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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

310 related items for PubMed ID: 33873117

  • 1. 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]

  • 2. Concurrent assessment of gait kinematics using marker-based and markerless motion capture.
    Kanko RM, Laende EK, Davis EM, Selbie WS, Deluzio KJ.
    J Biomech; 2021 Oct 11; 127():110665. PubMed ID: 34380101
    [Abstract] [Full Text] [Related]

  • 3. Markerless motion capture provides repeatable gait outcomes in patients with knee osteoarthritis.
    Outerleys J, Mihic A, Keller V, Laende E, Deluzio K.
    J Biomech; 2024 May 11; 168():112115. PubMed ID: 38663111
    [Abstract] [Full Text] [Related]

  • 4. Clothing condition does not affect meaningful clinical interpretation in markerless motion capture.
    Keller VT, Outerleys JB, Kanko RM, Laende EK, Deluzio KJ.
    J Biomech; 2022 Aug 11; 141():111182. PubMed ID: 35749889
    [Abstract] [Full Text] [Related]

  • 5. Inter-trial variability is higher in 3D markerless compared to marker-based motion capture: Implications for data post-processing and analysis.
    Horsak B, Prock K, Krondorfer P, Siragy T, Simonlehner M, Dumphart B.
    J Biomech; 2024 Mar 11; 166():112049. PubMed ID: 38493576
    [Abstract] [Full Text] [Related]

  • 6. Applications of markerless motion capture in gait recognition.
    Sandau M.
    Dan Med J; 2016 Mar 11; 63(3):. PubMed ID: 26931198
    [Abstract] [Full Text] [Related]

  • 7. Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system.
    Kanko RM, Laende EK, Strutzenberger G, Brown M, Selbie WS, DePaul V, Scott SH, Deluzio KJ.
    J Biomech; 2021 Jun 09; 122():110414. PubMed ID: 33915475
    [Abstract] [Full Text] [Related]

  • 8. Repeatability and minimal detectable change including clothing effects for smartphone-based 3D markerless motion capture.
    Horsak B, Kainz H, Dumphart B.
    J Biomech; 2024 Oct 09; 175():112281. PubMed ID: 39163799
    [Abstract] [Full Text] [Related]

  • 9. On the reliability of single-camera markerless systems for overground gait monitoring.
    Boldo M, Di Marco R, Martini E, Nardon M, Bertucco M, Bombieri N.
    Comput Biol Med; 2024 Mar 09; 171():108101. PubMed ID: 38340440
    [Abstract] [Full Text] [Related]

  • 10. Accuracy and repeatability of joint angles measured using a single camera markerless motion capture system.
    Schmitz A, Ye M, Shapiro R, Yang R, Noehren B.
    J Biomech; 2014 Jan 22; 47(2):587-91. PubMed ID: 24315287
    [Abstract] [Full Text] [Related]

  • 11. Absolute Reliability of Gait Parameters Acquired With Markerless Motion Capture in Living Domains.
    Riazati S, McGuirk TE, Perry ES, Sihanath WB, Patten C.
    Front Hum Neurosci; 2022 Jan 22; 16():867474. PubMed ID: 35782037
    [Abstract] [Full Text] [Related]

  • 12. Comparison of markerless and marker-based motion capture of gait kinematics in individuals with cerebral palsy and chronic stroke: A case study series.
    Steffensen EA, Magalhães F, Knarr BA, Kingston DC.
    Res Sq; 2023 Feb 08. PubMed ID: 36798184
    [Abstract] [Full Text] [Related]

  • 13. Markerless motion capture estimates of lower extremity kinematics and kinetics are comparable to marker-based across 8 movements.
    Song K, Hullfish TJ, Scattone Silva R, Silbernagel KG, Baxter JR.
    J Biomech; 2023 Aug 08; 157():111751. PubMed ID: 37552921
    [Abstract] [Full Text] [Related]

  • 14. Comparison of markerless and marker-based motion capture technologies through simultaneous data collection during gait: proof of concept.
    Ceseracciu E, Sawacha Z, Cobelli C.
    PLoS One; 2014 Aug 08; 9(3):e87640. PubMed ID: 24595273
    [Abstract] [Full Text] [Related]

  • 15. A comparison of three-dimensional kinematics between markerless and marker-based motion capture in overground gait.
    Ripic Z, Nienhuis M, Signorile JF, Best TM, Jacobs KA, Eltoukhy M.
    J Biomech; 2023 Oct 08; 159():111793. PubMed ID: 37725886
    [Abstract] [Full Text] [Related]

  • 16. Concurrent validity of smartphone-based markerless motion capturing to quantify lower-limb joint kinematics in healthy and pathological gait.
    Horsak B, Eichmann A, Lauer K, Prock K, Krondorfer P, Siragy T, Dumphart B.
    J Biomech; 2023 Oct 08; 159():111801. PubMed ID: 37738945
    [Abstract] [Full Text] [Related]

  • 17. Comparison of kinematics between Theia markerless and conventional marker-based gait analysis in clinical patients.
    Wren TAL, Isakov P, Rethlefsen SA.
    Gait Posture; 2023 Jul 08; 104():9-14. PubMed ID: 37285635
    [Abstract] [Full Text] [Related]

  • 18. Inclusion of a skeletal model partly improves the reliability of lower limb joint angles derived from a markerless depth camera.
    Collings TJ, Devaprakash D, Pizzolato C, Lloyd DG, Barrett RS, Lenton GK, Thomeer LT, Bourne MN.
    J Biomech; 2024 Jun 08; 170():112160. PubMed ID: 38824704
    [Abstract] [Full Text] [Related]

  • 19. 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 Jun 08; 12():1280363. PubMed ID: 38532880
    [Abstract] [Full Text] [Related]

  • 20. Pose2Sim: An End-to-End Workflow for 3D Markerless Sports Kinematics-Part 2: Accuracy.
    Pagnon D, Domalain M, Reveret L.
    Sensors (Basel); 2022 Apr 01; 22(7):. PubMed ID: 35408326
    [Abstract] [Full Text] [Related]

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