Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
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Randomized Controlled Trial Multicenter Study
In pursuit of a sensitive EEG functional connectivity outcome measure for clinical trials in Alzheimer's disease.
In clinical trials in Alzheimer's Disease (AD), an improvement of impaired functional connectivity (FC) could provide biological support for the potential efficacy of the drug. Electroencephalography (EEG) analysis of the SAPHIR-trial showed a treatment induced improvement of global relative theta power but not of FC measured by the phase lag index (PLI). We compared the PLI with the amplitude envelope correlation with leakage correction (AEC-c), a presumably more sensitive FC measure. ⋯ AEC-c may be a robust and sensitive FC measure for detecting treatment effects.
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Comparative Study
Improved detection of Parkinsonian resting tremor with feature engineering and Kalman filtering.
Accurate and reliable detection of tremor onset in Parkinson's disease (PD) is critical to the success of adaptive deep brain stimulation (aDBS) therapy. Here, we investigated the potential use of feature engineering and machine learning methods for more accurate detection of rest tremor in PD. ⋯ The proposed method offers a potential solution for efficient on-demand stimulation for PD tremor.