Comparing a template approach and complex bandpass filtering for single-trial analysis of auditory evoked M100
-
Alfred Link
Abstract
Two methods for single-trial analysis were compared, an established parametric template approach and a recently proposed non-parametric method based on complex bandpass filtering. The comparison was carried out by means of pseudo-real simulations based on magnetoencephalography measurements of cortical responses to auditory signals. The comparison focused on amplitude and latency estimation of the M100 response. The results show that both methods are well suited for single-trial analysis of the auditory evoked M100. While both methods performed similarly with respect to latency estimation, the non-parametric approach was observed to be more robust for amplitude estimation. The non-parametric approach can thus be recommended as an additional valuable tool for single-trial analysis.
References
[1] Woody CD. Characterization of an adaptive filter for the analysis of variable latency neuroelectric signals. Med Biol Eng1967; 5: 539–553.10.1007/BF02474247Search in Google Scholar
[2] Thakor NV. Adaptive filtering of evoked potentials. IEEE Trans Biomed Eng1987; 34: 6–12.10.1109/TBME.1987.326024Search in Google Scholar PubMed
[3] Tuan PD, Möcks J, Köhler W, Gasser T. Variable latencies of noisy signals: Estimation and testing in brain potential data. Biometrika1987; 74: 527–533.10.1093/biomet/74.3.525Search in Google Scholar
[4] Cerutti S, Chiarenza G, Liberati D, Mascellani P, Pavesi G. Parametric method of identification of single-trial event-related potentials in the brain. IEEE Trans Biomed Eng1988; 35: 701–711.10.1109/10.7271Search in Google Scholar PubMed
[5] von Spreckelsen M, Bromm B. Estimation of single-evoked cerebral potentials by means of parametric modeling and Kalman filtering. IEEE Trans Biomed Eng1988; 35: 691–700.10.1109/10.7270Search in Google Scholar PubMed
[6] Lange HD, Pratt H, Inbar GF. Segmented matched filtering of single event related evoked potentials. IEEE Trans Biomed Eng1995; 42: 317–321.10.1109/10.364520Search in Google Scholar PubMed
[7] Hansson M, Gänsler T, Salomonsson G. Estimation of single event-related potentials utilizing the Prony method. IEEE Trans Biomed Eng1996; 43: 973–981.10.1109/10.536898Search in Google Scholar PubMed
[8] Lange HD, Pratt H, Inbar GF. Modelling and estimation of single evoked brain potential components. IEEE Trans Biomed Eng1997; 44: 791–799.10.1109/10.623048Search in Google Scholar PubMed
[9] Karjalainen PA, Kaipio JP, Koistinen AS, Vauhkonen M. Subspace regularization method for the single-trial estimation of evoked potentials. IEEE Trans Biomed Eng1999; 46: 849–860.10.1109/10.771195Search in Google Scholar PubMed
[10] Jaśkowski P, Verleger R. Amplitudes and latencies of single-trial ERPs estimated by a maximum-likelihood method. IEEE Trans Biomed Eng1999; 46: 987–993.10.1109/10.775409Search in Google Scholar PubMed
[11] Heinrich H, Dickhaus H, Rothenberger A, Heinrich V, Moll GH. Single-sweep analysis of event-related potentials by wavelet networks – methodological basis and clinical application. IEEE Trans Biomed Eng1999; 46: 867–879.10.1109/10.771199Search in Google Scholar PubMed
[12] Brillinger DR. Some aspects of the analysis of evoked response experiments. In: Csörgö H, Dawson DA, Rao JNK, Saleh AJ, editors. Statistics and related topics. Amsterdam, The Netherlands: North-Holland 1981: 155–168.Search in Google Scholar
[13] Salajegheh A, Link A, Elster C, et al. Systematic latency variation of the auditory evoked M100: From average to single-trial data. Neuroimage2004; 23: 288–295.10.1016/j.neuroimage.2004.05.022Search in Google Scholar PubMed
[14] Burghoff M, Link A, Salajegheh A, Elster C, Poeppel D, Trahms L. A template-free approach for determining the latency of single events of auditory evoked M100. Phys Med Biol2005; 50: N43–N48.10.1088/0031-9155/50/3/N04Search in Google Scholar
[15] Link A, Endt P, Oeff M, Trahms L. Variability of the QRS signal in high-resolution electrocardiograms and magnetocardiograms. IEEE Trans Biomed Eng2001; 48: 133–142.10.1109/10.909634Search in Google Scholar PubMed
[16] MATLAB. Natick, MA: The MathWorks Inc 2000.Search in Google Scholar
©2007 by Walter de Gruyter Berlin New York
Articles in the same Issue
- Ralph Mueller and Herbert Witte join the Associate Editor team of Biomedizinische Technik/Biomedical Engineering
- Technological innovations in information engineering demand sustained updating and upgrading in biosignal processing applications: a continual renaissance
- Predicting initiation and termination of atrial fibrillation from the ECG
- Predicting the QRS complex and detecting small changes using principal component analysis
- The role of independent component analysis in the signal processing of ECG recordings
- Implantable cardioverter defibrillator algorithms: status review in terms of computational cost
- Assessment of dynamic changes in cerebral autoregulation
- Corrected body surface potential mapping
- Autonomic cardiac control in animal models of cardiovascular diseases. I. Methods of variability analysis
