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 *

192 related articles for article (PubMed ID: 34640689)

  • 1. A Muscle Fatigue Classification Model Based on LSTM and Improved Wavelet Packet Threshold.
    Wang J; Sun S; Sun Y
    Sensors (Basel); 2021 Sep; 21(19):. PubMed ID: 34640689
    [TBL] [Abstract][Full Text] [Related]  

  • 2. [Research on muscle fatigue recognition model based on improved wavelet denoising and long short-term memory].
    Wang J; Sun S; Sun Y; Chen J; Peng W; Li L
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2022 Jun; 39(3):507-515. PubMed ID: 35788520
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A Novel Method for Classification of Running Fatigue Using Change-Point Segmentation.
    Khan T; Lundgren LE; Järpe E; Olsson MC; Viberg P
    Sensors (Basel); 2019 Oct; 19(21):. PubMed ID: 31683532
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.
    Karthick PA; Ghosh DM; Ramakrishnan S
    Comput Methods Programs Biomed; 2018 Feb; 154():45-56. PubMed ID: 29249346
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Super wavelet for sEMG signal extraction during dynamic fatiguing contractions.
    Al-Mulla MR; Sepulveda F
    J Med Syst; 2015 Jan; 39(1):167. PubMed ID: 25526707
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Long short-term memory (LSTM) recurrent neural network for muscle activity detection.
    Ghislieri M; Cerone GL; Knaflitz M; Agostini V
    J Neuroeng Rehabil; 2021 Oct; 18(1):153. PubMed ID: 34674720
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Neuromuscular fatigue thresholds of the vastus lateralis, vastus medialis and rectus femoris muscles.
    Housh TJ; deVries HA; Johnson GO; Evans SA; Housh DJ; Stout JR; Bradway RM; Evetovich TK
    Electromyogr Clin Neurophysiol; 1996 Jun; 36(4):247-55. PubMed ID: 8803497
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Evolved pseudo-wavelet function to optimally decompose sEMG for automated classification of localized muscle fatigue.
    Al-Mulla MR; Sepulveda F; Colley M
    Med Eng Phys; 2011 May; 33(4):411-7. PubMed ID: 21256068
    [TBL] [Abstract][Full Text] [Related]  

  • 9. The analysis of hand movement distinction based on relative frequency band energy method.
    Zhang Y; Wang G; Teng C; Sun Z; Wang J
    Biomed Res Int; 2014; 2014():781769. PubMed ID: 25431766
    [TBL] [Abstract][Full Text] [Related]  

  • 10. sEMG-Based Neural Network Prediction Model Selection of Gesture Fatigue and Dataset Optimization.
    Ma F; Song F; Liu Y; Niu J
    Comput Intell Neurosci; 2020; 2020():8853314. PubMed ID: 33224188
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Research on the Recognition of Various Muscle Fatigue States in Resistance Strength Training.
    Wang Y; Lu C; Zhang M; Wu J; Tang Z
    Healthcare (Basel); 2022 Nov; 10(11):. PubMed ID: 36421616
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A CNN-LSTM model for six human ankle movements classification on different loads.
    Li M; Wang J; Yang S; Xie J; Xu G; Luo S
    Front Hum Neurosci; 2023; 17():1101938. PubMed ID: 36968785
    [TBL] [Abstract][Full Text] [Related]  

  • 13. EMG wavelet analysis of quadriceps muscle during repeated knee extension movement.
    So RC; Ng JK; Lam RW; Lo CK; Ng GY
    Med Sci Sports Exerc; 2009 Apr; 41(4):788-96. PubMed ID: 19276855
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Surface electromyography signal denoising via EEMD and improved wavelet thresholds.
    Sun Z; Xi X; Yuan C; Yang Y; Hua X
    Math Biosci Eng; 2020 Oct; 17(6):6945-6962. PubMed ID: 33378883
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A New Approach to Noninvasive-Prolonged Fatigue Identification Based on Surface EMG Time-Frequency and Wavelet Features.
    Jamaluddin FN; Ibrahim F; Ahmad SA
    J Healthc Eng; 2023; 2023():1951165. PubMed ID: 36756137
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Novel Method for Classifying Liver and Brain Tumors Using Convolutional Neural Networks, Discrete Wavelet Transform and Long Short-Term Memory Networks.
    Kutlu H; Avcı E
    Sensors (Basel); 2019 Apr; 19(9):. PubMed ID: 31035406
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Electromyographic fatigue thresholds of the superficial muscles of the quadriceps femoris.
    Housh TJ; deVries HA; Johnson GO; Housh DJ; Evans SA; Stout JR; Evetovich TK; Bradway RM
    Eur J Appl Physiol Occup Physiol; 1995; 71(2-3):131-6. PubMed ID: 7588679
    [TBL] [Abstract][Full Text] [Related]  

  • 18. sEMG wavelet-based indices predicts muscle power loss during dynamic contractions.
    González-Izal M; Rodríguez-Carreño I; Malanda A; Mallor-Giménez F; Navarro-Amézqueta I; Gorostiaga EM; Izquierdo M
    J Electromyogr Kinesiol; 2010 Dec; 20(6):1097-106. PubMed ID: 20579906
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Continuous Estimation of Knee Joint Angle Based on Surface Electromyography Using a Long Short-Term Memory Neural Network and Time-Advanced Feature.
    Ma X; Liu Y; Song Q; Wang C
    Sensors (Basel); 2020 Sep; 20(17):. PubMed ID: 32887326
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Myoeletric indices of fatigue adopting different rest intervals during leg press sets.
    Miranda H; Maia M; de Oliveira CG; Farias D; da Silva JB; Lima VP; Willardson JM; Paz GA
    J Bodyw Mov Ther; 2018 Jan; 22(1):178-183. PubMed ID: 29332743
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.