Abstract
Characterizing the quasi-stiffness and work of lower extremity joints is critical for evaluating human locomotion and designing assistive devices such as prostheses and orthoses intended to emulate the biological behavior of human legs. This work aims to establish statistical models that allow us to predict the ankle quasi-stiffness and net mechanical work for adults walking on level ground. During the stance phase of walking, the ankle joint propels the body through three distinctive phases of nearly constant stiffness known as the quasi-stiffness of each phase. Using a generic equation for the ankle moment obtained through an inverse dynamics analysis, we identify key independent parameters needed to predict ankle quasi-stiffness and propulsive work and also the functional form of each correlation. These parameters include gait speed, ankle excursion, and subject height and weight. Based on the identified form of the correlation and key variables, we applied linear regression on experimental walking data for 216 gait trials across 26 subjects (speeds from 0.75–2.63 m/s) to obtain statistical models of varying complexity. The most general forms of the statistical models include all the key parameters and have an R2 of 75% to 81% in the prediction of the ankle quasi-stiffnesses and propulsive work. The most specific models include only subject height and weight and could predict the ankle quasi-stiffnesses and work for optimal walking speed with average error of 13% to 30%. We discuss how these models provide a useful framework and foundation for designing subject- and gait-specific prosthetic and exoskeletal devices designed to emulate biological ankle function during level ground walking.
Highlights
Several engineering fields desire a better understanding of human locomotion biomechanics including anthropomorphic bipedal robots [1,2], lower-limb wearable exoskeletons [3,4,5,6,7,8,9,10], and biologically-inspired prosthetic limbs [11,12,13,14]
We extracted the generic equation of the ankle moment through an inverse dynamics analysis and simplified it for the stance phase
The simplified equation for the stance phase emphasizes that the quasi-stiffnesses of the ankle are linearly correlated with combinations of both gait and body parameters in the most general form
Summary
Several engineering fields desire a better understanding of human locomotion biomechanics including anthropomorphic bipedal robots [1,2], lower-limb wearable exoskeletons [3,4,5,6,7,8,9,10], and biologically-inspired prosthetic limbs [11,12,13,14]. Emulation of human locomotion in these artificial systems would ideally be built upon theoretical or empirical models that can accurately characterize the behavior of lower extremity joints during gait [15,16,17]. Theoretical and empirical models of varying complexity for the whole leg and for the compliant components have been investigated by other researchers and can be used in these systems to help generate human-like locomotion [1,17,18,19,20,21,22,23,24,25]. Researchers typically characterize the kinetic and kinematic behavior of the joints using data experimentally captured in a gait laboratory [26,27,28]. A common finding from all of these approaches is that compliance, both at the whole-limb and individual joint level, plays a central role in shaping human motion
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