ESTIMATION OF MULTI-DIRECTIONAL ANKLE IMPEDANCE AS A FUNCTION OF LOWER EXTREMITY MUSCLE ACTIVATION

The purpose of this research is to investigate the relationship between the mechanical impedance of the human ankle and the corresponding lower extremity muscle activity. Three experimental studies were performed to measure the ankle impedance about multiple degrees of freedom (DOF), while the ankle was subjected to different loading conditions and different levels of muscle activity. The first study determined the non-loaded ankle impedance in the sagittal, frontal, and transverse anatomical planes while the ankle was suspended above the ground. The subjects actively co-contracted their agonist and antagonistic muscles to various levels, measured using electromyography (EMG). An Artificial Neural Network (ANN) was implemented to characterize the relationship between the EMG and non-loaded ankle impedance in 3-DOF. The next two studies determined the ankle impedance and muscle activity during standing, while the foot and ankle were subjected to ground perturbations in the sagittal and frontal planes. These studies investigate the performance of subject-dependent models, aggregated models, and the feasibility of a generic, subject-independent model to predict ankle impedance based on the muscle activity of any person. Several regression models, including Least Square, Support Vector Machine, Gaussian Process Regression, and ANN, and EMG feature extraction techniques were explored. The resulting subject-dependent and aggregated models were able to predict ankle impedance with reasonable accuracy. Furthermore, preliminary efforts toward a subject-independent model showed promising results for the design of an EMG-impedance model that can predict ankle impedance using new subjects. This work contributes to understanding the relationship between the lower extremity muscles and the mechanical impedance of the ankle in multiple DOF. Applications of this work could be used to improve user intent recognition for the control of active ankle-foot prostheses

Using Lower Extremity Muscle Activations to Estimate Human Ankle Impedance in the External-Internal Direction

For millions of people, mobility has been afflicted by lower limb amputation. Lower extremity prostheses have been used to improve the mobility of an amputee; however, they often require additional compensation from other joints and do not allow for natural maneuverability. To improve upon the functionality of ankle-foot prostheses, it is necessary to understand the role of different muscle activations in the modulation of mechanical impedance of a healthy human ankle. This report presents the results of using artificial neural networks (ANN) to determine the functional relationship between lower extremity electromyography (EMG) signals and ankle impedance in the transverse plane. The Anklebot was used to apply pseudo-random perturbations to the human ankle in the transverse plane, while motion of the ankle in the sagittal and frontal planes was constrained. Using a stochastic system identification method, the mechanical impedance of the ankle in external-internal (EI) direction was determined as a function of the applied torque and corresponding ankle motion. The impedance of the ankle and muscle EMG signals were determined for three muscle activation levels, including with relaxed muscles, and with muscles activated and 10% and 20% of the subject’s maximum voluntary contraction (MVC). This information was used as the input and target matrices to train an ANN for each subject. The resulting ankle impedance from the proposed ANN was effectively predicted within 85% accuracy for nine out of ten subjects, and was within ±5 Nm/rad of the target impedance for all subjects. This work provides more understanding of the neuromuscular characteristics of the ankle and provides insight toward future design and control of ankle-foot prostheses

MECHANICAL IMPEDANCE OF ANKLE AS A FUNCTION OF ELECTROMYOGRAPHY SIGNALS OF LOWER LEG MUSCLES USING ARTIFICIAL NEURAL NETWORK

This paper reports on the feasibility of developing a model to describe the nonlinear relationship between the mechanical impedance of the human ankle within a specified range of frequency and the root mean square (RMS) value of the Electromyography (EMG) signals of the muscles of human ankle using Artificial Neural Network (ANN). A lower extremity rehabilitation robot — Anklebot was used to apply pseudo-random mechanical perturbations to the ankle and measure the angular displacement of the ankle to estimate the data of ankle mechanical impedance. Meanwhile, the surface EMG signals from the selected muscles were monitored and recorded using a Delsys Trigno® system. The final ANN models in this paper were created in two degrees of freedom — dorsiflexion-plantarflexion (DP) and inversioneversion (IE) at 3 different muscle activation levels. The results of analysis of the ANN model showed the feasibility of developing models with adequate accuracy and to define the mechanical impedance of the human ankle in terms of lower extremity muscles’ EMG statistical properties

ESTIMATION AND PREDICTION OF THE HUMAN GAIT DYNAMICS FOR THE CONTROL OF AN ANKLE-FOOT PROSTHESIS

With the growing population of amputees, powered prostheses can be a solution to improve the quality of life for many people. Powered ankle-foot prostheses can be made to behave similar to the lost limb via controllers that emulate the mechanical impedance of the human ankle. Therefore, the understanding of human ankle dynamics is of major significance. First, this work reports the modulation of the mechanical impedance via two mechanisms: the co-contraction of the calf muscles and a change of mean ankle torque and angle. Then, the mechanical impedance of the ankle was determined, for the first time, as a multivariable and time-varying system. These findings reveal the importance of recognizing the state of the user during the gait when the user interacts with the environment. In addition to studying the ankle impedance, a wearable device was designed and evaluated to further the studies on robotic perception for ankle-foot prostheses. This device is capable of characterizing the ground environment and estimating the gait state using visual-inertial sensors. Finally, this study contributes to the field of ankle-foot prostheses by identifying the mechanical behavior of the human ankle and developing a platform to test perception algorithms for the control of robotic prostheses

