Linear Logistic Regression for Estimation of Lower Limb Muscle Activations.
作者: Sekiya MasashiSakaino ShoToshiaki Tsuji
刊名: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2019, Vol.27 (3), pp.523-532
来源数据库: PubMed Journal
DOI: 10.1109/TNSRE.2019.2898207
原始语种摘要: This paper addresses a technique to estimate the muscle activity from the movement data. Statistical models, such as linear regression (LR) models and artificial neural networks (ANNs), are good candidate estimation techniques. Although an ANN has a high estimation capability, it is frequently in the clinical application that a very small amount of data leads to performance deterioration. Conversely, an LR model needs fewer data, while its generalization performance is limited. In this paper, therefore, a muscle activity estimation method is proposed that uses a linear logistic regression model to improve the generalization performance. The proposed method was compared with an LR model and an ANN in verification experiments with several different conditions. The results suggest that the...
全文获取路径: PubMed  (合作)

  • proposed 建议的
  • estimate 估计
  • regression 海退
  • estimation 估计
  • ANN All Numeral Numbering
  • performance 性能
  • method 方法
  • model 模型
  • capability 能力
  • paper