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.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

167 related items for PubMed ID: 36201910

  • 21. Data Augmentation for Deep-Learning-Based Multiclass Structural Damage Detection Using Limited Information.
    Dunphy K, Fekri MN, Grolinger K, Sadhu A.
    Sensors (Basel); 2022 Aug 18; 22(16):. PubMed ID: 36015955
    [Abstract] [Full Text] [Related]

  • 22. Inter-session repeatability of markerless motion capture gait kinematics.
    Kanko RM, Laende E, Selbie WS, Deluzio KJ.
    J Biomech; 2021 May 24; 121():110422. PubMed ID: 33873117
    [Abstract] [Full Text] [Related]

  • 23. Estimation of Vertical Ground Reaction Forces and Sagittal Knee Kinematics During Running Using Three Inertial Sensors.
    Wouda FJ, Giuberti M, Bellusci G, Maartens E, Reenalda J, van Beijnum BF, Veltink PH.
    Front Physiol; 2018 May 24; 9():218. PubMed ID: 29623042
    [Abstract] [Full Text] [Related]

  • 24. Enhancing biomechanical machine learning with limited data: generating realistic synthetic posture data using generative artificial intelligence.
    Dindorf C, Dully J, Konradi J, Wolf C, Becker S, Simon S, Huthwelker J, Werthmann F, Kniepert J, Drees P, Betz U, Fröhlich M.
    Front Bioeng Biotechnol; 2024 May 24; 12():1350135. PubMed ID: 38419724
    [Abstract] [Full Text] [Related]

  • 25. Spring-loaded inverted pendulum modeling improves neural network estimation of ground reaction forces.
    Kim B, Lim H, Park S.
    J Biomech; 2020 Dec 02; 113():110069. PubMed ID: 33142204
    [Abstract] [Full Text] [Related]

  • 26. Generating synthetic gait patterns based on benchmark datasets for controlling prosthetic legs.
    Kim M, Hargrove LJ.
    J Neuroeng Rehabil; 2023 Sep 04; 20(1):115. PubMed ID: 37667313
    [Abstract] [Full Text] [Related]

  • 27. Deep neural network approach for estimating the three-dimensional human center of mass using joint angles.
    Chebel E, Tunc B.
    J Biomech; 2021 Sep 20; 126():110648. PubMed ID: 34333241
    [Abstract] [Full Text] [Related]

  • 28. Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane.
    Patel G, Mullerpatan R, Agarwal B, Shetty T, Ojha R, Shaikh-Mohammed J, Sujatha S.
    Proc Inst Mech Eng H; 2022 May 20; 236(5):686-696. PubMed ID: 35001713
    [Abstract] [Full Text] [Related]

  • 29. Prediction of lower limb joint angles and moments during gait using artificial neural networks.
    Mundt M, Thomsen W, Witter T, Koeppe A, David S, Bamer F, Potthast W, Markert B.
    Med Biol Eng Comput; 2020 Jan 20; 58(1):211-225. PubMed ID: 31823114
    [Abstract] [Full Text] [Related]

  • 30. A Comparison of Three Neural Network Approaches for Estimating Joint Angles and Moments from Inertial Measurement Units.
    Mundt M, Johnson WR, Potthast W, Markert B, Mian A, Alderson J.
    Sensors (Basel); 2021 Jul 01; 21(13):. PubMed ID: 34283080
    [Abstract] [Full Text] [Related]

  • 31. BlazePose-Seq2Seq: Leveraging Regular RGB Cameras for Robust Gait Assessment.
    Hulleck AA, AlShehhi A, El Rich M, Khan R, Katmah R, Mohseni M, Arjmand N, Khalaf K.
    IEEE Trans Neural Syst Rehabil Eng; 2024 Jul 01; 32():1715-1724. PubMed ID: 38648155
    [Abstract] [Full Text] [Related]

  • 32. A generative flow-based model for volumetric data augmentation in 3D deep learning for computed tomographic colonography.
    Uemura T, Näppi JJ, Ryu Y, Watari C, Kamiya T, Yoshida H.
    Int J Comput Assist Radiol Surg; 2021 Jan 01; 16(1):81-89. PubMed ID: 33150471
    [Abstract] [Full Text] [Related]

  • 33. Improving Speech Emotion Recognition With Adversarial Data Augmentation Network.
    Yi L, Mak MW.
    IEEE Trans Neural Netw Learn Syst; 2022 Jan 01; 33(1):172-184. PubMed ID: 33035171
    [Abstract] [Full Text] [Related]

  • 34. A Deep Learning Model for Markerless Pose Estimation Based on Keypoint Augmentation: What Factors Influence Errors in Biomechanical Applications?
    Ruescas-Nicolau AV, Medina-Ripoll E, de Rosario H, Sanchiz Navarro J, Parrilla E, Juan Lizandra MC.
    Sensors (Basel); 2024 Mar 17; 24(6):. PubMed ID: 38544186
    [Abstract] [Full Text] [Related]

  • 35. Applications and limitations of current markerless motion capture methods for clinical gait biomechanics.
    Wade L, Needham L, McGuigan P, Bilzon J.
    PeerJ; 2022 Mar 17; 10():e12995. PubMed ID: 35237469
    [Abstract] [Full Text] [Related]

  • 36. DeepBBWAE-Net: A CNN-RNN Based Deep SuperLearner for Estimating Lower Extremity Sagittal Plane Joint Kinematics Using Shoe-Mounted IMU Sensors in Daily Living.
    Hossain MSB, Dranetz J, Choi H, Guo Z.
    IEEE J Biomed Health Inform; 2022 Aug 17; 26(8):3906-3917. PubMed ID: 35385394
    [Abstract] [Full Text] [Related]

  • 37. Combining Recurrent Neural Networks and Adversarial Training for Human Motion Synthesis and Control.
    Wang Z, Chai J, Xia S.
    IEEE Trans Vis Comput Graph; 2021 Jan 17; 27(1):14-28. PubMed ID: 31502979
    [Abstract] [Full Text] [Related]

  • 38. Using Deep Learning Models to Predict Prosthetic Ankle Torque.
    Prasanna C, Realmuto J, Anderson A, Rombokas E, Klute G.
    Sensors (Basel); 2023 Sep 06; 23(18):. PubMed ID: 37765769
    [Abstract] [Full Text] [Related]

  • 39. Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks.
    Sandfort V, Yan K, Pickhardt PJ, Summers RM.
    Sci Rep; 2019 Nov 15; 9(1):16884. PubMed ID: 31729403
    [Abstract] [Full Text] [Related]

  • 40. Estimating Lower Extremity Running Gait Kinematics with a Single Accelerometer: A Deep Learning Approach.
    Gholami M, Napier C, Menon C.
    Sensors (Basel); 2020 May 22; 20(10):. PubMed ID: 32455927
    [Abstract] [Full Text] [Related]

    Page: [Previous] [Next] [New Search]
    of 9.