Univ. Polytechnique Hauts-de-France, LAMIH, CNRS, UMR 8201, Campus Mont Houy, 59313, Valenciennes, France.
Centre de Recherche Cerveau et Cognition (CerCO), UMR CNRS 5549, Paul Sabatier University, Toulouse, France.
J Neuroeng Rehabil. 2023 Sep 26;20(1):130. doi: 10.1186/s12984-023-01253-1.
Different research fields, such as biomechanics, medical engineering or neurosciences take part in the development of biomechanical models allowing for the estimation of individual muscle forces involved in motor action. The heterogeneity of the terminology used to describe these models according to the research field is a source of confusion and can hamper collaboration between the different fields. This paper proposes a common language based on lexical disambiguation and a synthesis of the terms used in the literature in order to facilitate the understanding of the different elements of biomechanical modeling for force estimation, without questioning the relevance of the terms used in each field or the different model components or their interest. We suggest that the description should start with an indication of whether the muscle force estimation problem is solved following the physiological movement control (from the nervous drive to the muscle force production) or in the opposite direction. Next, the suitability of the model for force production estimation at a given time or for monitoring over time should be specified. Authors should pay particular attention to the method description used to find solutions, specifying whether this is done during or after data collection, with possible method adaptations during processing. Finally, the presence of additional data must be specified by indicating whether they are used to drive, assist, or calibrate the model. Describing and classifying models in this way will facilitate the use and application in all fields where the estimation of muscle forces is of real, direct, and concrete interest.
不同的研究领域,如生物力学、医学工程或神经科学,都参与到生物力学模型的开发中,这些模型可以估计运动动作中涉及的个体肌肉力。根据研究领域,用于描述这些模型的术语的异质性是混淆的一个来源,并且可能会阻碍不同领域之间的合作。本文提出了一种基于词汇消歧和文献中使用的术语综合的通用语言,以便于理解用于力估计的生物力学建模的不同元素,而不质疑每个领域中使用的术语的相关性、不同模型组件或它们的利益。我们建议,描述应首先指出肌肉力估计问题是根据生理运动控制(从神经驱动到肌肉力产生)来解决,还是相反。接下来,应指定模型是否适合在给定时间进行力产生估计或随时间进行监测。作者应特别注意用于寻找解决方案的方法描述,指定是在数据收集期间还是之后进行,并且在处理过程中可能会进行方法调整。最后,必须指定是否存在其他数据,指出这些数据是用于驱动、辅助还是校准模型。以这种方式描述和分类模型将有助于在所有真正、直接和具体关注肌肉力估计的领域中使用和应用。