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Journal Abstract Search

312 related items for PubMed ID: 34502766

  • 21. Measuring joint kinematics of treadmill walking and running: Comparison between an inertial sensor based system and a camera-based system.
    Nüesch C, Roos E, Pagenstert G, Mündermann A.
    J Biomech; 2017 May 24; 57():32-38. PubMed ID: 28366438
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  • 22. Inertial Sensor-to-Segment Calibration for Accurate 3D Joint Angle Calculation for Use in OpenSim.
    Di Raimondo G, Vanwanseele B, van der Have A, Emmerzaal J, Willems M, Killen BA, Jonkers I.
    Sensors (Basel); 2022 Apr 24; 22(9):. PubMed ID: 35590949
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  • 25. Lower Body Kinematics Monitoring in Running Using Fabric-Based Wearable Sensors and Deep Convolutional Neural Networks.
    Gholami M, Rezaei A, Cuthbert TJ, Napier C, Menon C.
    Sensors (Basel); 2019 Dec 03; 19(23):. PubMed ID: 31816931
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  • 28. Using Inertial Measurement Unit Sensor Single Axis Rotation Angles for Knee and Hip Flexion Angle Calculations During Gait.
    Oliveira N, Park J, Barrance P.
    IEEE J Transl Eng Health Med; 2023 Dec 03; 11():80-86. PubMed ID: 36704243
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  • 29. A Computationally Efficient Lower Limb Finite Element Musculoskeletal Framework Directly Driven Solely by Inertial Measurement Unit Sensors.
    Wang S, Hase K, Ota S.
    J Biomech Eng; 2022 May 01; 144(5):. PubMed ID: 34897395
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  • 31. Validity of inertial sensor based 3D joint kinematics of static and dynamic sport and physiotherapy specific movements.
    Teufl W, Miezal M, Taetz B, Fröhlich M, Bleser G.
    PLoS One; 2019 May 01; 14(2):e0213064. PubMed ID: 30817787
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  • 32. A Comparison of the Conventional PiG Marker Method Versus a Cluster-Based Model when recording Gait Kinematics in Trans-Tibial Prosthesis Users and the Implications for Future IMU Gait Analysis.
    Samala M, Rowe P, Rattanakoch J, Guerra G.
    Sensors (Basel); 2020 Feb 25; 20(5):. PubMed ID: 32106577
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  • 33. Generative deep learning applied to biomechanics: A new augmentation technique for motion capture datasets.
    Bicer M, Phillips ATM, Melis A, McGregor AH, Modenese L.
    J Biomech; 2022 Nov 25; 144():111301. PubMed ID: 36201910
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  • 34. Explainable Deep-Learning-Based Gait Analysis of Hip-Knee Cyclogram for the Prediction of Adolescent Idiopathic Scoliosis Progression.
    Kim YG, Kim S, Park JH, Yang S, Jang M, Yun YJ, Cho JS, You S, Jang SH.
    Sensors (Basel); 2024 Jul 12; 24(14):. PubMed ID: 39065902
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  • 35. Validation of inertial measurement units with optical tracking system in patients operated with Total hip arthroplasty.
    Zügner R, Tranberg R, Timperley J, Hodgins D, Mohaddes M, Kärrholm J.
    BMC Musculoskelet Disord; 2019 Feb 06; 20(1):52. PubMed ID: 30727979
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  • 37. A subject-specific musculoskeletal modeling framework to predict in vivo mechanics of total knee arthroplasty.
    Marra MA, Vanheule V, Fluit R, Koopman BH, Rasmussen J, Verdonschot N, Andersen MS.
    J Biomech Eng; 2015 Feb 01; 137(2):020904. PubMed ID: 25429519
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  • 38. Lower Extremity Inverse Kinematics Results Differ Between Inertial Measurement Unit- and Marker-Derived Gait Data.
    Hafer JF, Mihy JA, Hunt A, Zernicke RF, Johnson RT.
    J Appl Biomech; 2023 Jun 01; 39(3):133-142. PubMed ID: 37024103
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  • 39. Continuous Estimation of Human Knee Joint Angles by Fusing Kinematic and Myoelectric Signals.
    Sun N, Cao M, Chen Y, Chen Y, Wang J, Wang Q, Chen X, Liu T.
    IEEE Trans Neural Syst Rehabil Eng; 2022 Jun 01; 30():2446-2455. PubMed ID: 35994557
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  • 40. A Femoral Clamp to Reduce Soft Tissue Artifact: Accuracy and Reliability in Measuring Three-Dimensional Knee Kinematics During Gait.
    Ding Z, Güdel M, Smith SHL, Ademefun RA, Bull AMJ.
    J Biomech Eng; 2020 Apr 01; 142(4):. PubMed ID: 31596924
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