ANTHROPOMORPHIC ROBOTIC ANKLE-FOOT PROSTHESIS WITH ACTIVE DORSIFLEXION- PLANTARFLEXION AND INVERSION-EVERSION

The main goal of the research presented in this paper is the development of a powered ankle-foot prosthesis with anthropomorphic characteristics to facilitate turning, walking on irregular grounds, and reducing secondary injuries on bellow knee amputees. The research includes the study of the gait in unimpaired human subjects that includes the kinetics and kinematics of the ankle during different types of gait, in different gait speeds at different turning maneuvers. The development of a robotic ankle-foot prosthesis with two active degrees of freedom (DOF) controlled using admittance and impedance controllers is presented. Also, a novel testing apparatus for estimation of the ankle mechanical impedance in two DOF is presented. The testing apparatus allows the estimation of the time-varying impedance of the human ankle in stance phase during walking in arbitrary directions. The presented work gives insight on the turning mechanisms of the human ankle and how they can be mimicked by the prosthesis to improve the gait and agility of below-knee amputees

ANKLE IMPEDANCE AND ANKLE ANGLES DURING STEP TURN AND STRAIGHT WALK: IMPLICATIONS FOR THE DESIGN OF A STEERABLE ANKLE-FOOT PROSTHETIC ROBOT

During locomotion, turning is a common and recurring event which is largely neglected in the current state-of-the-art ankle-foot prostheses, forcing amputees to use different steering mechanisms for turning, compared to non-amputees. A better understanding of the complexities surrounding lower limb prostheses will lead to increased health and well-being of amputees. The aim of this research is to develop a steerable ankle-foot prosthesis that mimics the human ankle mechanical properties. Experiments were developed to estimate the mechanical impedance of the ankle and the ankles angles during straight walk and step turn. Next, this information was used in the design of a prototype, powered steerable ankle-foot prosthesis with two controllable degrees of freedom. One of the possible approaches in design of the prosthetic robots is to use the human joints’ parameters, especially their impedance. A series of experiments were conducted to estimate the stochastic mechanical impedance of the human ankle when muscles were fully relaxed and co-contracting antagonistically. A rehabilitation robot for the ankle, Anklebot, was employed to provide torque perturbations to the ankle. The experiments were performed in two different configurations, one with relaxed muscles, and one with 10% of maximum voluntary contraction (MVC). Surface electromyography (sEMG) was used to monitor muscle activation levels and these sEMG signals were displayed to subjects who attempted to maintain them constant. Time histories of ankle torques and angles in the lateral/medial (LM) directions, inversion-eversion (IE), and dorsiflexionplantarflexion (DP) were recorded. Linear time-invariant transfer functions between the measured torques and angles were estimated providing an estimate of ankle mechanical impedance. High coherence was observed over a frequency range up to 30 Hz. The main effect of muscle activation was to increase the magnitude of ankle mechanical impedance in all degrees of freedom of the ankle. Another experiment compared the three-dimensional angles of the ankle during step turn and straight walking. These angles were measured to be used for developing the control strategy of the ankle-foot prosthesis. An infrared camera system was used to track the trajectories and angles of the foot and leg. The combined phases of heel strike and loading response, mid stance, and terminal stance and pre-swing were determined and used to measure the average angles at each combined phase. The Range of motion (ROM) in IE increased during turning while ML rotation decreased and DP changed the least. During the turning step, ankle displacement in DP started with similar angles to straight walk and progressively showed less plantarflexion. In IE, the ankle showed increased inversion leaning the body toward the inside of the turn. ML rotation initiated with an increased medial rotation during the step turn relative to the straight walk transitioning to increased lateral rotation at the toe off. A prototype ankle-foot prosthesis capable of controlling both DP and IE using a cable driven mechanism was developed and assessed as part of a feasibility study. The design is capable of reproducing the angles required for straight walk and step turn; generates 712N of lifting force in plantarflexion, and shows passive stiffness comparable to a nonload bearing ankle impedance. To evaluate the performance of the ankle-foot prosthesis, a circular treadmill was developed to mimic human gait during steering. Preliminary results show that the device can appropriately simulate human gait with loading and unloading the ankle joint during the gait in circular paths

