About

The Biomechatronics Group uses a data-driven approach to study the mechanics and control of human walking, with the goal of applying the findings to hardware control.

Data driven neuromuscular model of walking

We have constructed a data-driven neuromuscular model of human walking and are applying it to prosthesis control.  The model has two novel aspects: (i) it leverages tendon elasticity to more accurately predict the metabolic cost of walking than conventional models, and (ii) it utilizes a feedback-only control architecture that allows direct application to prosthesis control.
Current neuromuscular models often overestimate the metabolic demands of walking.  We believe this is because they do not adequately consider the role of elasticity; specifically the parameters that govern the force-length relations of tendons in these models are typically taken from published values determined from cadaver studies.  We optimize these parameters for each individual, finding sets that simultaneously minimize the metabolic cost of walking and maximize agreement with kinetic data.  These results are then applied in a forward dynamic simulation where muscle stimulations are provided by spinal reflex loops governed by muscle force and state.  This control structure is optimized for stability and metabolic efficiency and then applied in the control of a robotic ankle prosthesis.  Clinical trials are conducted and seen to demonstrate adaptation across speed, suggesting both efficacy of the modeling approach and potential for its use in controlling life-like prosthetic limbs.

Jared Markowitz and Hugh Herr

A muscle-reflex model that encodes principles of legged mechanics produces human walking dynamics and muscle activities

While neuroscientists identify increasingly complex neural circuits that control animal and human gait, biomechanists find that locomotion requires little control if principles of legged mechanics are heeded that shape and exploit the dynamics of legged systems. Here we show that muscle reflexes could be vital to link these two observations. We develop a model of human locomotion that is controlled by muscle reflexes which encode principles of legged mechanics. Equipped with this reflex control, we find this model to stabilize into a walking gait from its dynamic interplay with the ground, reproduce human walking dynamics and leg kinematics, tolerate ground disturbances, and adapt to slopes without parameter interventions. In addition, we find this model to predict some individual muscle activation patterns known from walking experiments. The results suggest not only that the interplay between mechanics and motor control is essential to human locomotion, but also that human motor output could for some muscles be dominated by neural circuits that encode principles of legged mechanics.

H. Geyer and H. Herr.
A muscle-reflex model that encodes principles of legged mechanics produces human walking dynamics and muscle activities,
IEEE TNSRE, 2010.

A model of muscle-tendon function in human walking

We are studying the mechanical behavior of leg muscles and tendons during human walking in order to motivate the design of economical robotic legs. We hypothesize that quasi-passive, series-elastic clutch units spanning the knee joint in a musculoskeletal arrangement can capture the dominant mechanical behaviors of the human knee in level-ground walking. Biarticular elements necessarily need to transfer energy from the knee joint to hip and/or ankle joints, and this mechanism would reduce the necessary muscle work and improve the mechanical economy of a human-like walking robot.

K. Endo and H. Herr.
A model of muscle-tendon function in human walking,
IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, May 2009.

Angular momentum in human walking

Angular momentum is a conserved physical quantity for isolated systems where no external moments act about a bodyʼs center of mass (CM). However, in the case of legged locomotion, where the body interacts with the environment (ground reaction forces), there is no a priori reason for this relationship to hold. A key hypothesis in this paper is that angular momentum is highly regulated throughout the walking cycle about all three spatial directions [L(t)≈0], and therefore horizontal ground reaction forces and the center of pressure trajectory can be explained predominantly through an analysis that assumes zero net moment about the bodyʼs CM. Using a 16-segment human model and gait data for 10 study participants, we found that calculated zero-moment forces closely match experimental values (R2=0.91; R2 = 0.90). Additionally, the centroidal moment pivot (point where a line parallel to the ground reaction force, passing through the CM, intersects the ground) never leaves the ground support base, highlighting how closely the body regulates angular momentum. Principal component analysis was used to examine segmental contributions to whole-body angular momentum. We found that whole-body angular momentum is small, despite substantial segmental momenta, indicating large segment-to-segment cancellations (~95% medio-lateral, ~70% anterior–posterior and ~80% vertical). Specifically, we show that adjacent leg-segment momenta are balanced in the medio-lateral direction (left foot momentum cancels right foot momentum, etc.). Further, pelvis and abdomen momenta are balanced by leg, chest and head momenta in the anterior–posterior direction, and leg momentum is balanced by upper-body momentum in the vertical direction. Finally, we discuss the determinants of gait in the context of these segment-to-segment cancellations of angular momentum

H.M. Herr and M. Popovic.
Angular momentum in human walking,
JEB, 2008.
 

Ground reference points in legged locomotion: Definitions, biological trajectories and control implications

The zero moment point (ZMP), foot rotation indicator (FRI) and centroidal moment pivot (CMP) are important ground reference points used for motion identification and control in biomechanics and legged robotics. In this paper, we study these reference points for normal human walking, and discuss their applicability in legged machine control. Since the FRI was proposed as an indicator of foot rotation, we hypothesize that the FRI will closely track the ZMP in early single support when the foot remains flat on the ground, but will then significantly diverge from the ZMP in late single support as the foot rolls during heel-off. Additionally, since spin angular momentum has been shown to remain small throughout the walking cycle, we hypothesize that the CMP will never leave the ground support base throughout the entire gait cycle, closely tracking the ZMP. We test these hypotheses using a morphologically realistic human model and kinetic and kinematic gait data measured from ten human subjects walking at self-selected speeds. We find that the mean separation distance between the FRI and ZMP during heel-off is within the accuracy of their measurement (0.1% of foot length). Thus, the FRI point is determined not to be an adequate measure of foot rotational acceleration and a modified FRI point is proposed. Finally, we find that the CMP never leaves the ground support base, and the mean separation distance between the CMP and ZMP is small (14% of foot length), highlighting how closely the human body regulates spin angular momentum in level ground walking.

M. Popovic, A. Goswami, and H. M. Herr.
Ground reference points in legged locomotion: definitions, biological trajectories and control implications,
Intl. J. Robotics Research, 2005.