Quantification and Modeling of Ankle Stiffness During Standing Balance

• Published in: IEEE transactions on biomedical engineering Vol. 68; no. 6; pp. 1828 - 1837
• Main Authors: Nalam, Varun, Adjei, Ermyntrude, Lee, Hyunglae
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.06.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Ankle; Ankle impedance; Ankle stiffness; Contraction; Impedance; Loading; Modulation; Muscle contraction; Muscles; Perturbation methods; postural balance; Rehabilitation; Reliability analysis; Robots; Stiffness; stiffness model; Task analysis; Visual perception
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2020.3023328

Objective: This study investigates the factors contributing to the modulation of ankle stiffness during standing balance and evaluates the reliability of linear stiffness models. Methods: A dual-axis robotic platform and a visual feedback display were used to quantify ankle stiffness in both the sagittal and frontal planes while subjects controlled different levels of ankle muscle co-contraction, center-of-pressure (CoP), and loading on the ankle. Results: Results of 40 subjects demonstrated that ankle stiffness in the sagittal plane linearly increased with the increasing level of these three factors. The linear model relating the change in these factors from the baseline measurements during quiet standing to the change in weight normalized ankle stiffness resulted in high reliability (R 2 = 0.83). Ankle stiffness in the frontal plane increased with the increasing ankle muscle co-contraction and ankle loading, but the linearity was less obvious. It also exhibited a clear nonlinear trend when CoP was shifted mediolaterally. Consequently, the reliability of the linear model was low for ankle stiffness in the frontal plane (R 2 = 0.37). Conclusion: During standing balance, ankle stiffness in the sagittal plane could be well explained by a linear model if ankle muscle activation, CoP, and ankle loading were collectively considered. However, the linear model cannot capture highly variable and nonlinear ankle stiffness characteristics in the frontal plane. Significance: The outcomes of this study could benefit the development of lower-extremity robots and their controllers. Furthermore, the ankle stiffness models could be used as a baseline in developing patient-specific ankle rehabilitation protocols.