کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4335138 1295126 2012 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Parkinsonian tremor identification with multiple local field potential feature classification
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب (عمومی)
پیش نمایش صفحه اول مقاله
Parkinsonian tremor identification with multiple local field potential feature classification
چکیده انگلیسی

This paper explores the development of multi-feature classification techniques used to identify tremor-related characteristics in the Parkinsonian patient. Local field potentials were recorded from the subthalamic nucleus and the globus pallidus internus of eight Parkinsonian patients through the implanted electrodes of a Deep brain stimulation (DBS) device prior to device internalization.A range of signal processing techniques were evaluated with respect to their tremor detection capability and used as inputs in a multi-feature neural network classifier to identify the activity of Parkinsonian tremor. The results of this study show that a trained multi-feature neural network is able, under certain conditions, to achieve excellent detection accuracy on patients unseen during training. Overall the tremor detection accuracy was mixed, although an accuracy of over 86% was achieved in four out of the eight patients.


► Design of a pattern detection system for Parkinson's disease tremor.
► Detection uses processing of LFP signals from the stimulation electrodes.
► The system was based on neural network using multiple feature types.
► Satisfactory results were obtained for a subgroup of tested patients.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Neuroscience Methods - Volume 209, Issue 2, 15 August 2012, Pages 320–330
نویسندگان
, , , , , ,