Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, 400076, India.
Hardas Heart Care, Shivajinagar, Pune, Maharashtra, 411005, India.
Med Biol Eng Comput. 2018 Jun;56(6):1077-1089. doi: 10.1007/s11517-017-1752-5. Epub 2017 Nov 18.
Impedance cardiography is a low-cost noninvasive technique, based on monitoring of the thoracic impedance, for estimation of stroke volume (SV). Impedance cardiogram (ICG) is the negative of the first derivative of the impedance signal. A technique for beat-to-beat SV estimation using impedance cardiography and artificial neural network (ANN) is proposed. A three-layer feed-forward ANN with error back-propagation algorithm is optimized by examining the effects of number of neurons in the hidden layer, activation function, training algorithm, and set of input parameters. The input parameters are obtained by automatic detection of the ICG characteristic points, and the target values are obtained by beat-to-beat SV measurements from time-aligned Doppler echocardiogram. The technique is evaluated using an ICG-echocardiography database with recordings from subjects with normal health in the under-rest and post-exercise conditions and from subjects with cardiovascular disorders in the under-rest condition. The proposed technique performed much better than the earlier established equation-based estimations, and it resulted in correlation coefficient of 0.93 for recordings from subjects with cardiovascular disorders. It may be helpful in improving the acceptability of impedance cardiography in clinical practice. Graphical abstract ᅟ.
阻抗心动描记术是一种基于监测胸部阻抗的低成本非侵入性技术，用于估计心搏量 (SV)。阻抗心动图 (ICG) 是阻抗信号的一阶导数的负数。提出了一种使用阻抗心动描记术和人工神经网络 (ANN) 进行逐搏 SV 估计的技术。采用具有误差反向传播算法的三层前馈 ANN 进行优化，通过检查隐藏层神经元数量、激活函数、训练算法和输入参数集的影响来进行优化。输入参数通过 ICG 特征点的自动检测获得，目标值通过与时间对齐的多普勒超声心动图的逐搏 SV 测量获得。该技术使用 ICG-超声心动图数据库进行评估，该数据库记录了处于休息不足和运动后状态的健康受试者以及处于休息不足状态的心血管疾病受试者的数据。与早期建立的基于方程的估计相比，该技术的表现要好得多，对于心血管疾病患者的记录，其相关系数为 0.93。它可能有助于提高阻抗心动描记术在临床实践中的可接受性。
