in enabling lower limb amputees to control robotic prosthetic legs as they desire, thereby contributing significantly to rehabilitation and an improved quality of life.

In recent years, there has been a significant increase in the number of lower limb amputees, largely due to the rise in lifestyle diseases such as diabetes. The permanent consequences of lower limb amputation extend beyond physical disability and often result in psychological challenges. To address this issue, researchers have been developing bionic lower limb technology to replace lost legs with robotic prosthetics.

The key to successfully developing robotic prosthetic legs lies in effectively implementing lower limb functionality, as intended by amputees. To do so, the ability to rapidly and accurately capture the biological signals of amputees is essential. The most suitable method for this is through the use of non-invasive sEMG sensors. However, the practical application of these sensors has proven to be a challenge.

The sensor must be placed inside the silicone liner of the socket to record electromyographic signals. However, the narrow dimensions of the silicone liner create a humid environment and make it susceptible to the strong dynamic movements of the socket caused by the weight of the robotic prosthetic leg. As a result, it is impossible to consistently record the biological signals of muscles over an extended period without damaging the sensor itself.

In response to this issue, the research team at DGIST, led by Professor Sang-hoon Lee, has developed an imperceptive sEMG sensor using a microelectromechanical system. Published in the journal npj Flexible Electronics, the team’s study describes the sensor’s unique structure, resembling a serpentine structure, which provides flexibility, elasticity, breathability, and adhesion. These properties allow the sensor to be applied to various amputated body parts and used repeatedly over an extended period of time. Additionally, when combined with a wireless module, the sensor captures real-time signals generated when amputees walk with robotic prosthetic limbs, sockets, and silicone liners.

To validate the sensor’s functionality, the research team attached the imperceptive sEMG sensor to a lower limb amputee and recorded the amputee’s muscle signals. The results demonstrated that the sensor successfully acquired high-quality real-time muscle signals while the amputee walked in different environments such as flat ground, slopes, and stairs. These signals were wirelessly transmitted to assist the amputee in walking, as verified by the motion analysis sensor embedded in the robotic prosthetic leg.

Furthermore, through the analysis of muscle signals generated during plantar flexion and dorsiflexion in amputees, the team confirmed that the imperceptive sEMG sensor has better selective signal acquisition performance compared to other commercial sensors. Consequently, the team anticipates that this sensor can be applied to various wearable technologies, in addition to enabling precise control of robotic prosthetic legs and hands based on bio-signals.

Professor Lee emphasized the significant impact of this research, stating, “Although there are more amputees in Korea and around the world than we realize, their daily activities and quality of life are often restricted due to the unavailability of prosthetic legs that can be controlled as intended by the wearer. Based on the findings of this research, we will continue to conduct further studies and ultimately develop bionic limbs that can replicate the sensory and motor functions of human limbs, allowing amputees to enjoy all daily activities.”

 

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1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it