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A computational musculoskeletal arm model for assessing muscle dysfunction in chronic obstructive pulmonary disease.
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- المؤلفون: Asghari M;Asghari M; Peña M; Peña M; Ruiz M; Ruiz M; Johnson H; Johnson H; Ehsani H; Ehsani H; Ehsani H; Toosizadeh N; Toosizadeh N; Toosizadeh N; Toosizadeh N
- المصدر:
Medical & biological engineering & computing [Med Biol Eng Comput] 2023 Sep; Vol. 61 (9), pp. 2241-2254. Date of Electronic Publication: 2023 Mar 27.- نوع النشر :
Journal Article- اللغة:
English - المصدر:
- معلومة اضافية
- المصدر: Publisher: Springer Country of Publication: United States NLM ID: 7704869 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1741-0444 (Electronic) Linking ISSN: 01400118 NLM ISO Abbreviation: Med Biol Eng Comput Subsets: MEDLINE
- بيانات النشر: Publication: New York, NY : Springer
Original Publication: Stevenage, Eng., Peregrinus. - الموضوع:
- نبذة مختصرة : Computational models have been used extensively to assess diseases and disabilities effects on musculoskeletal system dysfunction. In the current study, we developed a two degree-of-freedom subject-specific second-order task-specific arm model for characterizing upper-extremity function (UEF) to assess muscle dysfunction due to chronic obstructive pulmonary disease (COPD). Older adults (65 years or older) with and without COPD and healthy young control participants (18 to 30 years) were recruited. First, we evaluated the musculoskeletal arm model using electromyography (EMG) data. Second, we compared the computational musculoskeletal arm model parameters along with EMG-based time lag and kinematics parameters (such as elbow angular velocity) between participants. The developed model showed strong cross-correlation with EMG data for biceps (0.905, 0.915) and moderate cross-correlation for triceps (0.717, 0.672) within both fast and normal pace tasks among older adults with COPD. We also showed that parameters obtained from the musculoskeletal model were significantly different between COPD and healthy participants. On average, higher effect sizes were achieved for parameters obtained from the musculoskeletal model, especially for co-contraction measures (effect size = 1.650 ± 0.606, p < 0.001), which was the only parameter that showed significant differences between all pairwise comparisons across the three groups. These findings suggest that studying the muscle performance and co-contraction, may provide better information regarding neuromuscular deficiencies compared to kinematics data. The presented model has potential for assessing functional capacity and studying longitudinal outcomes in COPD.
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- Contributed Indexing: Keywords: COPD exacerbation; COPD longitudinal outcomes; Computational arm model; Muscle co-contraction; Upper-extremity function tasks
- الموضوع: Date Created: 20230327 Date Completed: 20230811 Latest Revision: 20230811
- الموضوع: 20240628
- الرقم المعرف: 10.1007/s11517-023-02823-0
- الرقم المعرف: 36971957
- المصدر:
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