Purpose： The purpose of this review was to critically analyse the cun;ent evidence investigating the effect of an athlete＇s hydration status on physical performance. Methods： A literature search of multiple databas...Purpose： The purpose of this review was to critically analyse the cun;ent evidence investigating the effect of an athlete＇s hydration status on physical performance. Methods： A literature search of multiple databases was used to identify studies that met the inclusion criteria for this review. The included studies were then critically appraised using the Downs and Black protocol. Results： Nine articles were found to meet the inclusion criteria, with an average score of 79% for methodological quality representative of a ＂high＂ standard of research. Conclusion： The evidence suggests that dehydration has a negative impact on physical performance for activities lasting more than 30 s in duration. However dehydration was found to have no significant impact on physical performance for activities lasting less than 15 s in duration.展开更多
The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Ef...The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Effect of feature selection in EMG signal processing was also verified by comparing classification accuracy of each feature, and the enhancement of classification accuracy by normalization was confirmed. EMG signals were acquired from two electrodes placed on the forearm of twenty eight healthy subjects and used for recognition of wrist motion. Features were extracted from the obtained EMG signals in the time domain and were applied to classification methods. The difference absolute mean value (DAMV), difference absolute standard deviation value (DASDV), mean absolute value (MAV), root mean square (RMS) were used for composing 16 double features which were combined of two channels. In the classification methods, the highest accuracy of classification showed in the GMM. The most effective combination of classification method and double feature was (MAV, DAMV) of GMM and its classification accuracy was 96.85%. The results of normalization were better than those of non-normalization in GMM, k-NN, and LDA.展开更多
Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface. Firstly, discrete wavelet transform method was used to decompose the average power of C3 electrode an...Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface. Firstly, discrete wavelet transform method was used to decompose the average power of C3 electrode and C4 electrode in left-right hands imagery movement during some periods of time. The reconstructed signal of approximation coefficient A6 on the 6al level was selected to build up a feature signal. Secondly, the performances by Fisher Linear Discriminant Analysis with two different threshold calculation ways and Support Vector Machine methods were compared. The final classification results showed that false classification rate by Support Vector Machine was lower and gained an ideal classification results.展开更多
It has been shown that for two different multipartite unitary operations U_1 and U_2, when tr(U_1~?U_2) = 0, they can always be perfectly distinguished by local operations and classical communication in the single-run...It has been shown that for two different multipartite unitary operations U_1 and U_2, when tr(U_1~?U_2) = 0, they can always be perfectly distinguished by local operations and classical communication in the single-run scenario. However, how to find the detailed scheme to complete the local discrimination is still a fascinating problem. In this paper, aiming at some U_1 and U_2 acting on the bipartite and tripartite space respectively, especially for U_1~?U_2 locally unitary equivalent to the high dimensional X-type hermitian unitary matrix V with trV = 0, we put forward the explicit local distinguishing schemes in the single-run scenario.展开更多
文摘Purpose： The purpose of this review was to critically analyse the cun;ent evidence investigating the effect of an athlete＇s hydration status on physical performance. Methods： A literature search of multiple databases was used to identify studies that met the inclusion criteria for this review. The included studies were then critically appraised using the Downs and Black protocol. Results： Nine articles were found to meet the inclusion criteria, with an average score of 79% for methodological quality representative of a ＂high＂ standard of research. Conclusion： The evidence suggests that dehydration has a negative impact on physical performance for activities lasting more than 30 s in duration. However dehydration was found to have no significant impact on physical performance for activities lasting less than 15 s in duration.
基金Project(NIPA-2012-H0401-12-1007) supported by the MKE(The Ministry of Knowledge Economy), Korea, supervised by the NIPAProject(2010-0020163) supported by Key Research Institute Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology, Korea
文摘The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Effect of feature selection in EMG signal processing was also verified by comparing classification accuracy of each feature, and the enhancement of classification accuracy by normalization was confirmed. EMG signals were acquired from two electrodes placed on the forearm of twenty eight healthy subjects and used for recognition of wrist motion. Features were extracted from the obtained EMG signals in the time domain and were applied to classification methods. The difference absolute mean value (DAMV), difference absolute standard deviation value (DASDV), mean absolute value (MAV), root mean square (RMS) were used for composing 16 double features which were combined of two channels. In the classification methods, the highest accuracy of classification showed in the GMM. The most effective combination of classification method and double feature was (MAV, DAMV) of GMM and its classification accuracy was 96.85%. The results of normalization were better than those of non-normalization in GMM, k-NN, and LDA.
基金The Open Project of the State Key Laboratory of Robotics and System (HIT)the State Key Laboratory of Cognitive Neuroscience and Learning+3 种基金Natural Science Fund for Colleges and Universities in Jiangsu Provincegrant number:105TB51003Natural Science Fund in Changzhougrant number:CJ20110023
文摘Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface. Firstly, discrete wavelet transform method was used to decompose the average power of C3 electrode and C4 electrode in left-right hands imagery movement during some periods of time. The reconstructed signal of approximation coefficient A6 on the 6al level was selected to build up a feature signal. Secondly, the performances by Fisher Linear Discriminant Analysis with two different threshold calculation ways and Support Vector Machine methods were compared. The final classification results showed that false classification rate by Support Vector Machine was lower and gained an ideal classification results.
基金supported by the National Natural Science Foundation of China(Grants Nos.61272057 and 61572081)the Beijing Higher Education Young Elite Teacher Project(Grants Nos.YETP0475 and YETP0477)the Natural Science Foundation of Shaanxi Province of China(Grant No.2015JM6263)
文摘It has been shown that for two different multipartite unitary operations U_1 and U_2, when tr(U_1~?U_2) = 0, they can always be perfectly distinguished by local operations and classical communication in the single-run scenario. However, how to find the detailed scheme to complete the local discrimination is still a fascinating problem. In this paper, aiming at some U_1 and U_2 acting on the bipartite and tripartite space respectively, especially for U_1~?U_2 locally unitary equivalent to the high dimensional X-type hermitian unitary matrix V with trV = 0, we put forward the explicit local distinguishing schemes in the single-run scenario.