Simulation of Human Ankle Trajectory during Stance Phase of Gait

A simulation was developed which mimics the human gait characteristics based on the input of an individual’s gait trajectory. This simulation also estimates the impedance of the human ankle based on the ground reaction forces measured by the force plate. This simulation will accept alterations of the following parameters: total body weight, weight of the shank, weight of the foot, trajectories of the shank and foot of the individual and orientation of the force plate, which would generate a new gait trajectory for the ankle during the stance phase of gait. The goal of this simulation was to validate the protocols followed during experiments conducted on human participants to estimate the impedance of the ankle. It also allowed us to understand and explore different system identification methods. The gait data of two individuals measured experimentally was used to build this simulation model. The simulation implements proportional-integral-derivative (PID) control and impedance control to regenerate the ankle trajectories with time-varying impedance of the ankle joint. This model was tested using the trajectories of the shank and foot from two additional individuals and replicated experimentally obtained ankle trajectories of these individuals, with a mean relative error of 0.53±0.3%, 5.74±4.85% and 4.94±3.13%, in ankle translational trajectory and ankle angular trajectories in dorsi-plantarflexion and inversion-eversion respectively

Quantitative characterization of multi-variable human ankle mechanical impedance

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 222-230).Ankle mechanical impedance, which is a dynamic relationship between angular displacement and the corresponding torque at the ankle joint, plays a key role in natural interaction of the lower-extremity with the environment. The human ankle is a biomechanically complex joint consisting of three bones with non-intersecting anatomical axes, and its motions under normal motor control and function are predominantly in multiple degrees-of-freedom (DOF). This thesis provides a quantitative characterization of multivariable ankle mechanical impedance of young healthy subjects in two DOF, both in the sagittal and the frontal planes. Multi-variable studies provide several important characteristics of the human ankle, unavailable from single DOF studies, which have mostly been in the sagittal plane. Three characterization methods were developed to study ankle mechanical impedance in different conditions: 1) steady-state static, 2) steady-state dynamic, and 3) transient dynamic. First, steady-state static ankle mechanical impedance, which is a non-linear torque and angle relationship at the ankle, was characterized in two coupled DOFs over the normal range of motion. Robust vector field approximation methods based on thin-plate spline smoothing with generalized cross validation showed that static ankle impedance is highly direction dependent, being weak in the inversion-eversion direction. Activating a single muscle or co-contracting antagonistic muscles significantly increased static ankle impedance in all directions but more in the dorsiflexion-plantarflexion direction than the inversion-eversion. Static ankle behavior in both relaxed and active muscles was close to that of a passive elastic system. Second, steady-state dynamic ankle mechanical impedance was characterized based on linear time-invariant multi-input multi-output stochastic system identification methods. A highly linear relationship between muscle activation and ankle impedance was identified in all movement directions in the sagittal and frontal planes. Furthermore, small coupling between 2 DOF and energetic passivity were observed at different levels of muscle activation and over a wide frequency range. Third, transient dynamic ankle mechanical impedance was characterized during walking on a treadmill, across the gait cycle from the end of stance phase through swing and to early stance phase. Modified linear time-varying ensemble based system identification methods enabled reliable identification of transient behavior of the ankle. In both DOF, damping and stiffness decreased at the end of stance phase before the toe-off, remained relatively constant during the whole swing phase, and substantially increased around the heel-strike. Quantitative characterization of multi-variable ankle mechanical impedance of young healthy subjects will shed light on its roles in lower-extremity motor function. It will serve as a baseline for clinical studies in patients, especially those with neurological disorders, as well as studies of elderly subjects, whose biomechanical and neurological properties may be altered due to impairments and/or aging. Finally, the methods presented in this thesis are intended to be sufficiently general to be applicable to any multi-joint system or single joint having multiple DOF.by Hyunglae Lee.Ph.D

Passive Wrist Stiffness: The Influence of Handedness

Objective: This paper reports on the quantification of passive wrist joint stiffness and investigates the potential influence of handedness and gender on stiffness estimates. Methods: We evaluated the torque-angle relationship during passive wrist movements in 2 degrees of freedom (into flexion-extension and radial-ulnar deviation) in 13 healthy subjects using a wrist robot. Experimental results determined intrasubject differences between dominant and nondominant wrist and intersubject differences between male and female participants. Results: We found differences in the magnitude of passive stiffness of left- and right-hand dominant males and right-hand dominant females suggesting that the dominant hand tends to be stiffer than the nondominant hand. Left-hand stiffness magnitude was found to be 37% higher than the right-hand stiffness magnitude in the left-handed male group and the right-hand stiffness magnitude was 11% and 40% higher in the right-handed male and female groups, respectively. Other joint stiffness features such as the orientation and the anisotropy of wrist stiffness followed the expected pattern from previous studies. Conclusion: The observed difference in wrist stiffness between the dominant and nondominant limb is likely due to biomechanical adaptations to repetitive asymmetric activities (such as squash, tennis, basketball, or activities of daily living such as writing, teeth brushing, etc.). Significance: Understanding and quantifying handedness influence on stiffness may have critical implication for the optimization of surgical and rehabilitative interventions