Literature DB >> 28092813

Walking mechanics for patellofemoral pain subjects with similar self-reported pain levels can differ based upon neuromuscular activation.

Matthew K Seeley1, S Jun Son2, Hyunsoo Kim3, J Ty Hopkins4.   

Abstract

Patellofemoral pain (PFP) is often studied on subjects who are classified using only self-reported data. Neuromuscular activation influences movement mechanics for PFP subjects, but is not likely to be self-reported. We compared lower-extremity mechanics, during a common movement (walking), between two subdivisions of a group of PFP subjects that were similar, based on common self-report tools, but different, based on a common objective measure of quadriceps activation. Our intent was to highlight the importance of objectively considering neuromuscular activation when researching PFP movement mechanics. Thirty similar PFP research subjects (based on four common self-report tools) were divided into two subdivisions, based on different quadriceps central activation ratios (CAR): a quadriceps deficit (QD; CAR <0.95) group and a no quadriceps deficit (NQD; CAR ≥0.95) group. All subjects in both groups performed five walking trials, while common mechanical characteristics were measured: 3D ground reaction force, and 3D joint kinematics and kinetics. Functional statistics were used to compare mechanical characteristics between the groups across the entire stance phase of gait (α=0.05). Numerous differences were found between the two groups for ground reaction force, and joint kinematics and kinetics. For example, the NQD group exhibited 5% greater vertical ground reaction force at peak impact, and 5% less vertical ground reaction force during the unloading portion of stance, relative to the QD group. The results indicate that when researching movement mechanics associated with PFP, it is important to consider objectively-measured neuromuscular activation characteristics that are not likely to be self-reported by PFP subjects.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Ground reaction force; Kinematics; Kinetics; Patellofemoral pain; Quadriceps activation ratio

Mesh:

Year:  2017        PMID: 28092813     DOI: 10.1016/j.gaitpost.2017.01.005

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  1 in total

1.  Functional Data Analyses of Gait Data Measured Using In-Shoe Sensors.

Authors:  Jihui Lee; Gen Li; William F Christensen; Gavin Collins; Matthew Seeley; Anton E Bowden; David T Fullwood; Jeff Goldsmith
Journal:  Stat Biosci       Date:  2018-12-07
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.