病理歩行における筋力分担の逆最適制御
Inverse Optimal Control of Muscle Force Sharing During Pathological Gait
脳卒中患者の歩行時の筋力分担を逆最適制御で解析し、最適な目的関数が個人・脚ごとに異なることを示した。麻痺側では筋パワー最小化、非麻痺側では筋活性最小化が重要である可能性を報告。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Filip Bečanović, Vincent Bonnet, Kosta Jovanović, Samer Mohammed, Raphaël Dumas
分類: physics.med-ph, cs.RO, cs.SY, eess.SY, math.OC
原文アブストラクト
Muscle force sharing is typically resolved by minimizing a specific objective function to approximate neural control strategies. An inverse optimal control approach was applied to identify the "best" objective function, among a positive linear combination of basis objective functions, associated with the gait of two post-stroke males, one high-functioning (subject S1) and one low-functioning (subject S2). It was found that the "best" objective function is subject- and leg-specific. No single function works universally well, yet the best options are usually differently weighted combinations of muscle activation- and power-minimization. Subject-specific inverse optimal control models performed best on their respective limbs (\textbf{RMSE 178/213 N, CC 0.71/0.61} for non-paretic and paretic legs of S1; \textbf{RMSE 205/165 N, CC 0.88/0.85} for respective legs of S2), but cross-subject generalization was poor, particularly for paretic legs. Moreover, minimizing the root mean square of muscle power emerged as important for paretic limbs, while minimizing activation-based functions dominated for non-paretic limbs. This may suggest different neural control strategies between affected and unaffected sides, possibly altered by the presence of spasticity. Among the 15 considered objective functions commonly used in inverse dynamics-based computations, the root mean square of muscle power was the only one explicitly incorporating muscle velocity, leading to a possible model for spasticity in the paretic limbs. Although this objective function has been rarely used, it may be relevant for modeling pathological gait, such as post-stroke gait.
