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使用稀疏回归检测大鼠尿道外括约肌活动中的膀胱收缩。

Detection of Bladder Contractions From the Activity of the External Urethral Sphincter in Rats Using Sparse Regression.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2018 Aug;26(8):1636-1644. doi: 10.1109/TNSRE.2018.2854675. Epub 2018 Jul 9.

Abstract

Bladder overactivity and incontinence and dysfunction can be mitigated by electrical stimulation of the pudendal nerve applied at the onset of a bladder contraction. Thus, it is important to predict accurately both bladder pressure and the onset of bladder contractions. We propose a novel method for prediction of bladder pressure using a time-dependent spectrogram representation of external urethral sphincter electromyographic (EUS EMG) activity and a least absolute shrinkage and selection operator regression model. There was a statistically significant improvement in prediction of bladder pressure compared with methods based on the firing rate of EUS EMG activity. This approach enabled prediction of the onset of bladder contractions with 91% specificity and 96% sensitivity and may be suitable for closed-loop control of bladder continence.

摘要

通过在膀胱收缩开始时对阴部神经进行电刺激,可以缓解膀胱过度活动和失禁以及功能障碍。因此,准确预测膀胱压力和膀胱收缩的开始非常重要。我们提出了一种使用外部尿道括约肌肌电图(EUS EMG)活动的时变频谱图表示和最小绝对值收缩和选择算子回归模型来预测膀胱压力的新方法。与基于 EUS EMG 活动的发射率的方法相比,该方法在预测膀胱压力方面有了统计学上的显著改善。该方法能够以 91%的特异性和 96%的灵敏度预测膀胱收缩的开始,可能适用于膀胱控尿的闭环控制。

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