A model to predict ground reaction force for elastically-suspended backpacks

Yuquan Leng; Xin Lin; Zeyu Lu; Aiguo Song; Zhangguo Yu; Chenglong Fu

doi:10.1016/j.gaitpost.2020.08.131

A model to predict ground reaction force for elastically-suspended backpacks

Gait Posture. 2020 Oct:82:118-125. doi: 10.1016/j.gaitpost.2020.08.131. Epub 2020 Sep 15.

Authors

Yuquan Leng¹, Xin Lin¹, Zeyu Lu¹, Aiguo Song², Zhangguo Yu³, Chenglong Fu⁴

Affiliations

¹ Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
² State Key Lab Bioelect, Southeast University, Nanjing 210096, China.
³ Intelligent Robotics Institute, Beijing Institute of Technology, Beijing 100081, China.
⁴ Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen 518055, China. Electronic address: fucl@sustech.edu.cn.

PMID: 32947177
DOI: 10.1016/j.gaitpost.2020.08.131

Abstract

Background: Leg muscle fatigue is the most important factor that affects walking endurance. Considering the legs act as actuators in alternate contact with the ground during walking, the ground reaction force (GRF) of each leg can indirectly reflect the strength of leg muscles. However, it is not clear how the elastically-suspended backpack (ESB) affects GRF of each leg during human level walking.

Research question: How is ESB related in GRF of each leg during walking, and how do multiple variables (stiffness and damping of ESB, load mass, walking speed) affect GRF?

Methods: An extended bipedal walking model (EBW) with a spring-mass-damping system was proposed to predict the GRF of each leg. In order to evaluate the prediction effect of the model, seven healthy subjects were recruited to attend the experiments using our backpack prototype and the GRFs data was compared. Each subject walked under 12 conditions (load states: locked or unlocked, walking speed: 3.6 km/h, 4.0 km/h, 4.5 km/h, 5.0 km/h, 5.5 km/h, 6.0 km/h).

Results: Results showed that the model could quantitatively predict experimental GRFs over the whole gait cycle (R²≥0.9628) and the characteristic forces (two peak forces and one trough force) were close to the experimental data (average predicted accuracy 93.7 %). The model can reflect relationships between variables and GRF. The relationships showed that an apparent tradeoff exists among the three characteristic forces, and the ESB can produce positive or negative effect under different variables.

Significance: This work could help us understand the experimental GRF phenomena, especially the contradictory experimental phenomenon caused by the different parameters. It could also help designers optimize structural parameters of ESB for excellent effects on human. The ESBs with excellent performance can be wildly used in military and tourism.

Keywords: Bipedal walking; Elastically-suspended backpack; Ground reaction force; Muscle fatigue; Spring-mass-damping system.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biomechanical Phenomena
Female
Gait / physiology*
Humans
Male
Muscle, Skeletal / physiology*
Research Design
Weight-Bearing