Carmichael Ong
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A model of the cerebellum generates gait adaptations in a reflex-based neuromusculoskeletal model during split-belt walking Open
Background During split-belt treadmill walking, neurotypical humans exhibit adaptations characterized by a gradual decrease in step length asymmetry (SLA) toward or beyond symmetry, whereas individuals with cerebellar damage do not show th…
PREDICTING SAVINGS IN THE METABOLIC COST OF RUNNING WITH AN EXOTENDON Open
The exotendon is a passive device that reduces the energetic cost of running at 2.7 m/s, but its potential benefits at higher speeds remain unknown. Experimental testing is challenging because of the wide range of conditions that must be t…
A model of the cerebellum generates gait adaptations in a reflex-based neuromusculoskeletal model during split-belt walking Open
Background During split-belt treadmill walking, neurotypical humans exhibit adaptations characterized by a gradual decrease in step length asymmetry (SLA) toward or beyond symmetry, whereas individuals with cerebellar damage do not show th…
Personalizing a computational upper body model improves kinematic tracking in high range-of-motion arm movements Open
Musculoskeletal models of the shoulder are needed to understand the mechanics of overhead motions. Existing models can be scaled to represent the size of an individual person, but the kinematics are generic. We introduce a method to person…
AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale Open
While reconstructing human poses in 3D from inexpensive sensors has advanced significantly in recent years, quantifying the dynamics of human motion, including the muscle-generated joint torques and external forces, remains a challenge. Pr…
OpenSense: An open-source toolbox for Inertial-Measurement-Unit-based measurement of lower extremity kinematics over long durations Open
Background The ability to measure joint kinematics in natural environments over long durations using inertial measurement units (IMUs) could enable at-home monitoring and personalized treatment of neurological and musculoskeletal disorders…
Deep reinforcement learning for modeling human locomotion control in neuromechanical simulation Open
Modeling human motor control and predicting how humans will move in novel environments is a grand scientific challenge. Despite advances in neuroscience techniques, it is still difficult to measure and interpret the activity of the million…
View article: Predicting gait adaptations due to ankle plantarflexor muscle weakness and contracture using physics-based musculoskeletal simulations
Predicting gait adaptations due to ankle plantarflexor muscle weakness and contracture using physics-based musculoskeletal simulations Open
Deficits in the ankle plantarflexor muscles, such as weakness and contracture, occur commonly in conditions such as cerebral palsy, stroke, muscular dystrophy, Charcot-Marie-Tooth disease, and sarcopenia. While these deficits likely contri…
Predicting gait adaptations due to ankle plantarflexor muscle weakness and contracture using physics-based musculoskeletal simulations Open
Deficits in the ankle plantarflexor muscles, such as weakness and contracture, occur commonly in conditions such as cerebral palsy, stroke, muscular dystrophy, and Charcot-Marie-Tooth disease. While these deficits likely contribute to obse…
View article: Artificial Intelligence for Prosthetics - challenge solutions
Artificial Intelligence for Prosthetics - challenge solutions Open
In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a given time-varying velocity vector. Top participants were invi…
OpenSim: Simulating musculoskeletal dynamics and neuromuscular control to study human and animal movement Open
Movement is fundamental to human and animal life, emerging through interaction of complex neural, muscular, and skeletal systems. Study of movement draws from and contributes to diverse fields, including biology, neuroscience, mechanics, a…
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments Open
In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle course. Top participants were invited to describe their algo…
Learning to Run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning Open
Synthesizing physiologically-accurate human movement in a variety of conditions can help practitioners plan surgeries, design experiments, or prototype assistive devices in simulated environments, reducing time and costs and improving trea…