RESUMO
The core problem of the brain-computer interface (BCI) based on neural signal is estimating neural firing rate from a spike train and then using neural population decoding algorithm to decode movement trajectory.In this artical, we review the theoretical basis of both classic and current firing rate estimations and compare the advantages and drawbacks of these methods. At the same time we also review the decoding algorithm which using neural firing rate to decode movement trajectory in brain- computer interface: population vector algorithm, linear filter and kalman filter. At last, some results applying these estimators of firing rate to decode arm movement in BCI are introduced. The results show apparently different performance of the different firing rate estimators, while minimal differences are observed in the actual application of BCI.
RESUMO
Objective To provide the administrative departments in the health sector with a method for estimating hospital beds when making regional health plans. Methods The method of general surveys was adopted to make relevant investigation on all the cities and districts in Shandong Province. Data collected were estimated by borrowed and self-developed formulas. Results By 2005, the total number of hospital beds in the province will be reduced by 5.19%, the number of beds in the city seats will be reduced by 4.97%, the number of beds in the county seats will be reduced by 1.03%, and the number of beds in the township seats will be reduced by 9.68%. Conclusion The findings of the study have filled in a gap at present when there is a lack of estimating methods. They are viable and yet still need to be polularized and perfected in practice.