A5088832785- Prosthetics and Rehabilitation Robotics
- Muscle activation and electromyography studies
- Advanced Sensor and Energy Harvesting Materials
- Healthcare Policy and Management
- Hand Gesture Recognition Systems
- Statistical Methods and Inference
- Robot Manipulation and Learning
- Robotic Locomotion and Control
- Ultrasonics and Acoustic Wave Propagation
- Hydraulic and Pneumatic Systems
- Structural Health Monitoring Techniques
- Probability and Risk Models
Korea Advanced Institute of Science and Technology
2021-2024
Hand gesture recognition has received considerable attention as an intuitive interaction method in recent years. This research introduces a new wearable hand system that employs pneumatic mechanomyography (pMMG) to directly monitor the wrist tendon group, which transmits muscle force fingers. The experimental findings demonstrate proposed provides raw observations proportional finger flexion force, with high <italic xmlns:mml="http://www.w3.org/1998/Math/MathML"...
In many research areas, such as biomedical engineering, rehabilitation medicine, and sports science, electromyography (EMG) is used a key indicator of muscle activity. While EMG provides information about active activation, it does not provide on passive activation. Muscle contraction the result actuation. contractions are directly related to strength general understanding performance. this paper, real-time observation method using pneumatic myography (pMMG) introduced. A modular system was...
Many robotic applications that physically interact with humans require the measurement of interaction forces to ensure accurate control as well safety. Devices are directly attached human body, such wearable devices, must use soft and flexible materials be comfortable safe. Most sensors cannot measure large amounts force because can easily deform break when subjected forces. In this paper, we present a unit (sFMU) three-axis force. The proposed sFMU is made three polyurethane air sacs...
Seongbin An, Trang Doan, Juhee Lee, Jiwoo Kim, Yong Jae Yunji Changwon Yoon, Sungkyu Jung, Dongha Sunghoon Kwon, Hang J Jeongyoun Ahn, Cheolwoo Park. Korean Appl Stat 2023;36:141-66. https://doi.org/10.5351/KJAS.2023.36.2.141