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    Home > Active Ingredient News > Study of Nervous System > IEEE trans: Application of muscle synergy analysis in gait in patients with knee osteoarthritis

    IEEE trans: Application of muscle synergy analysis in gait in patients with knee osteoarthritis

    • Last Update: 2021-05-08
    • Source: Internet
    • Author: User
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    As we age, abnormalities in the neuromuscular system include loss of muscle strength.


    In addition, some studies have reported the relationship between aging and increased co-contraction of muscles.


    This article proposes two purposes: (1) To clarify whether the elderly and patients with knee arthritis have lower muscle synergy in gait; (2) Through detailed analysis of muscle synergy components, to clarify the characteristic muscle synergy of knee arthritis effect.


    This article proposes two purposes: (1) To clarify whether the elderly and patients with knee arthritis have lower muscle synergy in gait; (2) Through detailed analysis of muscle synergy components, to clarify the characteristic muscle synergy of knee arthritis effect.


    diagnosis

    The number of muscle modules in the EC group (2-3) and KOA (2-3) group was significantly lower than that in the YC group (3-4), which reflects the fusion of late swing and early standing modules.


    Muscle Synergy Module

    Muscle synergy analysis may help to explore the characteristics of other musculoskeletal diseases in future research, focusing on abnormal components in muscle activity.


    Muscle synergy analysis may help to explore the characteristics of other musculoskeletal diseases in future research, focusing on abnormal components in muscle activity.


    K.
    Kubotaet al .
    , " ieee.
    org/document/9290090" target="_blank" rel="noopener">Usefulness of Muscle Synergy Analysis in Individuals With Knee Osteoarthritis During Gaitieee.
    org/document/9290090" target="_blank" rel="noopener"> Usefulness of Muscle Synergy Analysis in Individuals With Knee Osteoarthritis During Gait ," in IEEE Transactions on Neural Systems and Rehabilitation Engineering , vol.
    29, pp.
    239-248, 2021, doi: 10.
    1109/TNSRE.
    2020.
    3043831.
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