2023 Fiscal Year Final Research Report
Estimation of human motion intentions using high density EMG signals
| Project/Area Number |
21K18105
|
|---|
| Research Category |
Grant-in-Aid for Early-Career Scientists
|
| Allocation Type | Multi-year Fund |
|---|
| Review Section |
Basic Section 90150:Medical assistive technology-related
|
|---|
| Research Institution | Kyushu University |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2021-04-01 – 2024-03-31
|
| Keywords | Wearable Robotics / Rehabilitation / Esoskeleton |
|---|
| Outline of Final Research Achievements |
In wearable robotic systems like exoskeletons and prostheses, capturing the motion intention of their wearer is crucial for intuitive control to supplement or support the intended motion. In this study, high-density electromyography (HDEMG) was utilized as a biological signal to extract human motion intention, focusing on a prosthetic hand user. The human hand possesses a higher number of degrees of freedom (DOFs). However, conventional muscle signal measurement and analysis techniques are inadequate to provide sufficient information related to this higher number of DOFs. This study demonstrated that variations in spatial activations of human muscles, measured with HDEMG can offer adequate information to estimate motion intention for higher DOFs with higher accuracy in real-time. Initially, the spatial information of the human muscles was mapped into heatmaps. Later, corresponding information related to the spatial changes in the heatmaps over time was used to estimate intended motion.
|
| Free Research Field |
Medical Robotics
|
| Academic Significance and Societal Importance of the Research Achievements |
This study will provide insights into how enough information related to multi DOFs of human moiton can be extracted from HDEMG for motion intention estimation, considering the spatial variations of the muscle activations. This will help to improve the quality of life of wearable robotic users.
|
