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Gait models are important for the design and control of lower limb exoskeletons. The inverted pendulum model has advantages in simplicity and computational efficiency, but it also has the limitations of oversimplification and lack of realism. This paper proposes a two-degrees-of-freedom (DOF) inverted pendulum walking model by considering the knee joints for describing the characteristics of human gait. A new parameter, roll factor, is defined to express foot function in the model, and the relationships between the roll factor and gait parameters are investigated. Experiments were conducted to verify the model by testing seven healthy adults at different walking speeds. The results demonstrate that the roll factor has a strong relationship with other gait kinematics parameters, so it can be used as a simple parameter for expressing gait kinematics. In addition, the roll factor can be used to identify walking styles with high accuracy, including small broken step walking at 99.57%, inefficient walking at 98.14%, and normal walking at 99.43%. [ABSTRACT FROM AUTHOR]

Human gait reflects health condition and is widely adopted as a diagnostic basis in clinical practice. This research adopts compact inertial sensor nodes to monitor the function of human lower limbs, which implies the most fundamental locomotion ability. The proposed wearable gait analysis system captures limb motion and reconstructs 3D models with high accuracy. It can output the kinematic parameters of joint flexion and extension, as well as the displacement data of human limbs. The experimental results provide strong support for quick access to accurate human gait data. This paper aims to provide a clue for how to learn more about gait posture and how wearable gait analysis can enhance clinical outcomes. With an ever-expanding gait database, it is possible to help physiotherapists to quickly discover the causes of abnormal gaits, sports injury risks, and chronic pain, and provides guidance for arranging personalized rehabilitation programs for patients. The proposed framework may eventually become a useful tool for continually monitoring spatio-temporal gait parameters and decision-making in an ambulatory environment. [ABSTRACT FROM AUTHOR]