These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

110 related articles for article (PubMed ID: 26774029)

  • 1. High-pass filters and baseline correction in M/EEG analysis. Commentary on: "How inappropriate high-pass filters can produce artefacts and incorrect conclusions in ERP studies of language and cognition".
    Maess B; Schröger E; Widmann A
    J Neurosci Methods; 2016 Jun; 266():164-5. PubMed ID: 26774029
    [TBL] [Abstract][Full Text] [Related]  

  • 2. How inappropriate high-pass filters can produce artifactual effects and incorrect conclusions in ERP studies of language and cognition.
    Tanner D; Morgan-Short K; Luck SJ
    Psychophysiology; 2015 Aug; 52(8):997-1009. PubMed ID: 25903295
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Optimal digital filters for analyzing the mid-latency auditory P50 event-related potential in patients with Alzheimer's disease.
    Liljander S; Holm A; Keski-Säntti P; Partanen JV
    J Neurosci Methods; 2016 Jun; 266():50-67. PubMed ID: 27015794
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Systematic biases in early ERP and ERF components as a result of high-pass filtering.
    Acunzo DJ; Mackenzie G; van Rossum MC
    J Neurosci Methods; 2012 Jul; 209(1):212-8. PubMed ID: 22743800
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Digital filter design for electrophysiological data--a practical approach.
    Widmann A; Schröger E; Maess B
    J Neurosci Methods; 2015 Jul; 250():34-46. PubMed ID: 25128257
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A simple algorithm for a digital three-pole Butterworth filter of arbitrary cut-off frequency: application to digital electroencephalography.
    Alarcon G; Guy CN; Binnie CD
    J Neurosci Methods; 2000 Dec; 104(1):35-44. PubMed ID: 11163409
    [TBL] [Abstract][Full Text] [Related]  

  • 7. High-pass filtering artifacts in multivariate classification of neural time series data.
    van Driel J; Olivers CNL; Fahrenfort JJ
    J Neurosci Methods; 2021 Mar; 352():109080. PubMed ID: 33508412
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Fast time-varying linear filters for suppression of baseline drift in electrocardiographic signals.
    Kozumplík J; Provazník I
    Biomed Eng Online; 2017 Feb; 16(1):24. PubMed ID: 28173809
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Event Related Potential Signal Capture Can Be Enhanced through Dynamic SNR-Weighted Channel Pooling.
    Hajra SG; Liu CC; Fickling SD; Pawlowski GM; Song X; D'Arcy RCN
    Sensors (Basel); 2021 Oct; 21(21):. PubMed ID: 34770564
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Use of finite wordlength FIR digital filter structures with improved magnitude and phase characteristics for reduction of muscle noise in EEG signals.
    Sadasivan PK; Dutt DN
    Med Biol Eng Comput; 1995 May; 33(3):306-12. PubMed ID: 7475367
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A periodic spatio-spectral filter for event-related potentials.
    Ghaderi F; Kim SK; Kirchner EA
    Comput Biol Med; 2016 Dec; 79():286-298. PubMed ID: 27837720
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Improving liquid chromatography-tandem mass spectrometry determinations by modifying noise frequency spectrum between two consecutive wavelet-based low-pass filtering procedures.
    Chen HP; Liao HJ; Huang CM; Wang SC; Yu SN
    J Chromatogr A; 2010 Apr; 1217(17):2804-11. PubMed ID: 20227706
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparing the Performance of Popular MEG/EEG Artifact Correction Methods in an Evoked-Response Study.
    Haumann NT; Parkkonen L; Kliuchko M; Vuust P; Brattico E
    Comput Intell Neurosci; 2016; 2016():7489108. PubMed ID: 27524998
    [TBL] [Abstract][Full Text] [Related]  

  • 14. The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects.
    Karpiel I; Kurasz Z; Kurasz R; Duch K
    Sensors (Basel); 2021 Nov; 21(22):. PubMed ID: 34833790
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Cardinal series to filter oversampled truncated magnetic resonance signals.
    Rodts S; Bytchenkoff D; Fen-Chong T
    J Magn Reson; 2010 May; 204(1):64-75. PubMed ID: 20303807
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Filtering and thresholding the analytic signal envelope in order to improve peak and spike noise reduction in EEG signals.
    Melia U; Clariá F; Vallverdú M; Caminal P
    Med Eng Phys; 2014 Apr; 36(4):547-53. PubMed ID: 24365255
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A programmable rapid roll-off low pass filter for evoked potential and EEG recording.
    Dowman R; Stockbridge N
    Brain Res Bull; 1988 Aug; 21(2):335-9. PubMed ID: 3191416
    [TBL] [Abstract][Full Text] [Related]  

  • 18. The effects of high pass filters on computer-reconstructed evoked potentials.
    Campbell JA; Leandri M
    Electroencephalogr Clin Neurophysiol; 1984 Jan; 57(1):99-101. PubMed ID: 6198149
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Time-shift denoising source separation.
    de Cheveigné A
    J Neurosci Methods; 2010 May; 189(1):113-20. PubMed ID: 20298717
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Pitfalls of high-pass filtering for detecting epileptic oscillations: a technical note on "false" ripples.
    Bénar CG; Chauvière L; Bartolomei F; Wendling F
    Clin Neurophysiol; 2010 Mar; 121(3):301-10. PubMed ID: 19955019
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.