ObjectiveTo explore the relationship between plasma homocysteine level and intracranial artery atherosclerosis in patients with cerebral infarction. MethodsA total of 120 patients with cerebral infarction diagnosed between January and December 2013 were selected.Plasma homocysteine level was analyzed and intracranial artery was detected by DSA. ResultsIntracranial artery atherosclerosis can be found in most of patients with cerebral infarction.Moreover,Plasma Hcy level of patients with large cerebral artery atherosclerosis was much higher than others (P<0.05).The much higher Plasma Hcy level,the severe intracranial artery atherosclerosis were found in internal carotid artery and cerebral middle artery (P<0.05). ConclusionIntracranial artery atherosclerosis is common in patients with cerebral infarction.Occurrence of intracranial artery atherosclerosis is positively correlated with plasma homocysteine level.Plasma homocysteine level may be a risk factor of intracranial artery atherosclerosis in patients with cerebral infarction.
Artifacts produced by chest compression during cardiopulmonary resuscitation (CPR) seriously affect the reliability of shockable rhythm detection algorithms. In this paper, we proposed an adaptive CPR artifacts elimination algorithm without needing any reference channels. The clean electrocardiogram (ECG) signals can be extracted from the corrupted ECG signals by incorporating empirical mode decomposition (EMD) and independent component analysis (ICA). For evaluating the performance of the proposed algorithm, a back propagation neural network was constructed to implement the shockable rhythm detection. A total of 1 484 corrupted ECG samples collected from pigs were included in the analysis. The results of the experiments indicated that this method would greatly reduce the effects of the CPR artifacts and thereby increase the accuracy of the shockable rhythm detection algorithm.