Welcome to the web site for the Locomotion Lab at the University of Maryland. The lab is part of the Department of Kinesiology, under the direction of Dr. Ross Miller in the Cognitive Motor Neurosciences division. We use a combination of experimentation on human subjects and computer modeling techniques to study how the neural, muscular, and skeletal systems interact to produce locomotion in health and disease.
See the links in the header for more information on our members, aims, and current activity.
To inquire about joining the lab, please click here.
- Grant on data sharing in gait biomechanics funded by NSERC
- A graduate research assistantship is available for a new Ph.D. student
Locomotion Lab - Joining the lab
I'm always looking for highly motivated students with interests that overlap with the lab’s. Interested students with backgrounds in biology, computer science, engineering, kinesiology, neuroscience, or physical therapy are encouraged to contact Dr. Miller.
Open positions in the lab will be advertised on this page and on the Biomch-L “Jobs and Positions” message board. Please contact me if you are interested in an advertised position, but don’t hesitate to contact me anyway if you see nothing listed here.
Graduate Research Assistantship – posted December 6, 2012
A full-time research assistantship is currently available for a new Ph.D. student under the supervision of Dr. Miller. The assistantship is available immediately for two semesters, with the possibilities of renewal for additional semesters and additional funding through departmental teaching assistantships. The student will be expected to assist with ongoing research in the lab and to develop a thesis project within the interests of the lab.
Locomotion Lab - People
Ross Miller, Assistant Professor
Dovin Kiernan, MA student
Jae Shim, University of Maryland
Tim Kiemel, University of Maryland
Kevin Deluzio, Queen's University (Canada)
Scott Selbie, C-Motion Inc.
Locomotion Lab - Research
The human neural, muscular, and skeletal systems are each enormously complex in isolation, let alone when their actions are considered in concert. Yet somehow, the body in a healthy state achieves an elegant, seemingly effortless control of these systems. Disruptions in the form of disease, injury, or degradation can make even the most trivial movement tasks very difficult and have a tremendous impact on quality of life.
Research projects in the lab often center on gait (walking, running, sprinting) and related tasks (e.g. side-cutting) but we occasionally study other movements as well. The lab's long-term objectives are (1) to develop theories that explain and accurately predict the mechanics and energetics of human locomotion under a wide range of circumstances, and (2) to use principles from engineering, physiology, and neuroscience for early identification and prevention of locomotor impairments (e.g. osteoarthritis, running injuries).
Much of our work is motivated by the notion of optimal control theory, which posits that humans learn to move in ways that are optimal with respect to physiologically relevant goals. For example, it is often assumed that the goal of normal, healthy walking is to minimize the metabolic cost. Pathological gait typically has a greater energy cost than healthy gait, and can be viewed as a forced deviation from optimality, or as being optimal with respect to a different goal (e.g. perhaps individuals with osteoarthritis minimize pain or instability rather than energy).
- A public database on human biomechanical gait analysis
Data sharing has many potential advantages in human movement science, but most biomechanists do not share their data with each other. In this project, we are initiating a publicly accessible database on the kinetics and kinematics of locomotion (walking and running) in healthy adults, along with statistical metrics for assessing data quality. Funding: NSERC (Engage)Collaborators: Kevin Deluzio (Queen's University), Scott Selbie (C-Motion Inc.)
- Optimal control simulations of human locomotion by direct collocation
Optimal control models are a versatile and powerful tool for studying human movement, but traditional approaches for implementing them in biomechanics research are extremely computationally intensive, often requiring days of CPU time on high-performance computing clusters. Direct collocation methods can solve optimal control problems in minutes on a single CPU, and can potentially make these simulations feasible for interactive clinical research and real-time applications. We have developed a 2D direct collocation simulation model of human movement to study neural control strategies and sensorimotor integration in locomotion. Collaborators: Tim Kiemel (University of Maryland)
- Peak and cumulative joint loads in human walking and running
Gait analysis produces a variety of complex, time-varying signals that must be collapsed to discrete data for statistical analysis. In osteoarthritis (OA) research, often the peak value of the joint load is chosen for this metric. If peak loads are generally injurious, we would expect nearly every runner to get knee OA, since peak knee joint loads in running are very high and are experienced thousands of times a day. However, runners do not have an especially high incidence rate of OA compared to non-runners. In this study we are comparing joint loading parameters between walking and running to assess if the biomechanics of running somehow protect the knee joint from loads that would be otherwise injurious, and if these principles can assist in preventing OA in at-risk individuals.
