Department of Electrical and Computer Engineering, Queen's University, Kingston, ON K7L 3N6, Canada.
Sensors (Basel). 2020 Aug 27;20(17):0. doi: 10.3390/s20174858.
Accurate and real-time estimation of force from surface electromyogram (EMG) signals enables a variety of applications. We developed and validated new approaches for selecting subsets of high-density (HD) EMG channels for improved and lower-dimensionality force estimation. First, a large dataset was recorded from a number of participants performing isometric contractions in different postures, while simultaneously recording HD-EMG channels and ground-truth force. The EMG signals were acquired from three linear surface electrode arrays, each with eight monopolar channels, and were placed on the long head and short head of the biceps brachii and brachioradialis. After data collection and pre-processing, fast orthogonal search (FOS) was employed for force estimation. To select a subset of channels, principal component analysis (PCA) in the frequency domain and a novel index called the power-correlation ratio (PCR), which maximizes the spectral power while minimizing similarity to other channels, were used. These approaches were compared to channel selection using time-domain PCA. We selected one, two, and three channels per muscle from the original seven differential channels to reduce the redundancy and correlation in the dataset. In the best case, we achieved an approximate improvement of 30% for force estimation while reducing the dimensionality by 57% for a subset of three channels.
准确、实时地从表面肌电图 (EMG) 信号中估计力可以实现各种应用。我们开发并验证了新的方法，用于选择高密度 (HD) EMG 通道的子集，以实现更好的、低维的力估计。首先，从许多参与者在不同姿势下进行等长收缩的过程中记录了大量数据集，同时记录了 HD-EMG 通道和地面真实力。EMG 信号是从三个线性表面电极阵列中获取的，每个阵列都有八个单极通道，放置在肱二头肌的长头和短头以及肱桡肌上。在数据收集和预处理之后，使用快速正交搜索 (FOS) 进行力估计。为了选择通道子集，在频域中使用主成分分析 (PCA) 和一种新的称为功率相关比 (PCR) 的指标，该指标最大化了光谱功率，同时最小化了与其他通道的相似性。这些方法与使用时域 PCA 的通道选择进行了比较。我们从原始的七个差分通道中为每个肌肉选择一个、两个和三个通道，以减少数据集的冗余和相关性。在最佳情况下，我们在估计力时实现了约 30%的近似改进，同时将维度减少了 57%，达到了三个通道的子集。
