Speed-dependent modulations of muscle modules in the gait of people with radiographical and asymptomatic knee osteoarthritis and elderly controls: Case-control pilot study

被引:1
作者
Takiyama, Ken [1 ]
Kubota, Keisuke [2 ]
Yokoyama, Hikaru [3 ]
Kanemura, Naohiko [4 ]
机构
[1] Tokyo Univ Agr & Technol, Dept Elect Engn & Comp Sci, Nakacho, Tokyo, Japan
[2] Saitama Prefectural Univ, Res & Dev Ctr, Saitama, Japan
[3] Tokyo Univ Agr & Technol, Div Adv Hlth Sci, Nakacho, Tokyo, Japan
[4] Saitama Prefectural Univ, Grad Course Hlth & Social Serv, Saitama, Japan
关键词
WALKING SPEED; SYNERGIES; PATTERNS; SEVERITY; SET; HIP;
D O I
10.1016/j.jbiomech.2024.112194
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
This study investigates the muscle modules involved in the increase of walking speed in radiographical and asymptomatic knee osteoarthritis (KOA) patients using tensor decomposition. The human body possesses redundancy, which is the property to achieve desired movements with more degrees of freedom than necessary. The muscle module hypothesis is a proposed solution to this redundancy. While previous studies have examined the pathological muscle activity modulations in musculoskeletal diseases such as KOA, they have focused on single muscles rather than muscle modules. Moreover, most studies have only examined the gait of KOA patients at a single speed, leaving the way in which gait speed affects gait parameters in KOA patients unclear. Assessing this influence is crucial for determining appropriate gait speed and understanding why preferred gait speed decreases in KOA patients. In this study, we apply tensor decomposition to muscle activity data to extract muscle modules in KOA patients and elderly controls during walking at different speeds. We found a muscle module comprising hip adductors and back muscles that activate bimodally in a gait cycle, specific to KOA patients when they increase their walking speed. These findings may provide valuable insights for rehabilitation for KOA patients.
引用
收藏
页数:8
相关论文
共 43 条
  • [1] A Systems View of Risk Factors for Knee Osteoarthritis Reveals Insights into the Pathogenesis of the Disease
    Andriacchi, Thomas P.
    Favre, Julien
    Erhart-Hledik, J. C.
    Chu, Constance R.
    [J]. ANNALS OF BIOMEDICAL ENGINEERING, 2015, 43 (02) : 376 - 387
  • [2] Angst F, 2005, J RHEUMATOL, V32, P1324
  • [3] Gait and neuromuscular pattern changes are associated with differences in knee osteoarthritis severity levels
    Astephen, Janie L.
    Deluzio, Kevin J.
    Caldwell, Graham E.
    Dunbar, Michael J.
    Hubley-Kozey, Cheryl L.
    [J]. JOURNAL OF BIOMECHANICS, 2008, 41 (04) : 868 - 876
  • [4] Bader B.W., 2017, MATLAB TENSOR TOOLBO
  • [5] Algorithm 862: MATLAB tensor classes for fast algorithm prototyping
    Bader, Brett W.
    Kolda, Tamara G.
    [J]. ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2006, 32 (04): : 635 - 653
  • [6] The influence of walking speed on gait parameters in healthy people and in patients with osteoarthritis
    Bejek, Zoltan
    Paroczai, Robert
    Illyes, Arpad
    Kiss, Rita M.
    [J]. KNEE SURGERY SPORTS TRAUMATOLOGY ARTHROSCOPY, 2006, 14 (07) : 612 - 622
  • [7] BERNSTEIN N., 1967
  • [8] COMPUTATIONS UNDERLYING THE EXECUTION OF MOVEMENT - A BIOLOGICAL PERSPECTIVE
    BIZZI, E
    MUSSAIVALDI, FA
    GISZTER, S
    [J]. SCIENCE, 1991, 253 (5017) : 287 - 291
  • [9] Midbrain circuits that set locomotor speed and gait selection
    Caggiano, V.
    Leiras, R.
    Goni-Erro, H.
    Masini, D.
    Bellardita, C.
    Bouvier, J.
    Caldeira, V.
    Fisone, G.
    Kiehn, O.
    [J]. NATURE, 2018, 553 (7689) : 455 - +
  • [10] Motor patterns in human walking and running
    Cappellini, G.
    Ivanenko, Y. P.
    Poppele, R. E.
    Lacquaniti, F.
    [J]. JOURNAL OF NEUROPHYSIOLOGY, 2006, 95 (06) : 3426 - 3437