障礙高度於模擬下肢肌肉力量和活動的影響

Abstract

Walking and obstacle negotiation are fundamental locomotor tasks performeddaily. In performing these activities, the human musculoskeletal system must maintain stability and generate sufficient forces to propel the body forward while overcoming environmental challenges. In contrast to normal walking however, the transition to negotiating environmental challenges requires adaptive adjustments in gait patterns and muscle activitiesto safely and efficiently clear obstacles - the mechanism of which remains largelyelusive. While existing studies that have examined obstacle negotiation have primarily focused on the kinematic aspects of gait, such as step length, step width,and clearance over the obstacle have contributed to our understanding of obstaclenegotiation strategies and trends, a comprehensive analysis of the underlying muscleforces similar to those in studies of normal and pathological gait and running onlevel ground has not yet been conducted. In recent years, advancements in technology and access to powerful computationhave driven a shift in the field towards simulation in biomechanics. OpenSim offerslibraries that allow researchers to create detailed musculoskeletal models of the human body, encompassing bones, joints, and muscles, while also providing advancedcapabilities for performing Inverse Kinematics (IK). IK enables the estimation ofjoint angles and positions from motion capture data, a crucial component in thesimulation of obstacle negotiation. Furthermore, OpenSim facilitates the simulationof muscle forces, activation, and joint dynamics, providing invaluable insights intohow muscles contribute to human movement. For studies involving patient data, OpenSim’s ability to create patient-specificmusculoskeletal models and its integration with motion capture systems offer advantages in incorporating real-world movement data into simulations, potentiallyyielding more accurate practical insights in the interpretation through analysis ofsimulated data. To date, there is no study that has conducted analysis of patientspecific muscle simulations during obstacle negotiation. The objective of this thesis is to explore the effects of obstacle height on jointmoments, muscle forces, and activations involved in these activities. using simulations based on data collected from young, healthy subjects. Due to the simulatednature of the data, kinematics was compared with established significant effects andtrends found in the calculated results in existing literature. If the simulated muscle activation patterns during obstacle negotiation can bereasonably representative of documented significant effects and trends, it could augment the kinematic analyses currently performed in the literature, and potentiallyenhance research directions in biomechanics, rehabilitation, and robotics

Walking and obstacle negotiation are fundamental locomotor tasks performeddaily. In performing these activities, the human musculoskeletal system must maintain stability and generate sufficient forces to propel the body forward while overcoming environmental challenges. In contrast to normal walking however, the transition to negotiating environmental challenges requires adaptive adjustments in gait patterns and muscle activitiesto safely and efficiently clear obstacles - the mechanism of which remains largelyelusive. While existing studies that have examined obstacle negotiation have primarily focused on the kinematic aspects of gait, such as step length, step width,and clearance over the obstacle have contributed to our understanding of obstaclenegotiation strategies and trends, a comprehensive analysis of the underlying muscleforces similar to those in studies of normal and pathological gait and running onlevel ground has not yet been conducted. In recent years, advancements in technology and access to powerful computationhave driven a shift in the field towards simulation in biomechanics. OpenSim offerslibraries that allow researchers to create detailed musculoskeletal models of the human body, encompassing bones, joints, and muscles, while also providing advancedcapabilities for performing Inverse Kinematics (IK). IK enables the estimation ofjoint angles and positions from motion capture data, a crucial component in thesimulation of obstacle negotiation. Furthermore, OpenSim facilitates the simulationof muscle forces, activation, and joint dynamics, providing invaluable insights intohow muscles contribute to human movement. For studies involving patient data, OpenSim’s ability to create patient-specificmusculoskeletal models and its integration with motion capture systems offer advantages in incorporating real-world movement data into simulations, potentiallyyielding more accurate practical insights in the interpretation through analysis ofsimulated data. To date, there is no study that has conducted analysis of patientspecific muscle simulations during obstacle negotiation. The objective of this thesis is to explore the effects of obstacle height on jointmoments, muscle forces, and activations involved in these activities. using simulations based on data collected from young, healthy subjects. Due to the simulatednature of the data, kinematics was compared with established significant effects andtrends found in the calculated results in existing literature. If the simulated muscle activation patterns during obstacle negotiation can bereasonably representative of documented significant effects and trends, it could augment the kinematic analyses currently performed in the literature, and potentiallyenhance research directions in biomechanics, rehabilitation, and robotics