- Autonomic cardiac control in animal models of cardiovascular diseases II. Variability analysis in transgenic rats with α-tropomyosin mutations Asp175Asn and Glu180Gly
- Fetal ECG extraction during labor using an adaptive maternal beat subtraction technique
- Heart rate variability in the fetus: a comparison of measures
- Estimation of spontaneous baroreflex sensitivity using transfer function analysis: effects of positive pressure ventilation
- Mobile nocturnal long-term monitoring of wheezing and cough
- Vigilance monitoring – review and practical aspects
- Coupled oscillators for modeling and analysis of EEG/MEG oscillations
- Auditory evoked potentials for the assessment of depth of anaesthesia: different configurations of artefact detection algorithms
- NeuMonD: a tool for the development of new indicators of anaesthetic effect
- Recording of focal direct current (DC) changes in the human cerebral cortex using refined non-invasive DC-EEG methodology
- Comparing a template approach and complex bandpass filtering for single-trial analysis of auditory evoked M100
- Wavelet-based analysis of MMN responses in children
- Branched EMG electrodes for stable and selective recording of single motor unit potentials in humans
- EMG analysis of the thenar muscles as a model for EMG-triggered larynx stimulation
- Physiological MR signal variations within the brain at 3 T
- Application of decorrelation-independent component analysis to biomagnetic multi-channel measurements
- A method for locating gradual changes in time series
- The use of digital signal processors (DSPs) in real-time processing of multi-parametric bioelectronic signals
- Steps towards a miniaturized, robust and autonomous measurement device for the long-term monitoring of patient activity: ActiBelt
- Motor timing and more – additional options using advanced registration and evaluation of tapping data
- Cellular signaling: aspects for tumor diagnosis and therapy
- List of reviewers engaged in the Special Issues on Biosignal Processing
- Stellungnahme zu „In vitro Langzeitkultur von humanem Knochen unter physiologischen Lastbedingungen“; Biomed Tech 2004; 49: 364–367
Articles in the same Issue
- Ralph Mueller and Herbert Witte join the Associate Editor team of Biomedizinische Technik/Biomedical Engineering
- Technological innovations in information engineering demand sustained updating and upgrading in biosignal processing applications: a continual renaissance
- Predicting initiation and termination of atrial fibrillation from the ECG
- Predicting the QRS complex and detecting small changes using principal component analysis
- The role of independent component analysis in the signal processing of ECG recordings
- Implantable cardioverter defibrillator algorithms: status review in terms of computational cost
- Assessment of dynamic changes in cerebral autoregulation
- Corrected body surface potential mapping
- Autonomic cardiac control in animal models of cardiovascular diseases. I. Methods of variability analysis
- Autonomic cardiac control in animal models of cardiovascular diseases II. Variability analysis in transgenic rats with α-tropomyosin mutations Asp175Asn and Glu180Gly
- Fetal ECG extraction during labor using an adaptive maternal beat subtraction technique
- Heart rate variability in the fetus: a comparison of measures
- Estimation of spontaneous baroreflex sensitivity using transfer function analysis: effects of positive pressure ventilation
- Mobile nocturnal long-term monitoring of wheezing and cough
- Vigilance monitoring – review and practical aspects
- Coupled oscillators for modeling and analysis of EEG/MEG oscillations
- Auditory evoked potentials for the assessment of depth of anaesthesia: different configurations of artefact detection algorithms
- NeuMonD: a tool for the development of new indicators of anaesthetic effect
- Recording of focal direct current (DC) changes in the human cerebral cortex using refined non-invasive DC-EEG methodology
- Comparing a template approach and complex bandpass filtering for single-trial analysis of auditory evoked M100
- Wavelet-based analysis of MMN responses in children
- Branched EMG electrodes for stable and selective recording of single motor unit potentials in humans
- EMG analysis of the thenar muscles as a model for EMG-triggered larynx stimulation
- Physiological MR signal variations within the brain at 3 T
- Application of decorrelation-independent component analysis to biomagnetic multi-channel measurements
- A method for locating gradual changes in time series
- The use of digital signal processors (DSPs) in real-time processing of multi-parametric bioelectronic signals
- Steps towards a miniaturized, robust and autonomous measurement device for the long-term monitoring of patient activity: ActiBelt
- Motor timing and more – additional options using advanced registration and evaluation of tapping data
- Cellular signaling: aspects for tumor diagnosis and therapy
- List of reviewers engaged in the Special Issues on Biosignal Processing
- Stellungnahme zu „In vitro Langzeitkultur von humanem Knochen unter physiologischen Lastbedingungen“; Biomed Tech 2004; 49: 364–367