Locomotion Lab - Publications
- Miller RH, Brandon SCE, and Deluzio KJ (2012). Predicting sagittal plane biomechanics that minimize the axial knee joint contact force during walking. ASME Journal of Biomechanical Engineering, accepted.
- Russell EM, Miller RH, Umberger BR, and Hamill J (2012). Lateral wedges alter mediolateral load distributions at the knee joint in obese individuals. Journal of Orthopaedic Research, accepted.
- Miller RH, Umberger BR, and Caldwell GE (2012). Sensitivity of maximum sprinting speed to characteristic parameters of the muscle force-velocity relationship. Journal of Biomechanics 45, 1406-1413.
- Miller RH, Umberger BR, and Caldwell GE (2012). Limitations to maximum sprinting speed imposed by muscle mechanical properties. Journal of Biomechanics 45, 1092-1097.
- Miller RH, Umberger BR, Hamill J, and Caldwell GE (2012). Evaluation of the minimum energy hypothesis and other potential optimality criteria for human running. Proceedings of the Royal Society B: Biological Sciences 279, 1498-1505.
- John D, Miller RH, Kozey-Keadle SL, Caldwell GE, and Freedson PS (2012). Biomechanical examination of the plateau phenomenon in ActiGraph vertical activity counts. Physiological Measurement 33, 219-230.
- Miller RH and Caldwell GE (2011). Practical lessons on running and jumping from computer simulations. Track and Cross Country Journal 1, 38-48.
- Hamill J, Russell EM, Gruber AH, and Miller RH (2011). Impact characteristics in shod and barefoot running. Footwear Science 3, 33-40.
- Hasson CJ, Miller RH, and Caldwell GE (2011). Contractile and elastic ankle joint muscular properties in young and older adults. PLoS ONE 6, e15953.
- Miller RH, Chang R, Baird JL, Van Emmerik REA, and Hamill J (2010). Variability in kinematic coupling assessed by vector coding and continuous relative phase. Journal of Biomechanics 43, 2554-2560.
- Gillette JC, Stevermer CA, Miller RH, Meardon SA, and Schwab CV (2010). The effects of age and type of carrying task on lower extremity kinematics. Ergonomics 53, 355-364.
- Hamill J, Russell EM, Gruber AH, Miller RH, and O'Connor KM (2009). Extrinsic foot muscle forces when running in varus, valgus and neutral shoes. Footwear Science 1, 153-161.
- Miller RH, Caldwell GE, Van Emmerik REA, Umberger BR, and Hamill J (2009). Ground reaction forces and lower extremity kinematics when running with suppressed arm swing. ASME Journal of Biomechanical Engineering 131, 124502.
- Miller RH and Hamill J (2009). Computer simulation of the effects of shoe cushioning on internal and external loading during running impacts. Computer Methods in Biomechanics and Biomedical Engineering 12, 481-490.
- Miller RH, Gillette JC, Derrick TR, and Caldwell GE (2009). Muscle forces during running predicted by gradient-based and random search static optimisation algorithms. Computer Methods in Biomechanics and Biomedical Engineering 12, 217-225.
- Hamill J, Miller RH, Noehren B, and Davis IS (2008). A prospective study of iliotibial band strain in runners. Clinical Biomechanics 23, 1018-1025.
- Miller RH, Meardon SA, Derrick TR, and Gillette JC (2008). Continuous relative phase variability during an exhaustive run in runners with a history of iliotibial band syndrome. Journal of Applied Biomechanics 24, 262-270.
- Miller RH, Lowry JL, Meardon SA, and Gillette JC (2007). Lower extremity mechanics of iliotibial band syndrome during an exhaustive run. Gait and Posture 26, 407-413.
Locomotion Lab - Courses
A list of selected Graduate Catalog Courses in the Kinesiology department with content related to work in the lab.
- KNES 402: Biomechanics of Sport Mechanical determinants influencing sport techniques. A quantitative, scientific basis for sport analysis with emphasis on the application to numerous sport activities. Evaluation and quantification of the filmed performance of athletes.
- KNES 462: Neural Basis of Human Movement An introduction to the neural substrates which underlie postural and volitional movement. Neuroanatomical and neurophysiological basis of motor functioning; past and present conceptualizations of motor control and coordination; movement disorders; and maturation of the neuromuscular system.
- KNES 603: Advanced Motor Development The analysis of major theoretical positions in motor skill development. Stage theory in motor development; development of motor skill memory; the development of motor control and coordination; and the role of reflexes in motor development.
