揭开人体生物力学的神秘面纱:深入了解下肢对可能引发跌倒的干扰的反应。

IF 2.9 Q2 ROBOTICS
Frontiers in Robotics and AI Pub Date : 2024-09-10 eCollection Date: 2024-01-01 DOI:10.3389/frobt.2024.1367474
Nuno Ferrete Ribeiro, Miguel Armada, João Nunes, Óscar Carvalho, Cristina P Santos
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引用次数: 0

摘要

导言:与滑倒有关的跌倒是一个令人严重关切的问题,尤其是对于老年人和步态障碍者等弱势群体而言,需要采取有效的预防措施。本手稿介绍了一项关于下肢如何对可能引发滑倒的扰动做出反应的生物力学研究,其最终目标是确定开发用于预防滑倒的可穿戴机器人系统的目标规格:我们的分析通过创新性地收集矢状面和前额面的参数,全面了解了滑倒腿和拖曳腿对滑倒扰动的自然人体生物力学反应,因为这两个平面在保持稳定和防止跌倒方面起着关键作用,从而为防止跌倒提供了新的见解。我们研究了各种外部因素,包括步速、地面倾斜度、滑倒脚和扰动强度,同时收集了包括运动学、时空参数、肌电数据以及扭矩、运动范围、每分钟旋转次数、检测和致动时间在内的各种数据集:滑动腿的髋关节、膝关节和踝关节对滑动样扰动的生物力学反应分别表现为伸展力矩、屈曲力矩和跖屈力矩。拖曳腿的反应包括髋关节屈曲、膝关节伸展和踝关节跖屈。此外,这些反应还受到步速、表面倾斜度和扰动强度的影响。我们的研究确定了髋关节、膝关节和踝关节的目标运动范围参数,分别为 85.19°、106.34° 和 95.23°。此外,髋关节的每分钟旋转次数从 17.85 到 51.10 不等,膝关节的每分钟旋转次数从 21.73 到 63.80 不等,踝关节的每分钟旋转次数从 17.52 到 57.14 不等。最后,髋关节的屈伸扭矩值估计为-3.05至3.22牛米/千克,膝关节为-1.70至2.34牛米/千克,踝关节为-2.21至0.90牛米/千克:这项研究对预防滑倒的生物力学方面提供了宝贵的见解,并为开发可穿戴机器人系统提供了信息,以提高弱势群体的安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unveiling human biomechanics: insights into lower limb responses to disturbances that can trigger a fall.

Introduction: Slip-related falls are a significant concern, particularly for vulnerable populations such as the elderly and individuals with gait disorders, necessitating effective preventive measures. This manuscript presents a biomechanical study of how the lower limbs react to perturbations that can trigger a slip-like fall, with the ultimate goal of identifying target specifications for developing a wearable robotic system for slip-like fall prevention.

Methods: Our analysis provides a comprehensive understanding of the natural human biomechanical response to slip perturbations in both slipping and trailing legs, by innovatively collecting parameters from both the sagittal and frontal plane since both play pivotal roles in maintaining stability and preventing falls and thus provide new insights to fall prevention. We investigated various external factors, including gait speed, surface inclination, slipping foot, and perturbation intensity, while collecting diverse data sets encompassing kinematic, spatiotemporal parameters, electromyographic data, as well as torque, range of motion, rotations per minute, detection, and actuation times.

Results: The biomechanical response to slip-like perturbations by the hips, knees, and ankles of the slipping leg was characterized by extension, flexion, and plantarflexion moments, respectively. In the trailing leg, responses included hip flexion, knee extension, and ankle plantarflexion. Additionally, these responses were influenced by gait speed, surface inclination, and perturbation intensity. Our study identified target range of motion parameters of 85.19°, 106.34°, and 95.23° for the hips, knees, and ankles, respectively. Furthermore, rotations per minute values ranged from 17.85 to 51.10 for the hip, 21.73 to 63.80 for the knee, and 17.52 to 57.14 for the ankle joints. Finally, flexion/extension torque values were estimated as -3.05 to 3.22 Nm/kg for the hip, -1.70 to 2.34 Nm/kg for the knee, and -2.21 to 0.90 Nm/kg for the ankle joints.

Discussion: This study contributes valuable insights into the biomechanical aspects of slip-like fall prevention and informs the development of wearable robotic systems to enhance safety in vulnerable populations.

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来源期刊
CiteScore
6.50
自引率
5.90%
发文量
355
审稿时长
14 weeks
期刊介绍: Frontiers in Robotics and AI publishes rigorously peer-reviewed research covering all theory and applications of robotics, technology, and artificial intelligence, from biomedical to space robotics.
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