An IMU-based ground reaction force estimation method and its application in walking balance assessment

地面反作用力 惯性测量装置 平衡(能力) 运动学 模拟 物理医学与康复 计算机科学 部队平台 康复 运动分析 计量单位 人工智能 物理疗法 医学 物理 经典力学 量子力学
作者
Xiangzhi Liu,Xiangliang Zhang,Bin Zhang,Bin Zeng,Zexia He,Tao Liu
出处
期刊:IEEE Transactions on Neural Systems and Rehabilitation Engineering [Institute of Electrical and Electronics Engineers]
卷期号:: 1-1
标识
DOI:10.1109/tnsre.2023.3347729
摘要

Walking is one of the most common daily movements of the human body. Therefore, quantitative evaluation of human walking has been commonly used to assist doctors in grasping the disease degree and rehabilitation process of patients in the clinic. Compared with the kinematic characteristics, the ground reaction force (GRF) during walking can directly reflect the dynamic characteristics of human walking. It can further help doctors understand the degree of muscle recovery and joint coordination of patients. This paper proposes a GRF estimation method based on the elastic elements and Newton-Euler equation hybrid driving GRF estimation method. Compared with the existing research, the innovations are as follows. i) The hardware system consists of only two inertial measurement units (IMUs) placed on shanks. The acquisition of the overall motion characteristics of human walking is realized through the simplified four-link walking model and the thigh prediction method. ii) The method was validated not only on 10 healthy subjects but also on 11 Parkinson’s patients and 10 stroke patients with normalized mean absolute errors (NMAEs) of 5.95%±1.32%, 6.09%±2.00%, 5.87%±1.59%. iii) This paper proposes a dynamic balance assessment method based on the acquired motion data and the estimated GRF. It evaluates the overall balance ability and fall risk at four key time points for all subjects recruited. Because of the low-cost system, ease of use, low motion interference and environmental constraints, and high estimation accuracy, the proposed GRF estimation method and walking balance automatic assessment have broad clinical value.
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