- KNES 604: Development of Posture & Locomotion Development of posture and locomotion in humans integrating the perspectives of biomechanics, neurophysiology, perception-action theory and dynamical systems.
- KNES 670: Biomechanics Theory Theoretical basis for understanding the investigation of biomechanical aspects of the human body. Integration of subject matter from physics, engineering, anatomy, kinesiology, and physiology as it relates to the study of human motion and the body as a mechanical system.
- KNES 676: Multisensory Perception & Human Motor Control Overview of the major sensory inputs to human motor control and spatial orientatin including auditory, somatosensory, visual and vestibular.
- KNES 703: Research Seminar in Motor Development Issues and strategies in the design and evaluation of research in motor skill development. Course culminates in student planning, conducting and interpreting a reserch study.
Beginning in 2013, all students in the Kinesiology graduate program are required to take KNES 600 (Kinesiology in Public Health), KNES 601 (Epidemiology of Physical Activity), and KNES 610 (Methods & Techniques of Research). Other courses of interest may be found in the Bioengineering, Electrical & Computer Engineering, and Mechanical Engineering departments, and the Biological Sciences and Neuroscience & Cognitive Science programs.
Locomotion Lab - Resources
Most data collections take place in the Locomotion Research Lab, a shared space on the first floor of the SPH Building with Dr. Jae Shim. The equipment available in the lab includes:
- A 12-camera Vicon optical motion capture system (six T160 cameras and six T40 cameras)
- A runway with 10 AMTI strain gauge force platforms
- A 16-channel Delsys Trigno wireless electromyography system
- A CosMed K4b2 portable pulmonary gas exchange system
Matlab - general scientific computing and numerical analysis
Visual3D - biomechanical data processing and inverse dynamics modeling
OpenSim - musculoskeletal modeling and simulation
MotionGenesis Kane - symbolic dynamics manipulation for multibody motion
Adobe Illustrator - preparation of graphics and figures
Access to the university's High Performance Computing Cluster is available for computationally intensive projects.
|Dalhousie University - Neuromuscular Control in Orthopedics|
|East Carolina University - Biomechanics Lab|
|Free University of Amsterdam - MOVE Research Institute|
|Harvard University - Concord Field Station|
|Harvard University - <a data-cke-saved-href="http://www.runsnrc.org/RUNSNRC/Home.html" href="http://www.runsnrc.org/RUNSNRC/Home.html" "="" target="new" style="color: rgb(204, 51, 0); text-decoration: none;">Spaulding National Running Center|
|Massachusetts Institute of Technology - Biomechatronics Group|
|Massachusetts Institute of Technology - Robot Locomotion Group|
|Northeastern University - Neuromotor Systems Lab|
|Northwestern University - Bayesian Behavior Lab|
|Ohio State University - Movement Lab|
|Queen's University - BioMotion Lab|
|Queen's University - Human Mobility Research Lab|
|Queen's University - LIMB Lab|
|Royal Veterinary College - Structure & Motion Lab|
|Simon Fraser University - Locomotion Lab|
|Stanford University - BioMotion Lab|
|Stanford University - Neuromuscular Biomechanics Lab|
|Technical University of Darmstadt - Locomotion Lab|
|University of Calgary - Human Performance Lab|
|University of California Berkeley - PolyPedal Lab|
|University of Cambridge - Sensorimotor Learning Group|
|University of Colorado Boulder - Locomotion Lab|
|University of Delaware - Biomechanics & Movement Science Program|
|University of Florida - Computational Biomechanics Lab|
|University of Iowa - Orthopaedic Biomechanics Lab|
|University of Manchester - Animal Simulation Lab|
|University of Maryland - Neuromechanics Lab|
|University of Massachusetts Amherst - Biomechanics Lab|
|University of Massachusetts Amherst - Locomotion Research Group|
|University of Michigan - Human Biomechanics & Control Lab|
|University of Southern California - Brain-Body Dynamics Lab|
|University of Texas Austin - Neuromuscular Biomechanics Lab|
|University of Washington - Movement Control Lab|
|University of Wisconsin Madison - Bone & Joint Biomechanics Lab|
|University of Wisconsin Madison - Neuromuscular Biomechanics Lab|
Other Sites of Interest
|Biomch-L message board|
|C-Motion, Inc. - creators of Visual3D software|
|GaitSym - Bill Sellers' open source program for forward dynamics modeling|
|The OpenSim Community at Stanford University|
|Russ Tedrake's course on Underactuated Robotics at MIT OpenCourseWare|