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Device Technologies and Biomedical Robotics

Device Technologies and Biomedical Robotics - Poster Session D

Poster W12 - A wearable patch system with integrated EMG sensor and motion marker for precise rehabilitation and guided sports training

Friday, October 25, 2024

3:30 PM - 4:30 PM EST

Location: Exhibit Hall E, F & G

Presenting Author(s)

Bohyung Choi

Master's student
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
Daejeon, United States

Co-Author(s)

KL

Kun-Do Lee

Ph.D. Student
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, United States
YJ

Yoo-jin Jun

Ph.D. Student
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, United States
HK

Heesoo Kim, MS

Ph.D. Student
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, United States
HC

Heewon Choee

Ph.D. Student
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, United States
Choong yeon Kim, PhD

Post-Doc.
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, United States
MJ

Minkyu Je

Professor
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, United States
HP

Hyung-Soon Park

Professor
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, United States

Last Author(s)

JJ

Jae-Woong Jeong

Professor
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, United States

Introduction: Currently, three out of five adults aged 50-80 suffer from arthritis and joint pain. Rehabilitation has faced increasing needs with the aging society due to the declining mortality rate, accompanied by recent advances in healthcare and social welfare. In response, recent advances in digital healthcare have led to the development of sports monitoring and feedback systems. Nonetheless, current rehabilitation protocols necessitate frequent visits to physical therapy clinics, posing challenges for the older population.
Some digital healthcare systems try to provide remote exercise, which can be done at home. However, these systems lack precise exercise analysis and guidance because they only monitor body movement without considering target muscle activation. To address this challenge, we present a novel wireless wearable feedback system that can simultaneously capture both joint movement and muscle activation, providing highly effective rehabilitation and sports training. Our system utilizes an electromyography (EMG)-sensor-integrated sports tape featuring specialized motion markers on the exterior. This system allows simultaneous monitoring of EMG signals and motion angles by wearing a simple patch in the form of sports tape (Fig. 1). With the help of our device, patients can complete recommended workouts in the comfort of their own homes while receiving real-time feedback on joint angles and muscle activation. This dual-faceted feedback ensures proper posture and prevents injury during exercise. Therefore, this easy-to-wear wireless system can be used not just for rehabilitation exercises but also for other applications requiring precise movement analysis and feedback.

Materials and

Methods: Our wearable patch is in the form of sports tape with EMG sensors on the interior and printed motion markers on the exterior. EMG sensors, made of Electrically Conductive Adhesive (ECA) electrodes, comprise Ag flakes (4-8 μm) and silicone gel, achieving high stretchability, conductivity, and adhesion (Figs. 2a-c). The ECA electrodes have a porous pattern to enhance skin breathability and are designed to contact the target leg muscles conformally. Interconnects are designed in a stretchable pattern (100 μm-thick), seamlessly linking ECA electrodes to the EMG measurement circuit, connected via magnetic connectors that align automatically with alternating polarity (Figs. 2d and e). The wireless EMG sensing circuit is encapsulated with silicone, where the flexible circuit is placed at the neutral mechanical plane of the soft-packaged unit. The circuit measures EMG signals from ECA electrodes and sends them to the PC via Bluetooth. Simultaneously, two Realsense D435 (RGBD) cameras capture the image of motion markers and estimate the abduction/adduction of the leg. The combined data from these sources are used to generate customized, meaningful feedback.
The mechanical robustness and stretchability of the wearable patch were both verified with mechanical stretching and resistance measurement while stretching the device. The porous pattern design of ECA electrodes was verified under ASTM E96-95 standards. Our device was tested in a rehabilitation exercise program. A person wearing our device was asked to perform a series of exercises and was trained with real-time written feedback. The effect of feedback was verified with subjective pain assessment.

Results, Conclusions, and Discussions: We have studied mechanical and electrical characteristics and performance of the wearable patch system with EMG and motion sensing capabilities. The patch can easily stretch more than 30% to adapt to the dynamic tissue formation of the user and exhibit only a 9.2% change in resistance when stretched 30%. Thanks to porous patterns (diameter = 500 μm) in the EMG electrodes, the patch showed excellent water vapor permeability (10.92 g·hour−1 ·m−2) according to measurements based on ASTM E96-95 standards, which falls within the range of transepidermal water loss in human skin (5 to 10 g·hour−1·m−2) (Fig. 3).
In addition, we verified that our system is capable of providing real-time feedback based on the motion angles captured by two RGBD cameras and EMG signals sent from the measurement circuit. While a subject wearing our wearable patches on both sides of the thigh and calf is performing single-leg-squat or double-leg-squat for a given period of time, real-time feedback was successfully generated through the multi-faceted signals (Figs. 4a and b). The feedback was given based on the combination of the ratio of EMG signals from leg muscles and the flexion, abduction, and rotation estimated from the motion angle. Based on the observation of abduction of legs, the feedback “stand wider” is generated, while the ratio of gastrocnemius muscle/tibialis anterior muscle activation reaching a certain limit triggers the message “move your knees slightly forward and focus on frontal calf muscle” (Fig. 4c).
We envision that this wearable patch system with EMG and motion sensing capabilities will have a practical impact not only on rehabilitation exercises but also on rigorous fitness routines and sports training. The system's ability to provide real-time, customized feedback based on detailed EMG and motion data holds promise for enhancing the effectiveness and safety of exercise programs. By integrating advanced sensing capabilities with user-friendly design, the wearable system can revolutionize the way we approach physical training and rehabilitation.

Acknowledgements (Optional): This work was supported by the LGE-KAIST Digital Healthcare Research Center grant funded by LG Electronics (LGE).