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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

473 related items for PubMed ID: 31465977

  • 1. IMU, sEMG, or their cross-correlation and temporal similarities: Which signal features detect lateral compensatory balance reactions more accurately?
    Nouredanesh M, Tung J.
    Comput Methods Programs Biomed; 2019 Dec; 182():105003. PubMed ID: 31465977
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  • 2. Automated Detection of Multidirectional Compensatory Balance Reactions: A Step Towards Tracking Naturally Occurring Near Falls.
    Nouredanesh M, Gordt K, Schwenk M, Tung J.
    IEEE Trans Neural Syst Rehabil Eng; 2020 Feb; 28(2):478-487. PubMed ID: 31794400
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  • 3. Detection of compensatory balance responses using wearable electromyography sensors for fall-risk assessment.
    Nouredanesh M, Kukreja SL, Tung J.
    Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():1680-1683. PubMed ID: 28268650
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  • 4. Towards an Inertial Sensor-Based Wearable Feedback System for Patients after Total Hip Arthroplasty: Validity and Applicability for Gait Classification with Gait Kinematics-Based Features.
    Teufl W, Taetz B, Miezal M, Lorenz M, Pietschmann J, Jöllenbeck T, Fröhlich M, Bleser G.
    Sensors (Basel); 2019 Nov 16; 19(22):. PubMed ID: 31744141
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  • 5. Accurate recognition of lower limb ambulation mode based on surface electromyography and motion data using machine learning.
    Zhou B, Wang H, Hu F, Feng N, Xi H, Zhang Z, Tang H.
    Comput Methods Programs Biomed; 2020 Sep 16; 193():105486. PubMed ID: 32402846
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  • 6. Enhanced Performance for Multi-Forearm Movement Decoding Using Hybrid IMU-sEMG Interface.
    Shahzad W, Ayaz Y, Khan MJ, Naseer N, Khan M.
    Front Neurorobot; 2019 Sep 16; 13():43. PubMed ID: 31333441
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  • 7. sEMG-signal and IMU sensor-based gait sub-phase detection and prediction using a user-adaptive classifier.
    Ryu J, Lee BH, Maeng J, Kim DH.
    Med Eng Phys; 2019 Jul 16; 69():50-57. PubMed ID: 31153877
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  • 10. Machine learning algorithms based on signals from a single wearable inertial sensor can detect surface- and age-related differences in walking.
    Hu B, Dixon PC, Jacobs JV, Dennerlein JT, Schiffman JM.
    J Biomech; 2018 Apr 11; 71():37-42. PubMed ID: 29452755
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  • 11. Technology in Strength and Conditioning: Assessing Bodyweight Squat Technique With Wearable Sensors.
    OʼReilly MA, Whelan DF, Ward TE, Delahunt E, Caulfield BM.
    J Strength Cond Res; 2017 Aug 11; 31(8):2303-2312. PubMed ID: 28731981
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  • 12. Influence of IMU position and orientation placement errors on ground reaction force estimation.
    Tan T, Chiasson DP, Hu H, Shull PB.
    J Biomech; 2019 Dec 03; 97():109416. PubMed ID: 31630774
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  • 13. Detecting compensatory movements of stroke survivors using pressure distribution data and machine learning algorithms.
    Cai S, Li G, Zhang X, Huang S, Zheng H, Ma K, Xie L.
    J Neuroeng Rehabil; 2019 Nov 04; 16(1):131. PubMed ID: 31684970
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  • 19. Use of a wearable electromyography armband to detect lift-lower tasks and classify hand loads.
    Taori S, Lim S.
    Appl Ergon; 2024 Sep 04; 119():104285. PubMed ID: 38797013
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