Non-genetic factors associated with the risk of Parkinson's disease in Iranian patients.

The aim of this study was to investigate some of nongenetic factors associated with Parkinson's disease (PD) in a sample of Iranian patients. This case-control study included 75 patients with idiopathic PD and 75 control patients. The patients in the control group were found to have drunk more glasses of tea per day than the case group before the onset of their problem (p=0.019). Every extra glass of tea per day decreased the risk of PD by 0.8 times (OR=0.8, 95%CI=0.73-0.97, p=0.02). Each cup of coffee per week decreased the chance of developing PD by 0.5 times (OR=0.5, 95%CI=0.28-0.9, p=0.021). A previous history of evening work increased PD risk by 4.6 times (OR=4.6, 95%CI=1.29-16.86, p=0.019) while major stressful events increased it by 13.5 times (OR=13.5, 95%CI=4.7-38.1, p=0.0001). In conclusion, coffee and tea consumption may exert a protective effect against PD, while evening work and stress may be risk factors for the development of the disease.

Enhancing P300 Wave of BCI Systems Via Negentropy in Adaptive Wavelet Denoising.

Brian Computer Interface (BCI) is a direct communication pathway between the brain and an external device. BCIs are often aimed at assisting, augmenting or repairing human cognitive or sensory-motor functions. EEG separation into target and non-target ones based on presence of P300 signal is of difficult task mainly due to their natural low signal to noise ratio. In this paper a new algorithm is introduced to enhance EEG signals and improve their SNR. Our denoising method is based on multi-resolution analysis via Independent Component Analysis (ICA) Fundamentals. We have suggested combination of negentropy as a feature of signal and subband information from wavelet transform. The proposed method is finally tested with dataset from BCI Competition 2003 and gives results that compare favorably.