Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China.
North China Institute of Aerospace EngineeringLangfang065000China.
IEEE J Transl Eng Health Med. 2021 Feb 3;9:2100320. doi: 10.1109/JTEHM.2021.3056911. eCollection 2021.
Most of effectiveness assessments of the widely-used Massage therapy were based on subjective routine clinical assessment tools, such as Visual Analogue Scale (VAS) score. However, few studies demonstrated the impact of massage on the Electroencephalograph (EEG) rhythm decoding of Motor imagery (MI) and motion execution (ME) with trunk left/right bending in patients with skeletal muscle pain.
We used the sample entropy (SampEn), permutation entropy (PermuEn), common spatial pattern (CSP) features, support vector machine (SVM) and logic regression (LR) classifiers. We also used the convolutional neural network (CNN) and attention-based bi-directional long short-term memory (BiLSTM) for classification.
The averaged SampEn and PermuEn values of alpha rhythm decreased in almost fourteen channels for five statuses (quiet, MI with left/right bending, ME with left/right bending). It indicated that massage alleviates the pain for the patients of skeletal pain. Furthermore, compared with the SVM and LR classifiers, the BiLSTM method achieved a better area under curve (AUC) of 0.89 for the classification of MI with trunk left/right bending before massage. The AUC became smaller after massage than that before massage for the classification of MI with trunk left/right bending using CNN and BiLSTM methods. The Permutation direct indicator (PDI) score showed the significant difference for patients in different statuses (before vs after massage, and MI vs ME).
Massage not only affects the quiet status, but also affects the MI and ME. Clinical Impact: Massage therapy may affect a bit on the accuracy of MI with trunk left/right bending and it change the topography of MI and ME with trunk left/right bending for the patients with skeletal muscle pain.
广泛使用的按摩疗法的大多数疗效评估都是基于主观的常规临床评估工具，如视觉模拟量表（VAS）评分。然而，很少有研究表明按摩对电机意象（MI）和运动执行（ME）的脑电图（EEG）节律解码以及骨骼肌肉疼痛患者躯干左右弯曲的影响。
我们使用样本熵（SampEn）、排列熵（PermuEn）、共空间模式（CSP）特征、支持向量机（SVM）和逻辑回归（LR）分类器。我们还使用卷积神经网络（CNN）和基于注意力的双向长短期记忆（BiLSTM）进行分类。
在五种状态（安静、左右弯曲的 MI、左右弯曲的 ME）下，alpha 节律的平均 SampEn 和 PermuEn 值在近 14 个通道中均降低。这表明按摩减轻了骨骼疼痛患者的疼痛。此外，与 SVM 和 LR 分类器相比，BiLSTM 方法在按摩前对躯干左右弯曲 MI 的分类中获得了更好的曲线下面积（AUC）为 0.89。按摩后，使用 CNN 和 BiLSTM 方法对躯干左右弯曲 MI 的分类的 AUC 比按摩前小。排列直接指标（PDI）评分显示患者在不同状态下（按摩前 vs 按摩后、MI vs ME）存在显著差异。
按摩不仅影响安静状态，还影响 MI 和 ME。临床影响：按摩疗法可能会对躯干左右弯曲的 MI 的准确性产生一定影响，并且会改变骨骼肌肉疼痛患者躯干左右弯曲的 MI 和 ME 的地形图。
