کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
557567 874720 2016 5 صفحه PDF ندارد دانلود کنید
عنوان انگلیسی مقاله
A regularised EEG informed Kalman filtering algorithm
ترجمه فارسی عنوان
الگوریتم فیلترینگ Kalman به صورت EEG تنظیم شده است
کلمات کلیدی
الکتروانسفالوگرام؛ آگاه کالمن؛ پیش بینی حرکات ارادی؛ تشخیص حالت
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
چکیده انگلیسی

The conventional Kalman filter assumes a constant process noise covariance according to the system's dynamics. However, in practice, the dynamics might alter and the initial model for the process noise may not be adequate to adapt to abrupt dynamics of the system. In this paper, we provide a novel informed Kalman filter (IKF) which is informed by an extrinsic data channel carrying information about the system's future state. Thus, each state can be represented with a corresponding process noise covariance, i.e. the Kalman gain is automatically adjusted according to the detected state. As a real-world application, we demonstrate for the first time how the analysis of electroencephalogram (EEG) can be used to predict the voluntary body movement and inform the tracking Kalman algorithm about a possible state transition. Furthermore, we provide a rigorous analysis to establish a relationship between the Kalman performance and the detection accuracy. Simulations on both synthetic and real-world data support our analysis.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biomedical Signal Processing and Control - Volume 25, March 2016, Pages 196–200
نویسندگان
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