page updated in October 2022
Seungmoon Song
sung-moon song

Assistant Professor
Mechanical and Industrial Engineering
Northeastern University
Boston, MA

Email: ssm0445 at gmail dot com

       



This page covers up to my postdoctoral research. You can find my work after 2021 at my lab homepage: NeuMove.

The goal of my research is to better understand and model the motor control and biomechanics of human locomotion and to apply the obtained knowledge to rehabilitation engineering. I develop computational models and conduct human experiments to propose and evaluate control hypotheses. I envision to bring about simulation testbeds (which I call digital motor clones) for developing rehabilitation treatment.


Journal papers


Optimized hip-knee-ankle exoskeleton assistance reduces the metabolic cost of walking with worn loads
GM Bryan, PW Franks, S Song, R Reyes, MP O'Donovan, KN Gregorczyk & SH Collins
Journal of NeuroEngineering and Rehabilitation, 2021
[paper]

Optimized hip-knee-ankle exoskeleton assistance at a range of walking speeds
GM Bryan, PW Franks, S Song, AS Voloshina, R Reyes, MP O'Donovan, KN Gregorczyk & SH Collins
Journal of NeuroEngineering and Rehabilitation, 2021
[paper]

Deep reinforcement learning for modeling human locomotion in neuromechanical simulation
S Song, Ł Kidziński, XB Peng, C Ong, J Hicks, S Levine, CG Atkeson & SL Delp
Journal of NeuroEngineering and Rehabilitation, 2021
[paper] [video 2017] [video 2018] [video 2019]

Optimizing exoskeleton assistance for faster self-selected walking
S Song & SH Collins
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021
[paper] [video 1] [video 2] [video Stanford] [press]

Using force data to self-pace an instrumented treadmill and measure self-selected walking speed
S Song, H Choi & SH Collins
Journal of NeuroEngineering and Rehabilitation, 2020
[paper] [code] [video]

Predictive neuromechanical simulations indicate why walking performance declines with aging
S Song & H Geyer
The Journal of Physiology, 2018
[paper] [press]

Evaluation of a Neuromechanical Walking Control Model Using Disturbance Experiments
S Song & H Geyer
Frontiers in Computational Neuroscience, 2017
[paper] [video 1] [video 2]

A neural circuitry that emphasizes spinal feedback generates diverse behaviours of human locomotion
S Song & H Geyer
The Journal of Physiology, 2015
[paper] [video] [model] [journal cover]



Conference papers


Bayesian optimization using domain knowledge on the ATRIAS biped
A Rai, R Antonova, S Song, W Martin, H Geyer & CG Atkeson
IEEE ICRA, 2018
[paper] [video]

Towards a hierarchical neuromuscular control model with reflex-based spinal control - A study with a simple running model
S Song
International Symposium on Advanced Intelligent Systems, 2015
[paper] [video] [best presentation award]

Regulating speed in a neuromuscular human running model
S Song & Hartmut Geyer
IEEE Humanoids, 2015
[paper] [video]

Toward a virtual neuromuscular control for robust walking in bipedal robots
Z Batts, S Song & Hartmut Geyer
IEEE IROS, 2015
[paper] [video]

Development of a bipedal robot that walks like an animation character
S Song, J Kim & K Yamane
IEEE ICRA, 2015
[paper] [video] [talk] [press]

Integration of an adaptive swing control into a neuromuscular human walking model
S Song, R Desai & H Geyer
IEEE EMBC, 2013
[paper] [video]

Generalization of a muscle-reflex control model to 3D walking
S Song & H Geyer
IEEE EMBC, 2013
[paper]

The effect of foot compliance encoded in the windlass mechanism on the energetics of human walking
S Song, C LaMontagna, SH Collins & H Geyer
IEEE EMBC, 2013
[paper] [video] [project page]

Regulating speed and generating large speed transitions in a neuromuscular human walking model
S Song & H Geyer
IEEE ICRA, 2012
[paper] [video] [slides]

The energetic cost of adaptive feet in walking
S Song & H Geyer
IEEE ROBIO, 2011
[paper] [slides] [project page]

Development of an omnidirectional walking engine for full-sized lightweight humanoid robots
S Song, YJ Ryoo & DW Hong
ASME IDETC, 2011
[paper] [video1] [video2] [slides] [project page]

Linear-time encodable rate-compatible punctured LDPC codes with low error floors
S Song, D Hwang, S Seo & J Ha
IEEE VTC, 2008
[paper]



Patents

J Kim, K Yamane & S Song, Method for developing and controlling a robot to have movements match-ing an animation character, United States Patent 9427868, 2016. [link]

J Nam, J An, D Hwang, J Ha & S Song, Apparatus and method for encoding low density parity check code, Korean patent 10-0999272-00-00, 2010. [link]




Conference abstracts

Invited talks