Argha Ahmadreza, Celler Branko G, Nguyen Hung T, Su Steven W
Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:1525-1528. doi: 10.1109/EMBC.2017.8037126.
This paper investigates the modelling of oxygen consumption (VO) response to jogging exercise on treadmill. Unlike most of the previous methods, which often use simple parametric models, e.g., first order linear time invariant model, this study applied a nonparametric kernel based regularised method to estimate VO to address the ill-conditioned modelling problem and achieve accurate estimation. In particular, it is worthy to be noted that the selection of kernels will affect the results for different modelling scenarios. Therefore, in this research, both radial basis kernel and stable spline kernel were selected for testing. In order to select the favourable kernel for this system, a simulation related to VO-jogging speed was carried out. The results of simulation indicated that spline kernel can achieve higher accuracy comparing to radial basis function kernel. Experimentally, the kernel based estimation method and spline kernel were tested using six participants. From the results, an average impulse response is obtained. It showed the VO estimation, based on the average finite impulse response, is fitted well to the six observations collected from the participants.
本文研究了在跑步机上进行慢跑运动时耗氧量（VO）响应的建模。与大多数先前的方法不同，这些方法通常使用简单的参数模型，例如一阶线性时不变模型，本研究应用了基于非参数核的正则化方法来估计VO，以解决病态建模问题并实现准确估计。特别值得注意的是，核的选择会影响不同建模场景的结果。因此，在本研究中，选择了径向基核和稳定样条核进行测试。为了为该系统选择合适的核，进行了与VO-慢跑速度相关的模拟。模拟结果表明，与径向基函数核相比，样条核可以实现更高的精度。在实验中，使用六名参与者对基于核的估计方法和样条核进行了测试。从结果中，获得了平均脉冲响应。结果表明，基于平均有限脉冲响应的VO估计与从参与者收集的六个观测值拟合良好。
