A review on the coordinative structure of human walking and the application of principal component analysis

Walking is a complex task which includes hundreds of muscles, bones and joints working together to deliver smooth movements. With the complexity, walking has been widely investigated in order to identify the pattern of multi-segment movement and reveal the control mechanism. The degree of freedom and dimensional properties provide a view of the coordinative structure during walking, which has been extensively studied by using dimension reduction technique. In this paper, the studies related to the coordinative structure, dimensions detection and pattern reorganization during walking have been reviewed. Principal component analysis, as a popular technique, is widely used in the processing of human movement data. Both the principle and the outcomes of principal component analysis were introduced in this paper. This technique has been reported to successfully reduce the redundancy within the original data, identify the physical meaning represented by the extracted principal components and discriminate the different patterns. The coordinative structure during walking assessed by this technique could provide further information of the body control mechanism and correlate walking pattern with injury.

Computational Models to Synthesize Human Walking

The synthesis of human walking is of great interest in biomechanics and biomimetic engineering due to its predictive capabilities and potential applications in clinical biomechanics, rehabilitation engineering and biomimetic robotics. In this paper, the various methods that have been used to synthesize humanwalking are reviewed from an engineering viewpoint. This involves a wide spectrum of approaches, from simple passive walking theories to large-scale computational models integrating the nervous, muscular and skeletal systems. These methods are roughly categorized under four headings： models inspired by the concept of a CPG （Central Pattern Generator）, methods based on the principles of control engineering, predictive gait simulation using optimisation, and models inspired by passive walking theory. The shortcomings and advantages of these methods are examined, and future directions are discussed in the context of providing insights into the neural control objectives driving gait and improving the stability of the predicted gaits. Future advancements are likely to be motivated by improved understanding of neural control strategies and the subtle complexities of the musculoskeletal system during human locomotion. It is only a matter of time before predictive gait models become a practical and valuable tool in clinical diagnosis, rehabilitation engineering and robotics.

Impact of different human walking patterns on flow and contaminant dispersion in residential kitchens:Dynamic simulation study

The effects of different human walking patterns on contaminant dispersion in residential kitchens were investigated through computational fluid dynamics simulation with the dynamic mesh method.A tracer gas experiment was performed to verify the feasibility and accuracy of the simulation method.Flow characteristics induced by human walking were minutely described,and the transient capture efficiency of the range hood was adopted to assess the impact of human walking quantitatively.Human walking parallel to a counter,human walking parallel to a counter manned by another human,and human walking toward a counter were studied.Results showed that the mutual effect of the wake and thermal plume caused contaminant dispersion and decreased the performance of the range hood as the human subject walked beside the counter.Even a standing person operated ahead the counter,the wake would affect the thermal plume in a certain extent.The decrement of capture efficiency approached 0.5 in the most unfavorable situation.Moreover,the coaction of the positive/negative pressure zone and impinging air jet drew the thermal plume to the human body.The fluctuation of capture efficiency in this condition was moderate relative to that for the human walking pattern beside the counter.This research could provide a comprehensive overview of different human walking patterns and their impact on residential kitchens and thereby facilitate the maintenance of kitchen air quality.

Effect of Relative Humidity on Resuspended Particles Caused by Human Walking

The goal of this study is to investigate the effects of relative humidity on particle resuspension.The experimental study on the resuspension of different size particles is performed in the laboratory at 50%,60%,70% and 80% relative humidity separately.The material of flooring is shaggy carpet.The experiments are carried out in a closed room with four laser dust instruments and a laser dust particle counter.The results show that when the relative humidity is 60% and 70%,the resuspension of indoor particulate matter is likely to occur.Human walking has a greater impact on larger-size particles.Under the conditions of different humidity,four situations all follow a rule that the larger the particle size is,the more stable the particle state is.

Multiple walking human recognition based on radar micro-Doppler signatures

The recognition of human movements based on radar m-D(micro-Doppler) signatures attracts great interest in the field of radar research on automatic target recognition. Because there are multiple frequency components overlapping seriously in the radar echoes from walking humans, it is a very difficult work to recognize walking humans based on radar echoes. In this paper, a recognition method of walking humans based on radar m-D signatures is proposed. In this method, the m-D spectrum is generated by generalized S transform first,and then the entropy segmentation is used to segment the interesting region from the original spectrum. Next,the m-D features are extracted from the m-D region. Lastly, the support vector machine is used to recognize different walking human targets. The simulation experiments considering two factors of height and velocity are also conducted to test the performance of this proposed method.

Development of a 3D Printed Bipedal Robot:Towards Humanoid Research Platform to Study Human Musculoskeletal Biomechanics

The objective of this study is to develop a bio robot with a high degree of biomechanical fidelity to the human musculoskeletal system in order to investigate the biomechanical principles underlying human walking.The robot was designed to possess identical biomechanical characteristics to the human body in terms of body segment properties,joint configurations and 3D musculoskeletal geometries.These design parameters were acquired based on the medical images,3D musculoskeletal model and gait measurements of a healthy human subject.To satistyall the design criteria sinultaneously,metal 3D printing was used to construct the whole-body humanoid robot.Flexible artificial muscles were fabricated in accordance with the predefined 3D musculoskeletal geometries.A series of physical tests were con-ducted to demonstrate the capacity of the robot platform.The fabricated robot shows equivalent mechanical characteristics to the human body as originally designed.The results of the physical tests by systematically changing environmental conditions and body structures have successfully demonstrated the capability of the robot platform to investigate the structure-function interplay in the human musculoskeletal system and also its interaction with the environment during walking.This robot might provide a valuable and powerful physical platfornm towards studying hunan musculoskeletal biomechanics by generating new hypotheses and revealing new insights into human locomotion science.