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 *

220 related articles for article (PubMed ID: 34892695)

  • 1. A Preliminary Study on Automatic Motion Artifact Detection in Electrodermal Activity Data Using Machine Learning.
    Hossain MB; Posada-Quintero HF; Kong Y; McNaboe R; Chon KH
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():6920-6923. PubMed ID: 34892695
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automatic identification of artifacts in electrodermal activity data.
    Taylor S; Jaques N; Chen W; Fedor S; Sano A; Picard R
    Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():1934-7. PubMed ID: 26736662
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A Deep Convolutional Autoencoder for Automatic Motion Artifact Removal in Electrodermal Activity Signals: A Preliminary Study.
    Hossain MB; Posada-Quintero HF; Chon KH
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():325-328. PubMed ID: 36085929
    [TBL] [Abstract][Full Text] [Related]  

  • 4. An unsupervised automated paradigm for artifact removal from electrodermal activity in an uncontrolled clinical setting.
    Subramanian S; Tseng B; Barbieri R; Brown EN
    Physiol Meas; 2022 Nov; 43(11):. PubMed ID: 36113446
    [No Abstract]   [Full Text] [Related]  

  • 5. Comparison of Electrodermal Activity from Multiple Body Locations Based on Standard EDA Indices' Quality and Robustness against Motion Artifact.
    Hossain MB; Kong Y; Posada-Quintero HF; Chon KH
    Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35590866
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Validation of Spectral Indices of Electrodermal Activity with a Wearable Device.
    McNaboe RQ; Hossain MB; Kong Y; Chon KH; Posada-Quintero HF
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():6991-6994. PubMed ID: 34892712
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Analysis of sympathetic responses to cognitive stress and pain through skin sympathetic nerve activity and electrodermal activity.
    Baghestani F; Kong Y; D'Angelo W; Chon KH
    Comput Biol Med; 2024 Mar; 170():108070. PubMed ID: 38330822
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Wavelet-based motion artifact removal for electrodermal activity.
    Chen W; Jaques N; Taylor S; Sano A; Fedor S; Picard RW
    Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():6223-6. PubMed ID: 26737714
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comparative Analysis of Electrodermal Activity Decomposition Methods in Emotion Detection Using Machine Learning.
    Sriram Kumar P ; Govarthan PK; Ganapathy N; Agastinose Ronickom JF
    Stud Health Technol Inform; 2023 May; 302():73-77. PubMed ID: 37203612
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automated Pain Assessment using Electrodermal Activity Data and Machine Learning.
    Susam BT; Akcakaya M; Nezamfar H; Diaz D; Xu X; de Sa VR; Craig KD; Huang JS; Goodwin MS
    Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():372-375. PubMed ID: 30440413
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A Deep Convolutional Autoencoder for Automatic Motion Artifact Removal in Electrodermal Activity.
    Hossain MB; Posada-Quintero HF; Chon KH
    IEEE Trans Biomed Eng; 2022 Dec; 69(12):3601-3611. PubMed ID: 35544485
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Unsupervised Machine Learning Methods for Artifact Removal in Electrodermal Activity.
    Subramanian S; Tseng B; Barbieri R; Brown EN
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():399-402. PubMed ID: 34891318
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Simulation of ambulatory electrodermal activity and the handling of low-quality segments.
    Pattyn E; Thammasan N; Lutin E; Tourolle D; Van Kraaij A; Kosunen I; De Raedt W; Van Hoof C
    Comput Methods Programs Biomed; 2023 Dec; 242():107859. PubMed ID: 37863009
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Human Activity Recognition Algorithm with Physiological and Inertial Signals Fusion: Photoplethysmography, Electrodermal Activity, and Accelerometry.
    Gilmore J; Nasseri M
    Sensors (Basel); 2024 May; 24(10):. PubMed ID: 38793858
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Optimal Electrodermal Activity Segment for Enhanced Emotion Recognition Using Spectrogram-Based Feature Extraction and Machine Learning.
    P SK; Agastinose Ronickom JF
    Int J Neural Syst; 2024 May; 34(5):2450027. PubMed ID: 38511233
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Stress State Classification Based on Deep Neural Network and Electrodermal Activity Modeling.
    Vasile F; Vizziello A; Brondino N; Savazzi P
    Sensors (Basel); 2023 Feb; 23(5):. PubMed ID: 36904705
    [TBL] [Abstract][Full Text] [Related]  

  • 17. ComEDA: A new tool for stress assessment based on electrodermal activity.
    Nardelli M; Greco A; Sebastiani L; Scilingo EP
    Comput Biol Med; 2022 Nov; 150():106144. PubMed ID: 36215850
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Female-male Differences Should be Considered in Physical Pain Quantification based on Electrodermal Activity: Preliminary Study.
    Kong Y; Posada-Quintero HF; Chon KH
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():6941-6944. PubMed ID: 34892700
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Exploration of physiological sensors, features, and machine learning models for pain intensity estimation.
    Pouromran F; Radhakrishnan S; Kamarthi S
    PLoS One; 2021; 16(7):e0254108. PubMed ID: 34242325
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Electrodermal Activity Based Pre-surgery Stress Detection Using a Wrist Wearable.
    S AA; P S; V S; S SK; A S; Akl TJ; P PS; Sivaprakasam M
    IEEE J Biomed Health Inform; 2020 Jan; 24(1):92-100. PubMed ID: 30668508
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.