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Journal Abstract Search

126 related items for PubMed ID: 39006209

  • 1. Prediction of joint moments from kinematics using machine learning in children with congenital talipes equino varus and typically developing peers.
    Kothurkar R, Gad M, Padate A, Rathod C, Bhaskar A, Lekurwale R, Rose J.
    J Orthop; 2024 Nov; 57():83-89. PubMed ID: 39006209
    [Abstract] [Full Text] [Related]

  • 2. Machine learning-based prediction of joint moments based on kinematics in patients with cerebral palsy.
    Ozates ME, Karabulut D, Salami F, Wolf SI, Arslan YZ.
    J Biomech; 2023 Jun; 155():111668. PubMed ID: 37276682
    [Abstract] [Full Text] [Related]

  • 3. 3D gait analysis in children using wearable sensors: feasibility of predicting joint kinematics and kinetics with personalized machine learning models and inertial measurement units.
    Mohammadi Moghadam S, Ortega Auriol P, Yeung T, Choisne J.
    Front Bioeng Biotechnol; 2024 Jun; 12():1372669. PubMed ID: 38572359
    [Abstract] [Full Text] [Related]

  • 4. Surgical versus Ponseti approach for the management of CTEV: a comparative study.
    Duffy CM, Salazar JJ, Humphreys L, McDowell BC.
    J Pediatr Orthop; 2013 Jun; 33(3):326-32. PubMed ID: 23482272
    [Abstract] [Full Text] [Related]

  • 5. Plantar pressures in children with congenital talipes equino varus--a comparison between surgical management and the Ponseti technique.
    Salazar-Torres JJ, McDowell BC, Humphreys LD, Duffy CM.
    Gait Posture; 2014 Jun; 39(1):321-7. PubMed ID: 23973353
    [Abstract] [Full Text] [Related]

  • 6. Management of Congenital Talipes Equino Varus (CTEV) by Ponseti Casting Technique in Neonates: Our Experience.
    Saif Ullah M, Md Noor-Ul Ferdous K, Shahjahan M, Abu Sayed S.
    J Neonatal Surg; 2013 Jun; 2(2):17. PubMed ID: 26023437
    [Abstract] [Full Text] [Related]

  • 7. Physiotherapy management of an infant with Bilateral Congenital Talipes Equino varus.
    Ezeukwu AO, Maduagwu SM.
    Afr Health Sci; 2011 Sep; 11(3):444-8. PubMed ID: 22275937
    [Abstract] [Full Text] [Related]

  • 8. 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]

  • 9. Estimation of lower-limb sagittal joint moments during gait using vertical ground reaction force.
    Inai T, Takabayashi T.
    J Biomech; 2022 Dec 01; 145():111389. PubMed ID: 36410202
    [Abstract] [Full Text] [Related]

  • 10. Prediction of ground reaction forces during gait based on kinematics and a neural network model.
    Oh SE, Choi A, Mun JH.
    J Biomech; 2013 Sep 27; 46(14):2372-80. PubMed ID: 23962528
    [Abstract] [Full Text] [Related]

  • 11. Comparison of kinematics and joint moments calculations for lower limbs during gait using markerless and marker-based motion capture.
    Huang T, Ruan M, Huang S, Fan L, Wu X.
    Front Bioeng Biotechnol; 2024 Sep 27; 12():1280363. PubMed ID: 38532880
    [Abstract] [Full Text] [Related]

  • 12. Multi-segment foot kinematics during gait in children with spastic cerebral palsy.
    Schallig W, Piening M, Quirijnen L, Witbreuk MM, Buizer AI, van der Krogt MM.
    Gait Posture; 2024 May 27; 110():144-149. PubMed ID: 38608379
    [Abstract] [Full Text] [Related]

  • 13. Prediction of ground reaction force and joint moments based on optical motion capture data during gait.
    Mundt M, Koeppe A, David S, Bamer F, Potthast W, Markert B.
    Med Eng Phys; 2020 Dec 27; 86():29-34. PubMed ID: 33261730
    [Abstract] [Full Text] [Related]

  • 14. 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 27; 144():111301. PubMed ID: 36201910
    [Abstract] [Full Text] [Related]

  • 15. Minimum incidence of congenital talipes equino-varus (CTEV) and post treatment evaluation of residual deformities in a population in Zimbabwe.
    Madzivire D, Useh D, Mashegede PT, Siziya S.
    Cent Afr J Med; 2002 Nov 27; 48(3-4):33-8. PubMed ID: 12971155
    [Abstract] [Full Text] [Related]

  • 16. A comparison of machine learning models' accuracy in predicting lower-limb joints' kinematics, kinetics, and muscle forces from wearable sensors.
    Moghadam SM, Yeung T, Choisne J.
    Sci Rep; 2023 Mar 28; 13(1):5046. PubMed ID: 36977706
    [Abstract] [Full Text] [Related]

  • 17. A probabilistic method to estimate gait kinetics in the absence of ground reaction force measurements.
    Tanghe K, Afschrift M, Jonkers I, De Groote F, De Schutter J, Aertbeliën E.
    J Biomech; 2019 Nov 11; 96():109327. PubMed ID: 31526586
    [Abstract] [Full Text] [Related]

  • 18. A comparison of running kinematics and kinetics in children with and without developmental coordination disorder.
    Chia LC, Licari MK, Guelfi KJ, Reid SL.
    Gait Posture; 2013 Jun 11; 38(2):264-9. PubMed ID: 23266248
    [Abstract] [Full Text] [Related]

  • 19. Comparison of sagittal plane gait characteristics between the overground and treadmill approach for gait analysis in typically developing children.
    Senden R, Marcellis R, Meijer K, Willems P, Lenssen T, Staal H, Janssen Y, Groen V, Vermeulen RJ, Witlox M.
    PeerJ; 2022 Jun 11; 10():e13752. PubMed ID: 35898943
    [Abstract] [Full Text] [Related]

  • 20. Analysis OF C677T polymorphism in methylene tetrahydrofolate reductase (MTHFR) gene as a risk factor for congenital talipes equino varus (CTEV).
    Pandey V, Chaturvedi P, Gehlot H, Ali Mahdi A, Singh A, Mahendra M.
    J Clin Orthop Trauma; 2021 Apr 11; 15():33-36. PubMed ID: 33717913
    [Abstract] [Full Text] [Related]

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