.png){kind=icon}
返回
Explainable and Robust Deep Forests for EMG-Force Modeling
.png){kind=icon}
OA
AI
DOI：10.1109/JBHI.2023.3262316.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Machine and deep learning techniques have received increasing attentions in estimating finger forces from high-density surface electromyography (HDsEMG), especially for neural interfacing. However, most machine learning models are normally employed as block-box modules. Additionally, most previous models suffer from performance degradation when dealing with noisy signals. In this work, we propose to employ a forest ensemble model for HDsEMG-force modeling. Our model is explainable and robust against noise. Additionally, we explored the effect of increasing the depth of forest models in EMG-force modeling problems. We evaluated the performance of deep forests with a finger force estimation task. Training and testing data were acquired 3-25 days apart, approximating realistic scenarios. Results showed that deep forests significantly outperformed other models. With artificial signal distortion in 20% channels, deep forests also showed a higher robustness, with the error reduced from that of the baseline by >50% compared with all other models. We provided explanations for the proposed model using the mean decrease impurity (MDI) metric, revealing a strong correspondence between the model and physiology.
Keyword:
EMG-force modeling
electromyography
myoelectric control
deep learning
deep forest
期刊
IF:
6.8
论文数:
4.6K
被引数:
2.0W
机构
引用论文
A review of wearable and unobtrusive sensing technologies for chronic disease management用于慢性病管理的可穿戴和不显眼的传感技术综述
OAAI
OAAI分享收藏The analysis of the functions of human B and T cells in humanized NOD/shi-scid/γcnull (NOG) mice (hu-HSC NOG mice)人源化NOD/shi-scid/γ-null (NOG) 小鼠 (hu-hsc NOG小鼠) 中人B和T细胞功能的分析OAAI
OAAI分享收藏Intercellular Adhesion Molecule 1 (ICAM-1) Gene Variant is Associated with Coronary Artery Calcification Independent of Soluble ICAM-1 Levels细胞间粘附分子1 (ICAM-1) 基因变异与冠状动脉钙化相关，与可溶性ICAM-1水平无关
PREAI
分享收藏Relationship between benthic assemblage structure and coal mining in the Boeza River basin (Spain)
PREAI
分享收藏Energy-Efficient Robot Configuration and Motion Planning Using Genetic Algorithm and Particle Swarm Optimization基于遗传算法和粒子群算法的节能机器人配置和运动规划.png)
EnergiesOAAI
EnergiesIF0
OAAI分享收藏分享收藏
查看更多内容