By applying the Huber regression algorithm to a relatively new technology of diffuse correlation spectroscopy(DCS),the blood flow index(BFI)from light electric field temporal autocorrelation data is extracted accurate...By applying the Huber regression algorithm to a relatively new technology of diffuse correlation spectroscopy(DCS),the blood flow index(BFI)from light electric field temporal autocorrelation data is extracted accurately via the Nth-order linear(NL)algorithm.The NL algorithm can extract BFI from tissues with irregular geometric shapes,and its accuracy depends on iterative linear regression.The combination of Huber regression with the NL algorithm is proposed in this paper for the first time.The Huber regression is compared with traditional ordinary least square(OLS)regression through computer simulations for evaluation.The results show that the Huber regression is more accurate in extracting BFI than OLS.Compared to the OLS with an error rate of 4.58%,Huber achieves a much smaller error rate(3.54%),indicating its potential in future clinical applications.展开更多
基金Shanxi Provincial Key Research and Development Project(No.201903D121149)Natural Science Foundation of Shanxi Province(No.201901D111153)+3 种基金National Natural Science Foundation of China(Nos.61671413,61771433)National Key Scientific Instrument and Equipment Development Project of China(No.2014YQ24044508)OIT Program of Shanxi Province,Shanxi Postgraduate Education Innovation Program(Nos.2020SY366,2020SY367)Graduate Science and Technology Project of North University of China(No.20201726)。
文摘By applying the Huber regression algorithm to a relatively new technology of diffuse correlation spectroscopy(DCS),the blood flow index(BFI)from light electric field temporal autocorrelation data is extracted accurately via the Nth-order linear(NL)algorithm.The NL algorithm can extract BFI from tissues with irregular geometric shapes,and its accuracy depends on iterative linear regression.The combination of Huber regression with the NL algorithm is proposed in this paper for the first time.The Huber regression is compared with traditional ordinary least square(OLS)regression through computer simulations for evaluation.The results show that the Huber regression is more accurate in extracting BFI than OLS.Compared to the OLS with an error rate of 4.58%,Huber achieves a much smaller error rate(3.54%),indicating its potential in future clinical applications.
