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Title: Efficient block processing of long duration biotelemetric brain data for health care monitoring

In real time clinical environment, the brain signals which doctor need to analyze are usually very long. Such a scenario can be made simple by partitioning the input signal into several blocks and applying signal conditioning. This paper presents various block based adaptive filter structures for obtaining high resolution electroencephalogram (EEG) signals, which estimate the deterministic components of the EEG signal by removing noise. To process these long duration signals, we propose Time domain Block Least Mean Square (TDBLMS) algorithm for brain signal enhancement. In order to improve filtering capability, we introduce normalization in the weight update recursion of TDBLMS, which results TD-B-normalized-least mean square (LMS). To increase accuracy and resolution in the proposed noise cancelers, we implement the time domain cancelers in frequency domain which results frequency domain TDBLMS and FD-B-Normalized-LMS. Finally, we have applied these algorithms on real EEG signals obtained from human using Emotive Epoc EEG recorder and compared their performance with the conventional LMS algorithm. The results show that the performance of the block based algorithms is superior to the LMS counter-parts in terms of signal to noise ratio, convergence rate, excess mean square error, misadjustment, and coherence.
Authors:
 [1] ;  [2] ;  [3] ;  [4]
  1. Department of E.I.E, GITAM University, Visakhapatnam (India)
  2. Department of E.C.E, K.L. University, Vaddeswaram, Green Fields, Guntur, Andhra Pradesh (India)
  3. Department of Instrumentation Engineering, College of Engineering, Andhra University, Visakhapatnam (India)
  4. Department of Innovation Engineering, University of Salento, Lecce (Italy)
Publication Date:
OSTI Identifier:
22392425
Resource Type:
Journal Article
Resource Relation:
Journal Name: Review of Scientific Instruments; Journal Volume: 86; Journal Issue: 3; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; ACCURACY; ALGORITHMS; BRAIN; ERRORS; FILTERS; MONITORING; NOISE; PERFORMANCE; RESOLUTION; SIGNAL CONDITIONING; SIGNALS; SIGNAL-TO-NOISE RATIO