Design and evaluation of a powered prosthetic foot with monoarticular and biarticular actuation

To overcome the limitations of passive prosthetic feet, powered prostheses have been developed, that can provide the range of motion and power of their human counterparts. These devices can equalize spatio-temporal gait parameters and improve the metabolic effort compared to passive prostheses, but asymmetries and compensatory motions between the healthy and impaired leg remain. Unlike their human counter part, existing powered prosthetic feet are fully monoarticular actuating only the prosthetic ankle joint, whereas in the biological counter part, ankle and knee joint are additionally coupled by the biarticular gastrocnemius muscle. The goal of this work is to investigate the benefits of a powered biarticular transtibial prosthesis comprising mono- and biarticular actuators similar to the human example. The contributions of the present work are as follows: A biarticular prosthesis prototype is methodically designed to match the capabilities of the monoarticular muscles at the human ankle joint as well as the biarticular gastrocnemius muscle during level walking. The prototype consists of an existing powered monoarticular prosthetic foot, which is extended with a knee orthoses and a stationary biarticular Bowden cable actuator. Both actuators are modeled as serial elastic actuators (SEA) and the identification of the model parameters is conducted. A model based torque control utilizing the measurements commonly available in SEAs, an impedance control law based on human ankle reference trajectories, and a high level control to enable steady walking in the lab are introduced. The proposed hardware setup and control structure can provide sagittal plane angles and torques similar to the mono- and biarticular muscles at the human ankle, with proper torque tracking performance and a freely adjustable allocation of torque between the monoarticular and biarticular actuator. The biarticular prosthesis is evaluated in the gait lab with three subjects with unilateral transtibial amputation utilizing a continuous sweep experimental protocol to investigate the metabolic effort and spatio-temporal gait parameters. All subjects show a tendency to reduced metabolic effort for medium activity of the artificial gastrocnemius, although noise level and time variation are large. In addition to the reduction in metabolic effort, the artificial gastrocnemius is able to influence spatio temporal gait parameters between the impaired and the intact side, but partially opposing effects are observed among the individual subjects. In conclusion, this thesis describes the implementation of an artificial gastrocnemius following the human example and the systematic investigation of metabolic effort and spatio-temporal gait parameters. It is shown that the addition of the artificial gastrocnemius to a monoarticular prosthesis can positively affect the investigated parameters. The meaningfulness of the results should be improved by increased clinical effort in future work

Exploring surface electromyography (EMG) as a feedback variable for the human-in-the-loop optimization of lower limb wearable robotics

Human-in-the-loop (HITL) optimization with metabolic cost feedback has been proposed to reduce walking effort with wearable robotics. This study investigates if lower limb surface electromyography (EMG) could be an alternative feedback variable to overcome time-intensive metabolic cost based exploration. For application, it should be possible to distinguish conditions with different walking efforts based on the EMG. To obtain such EMG data, a laboratory experiment was designed to elicit changes in the effort by loading and unloading pairs of weights (in total 2, 4, and 8 kg) in three randomized weight sessions for 13 subjects during treadmill walking. EMG of seven lower limb muscles was recorded for both limbs. Mean absolute values of each stride prior to and following weight loading and unloading were used to determine the detection rate (100% if every loading and unloading is detected accordingly) for changing between loaded and unloaded conditions. We assessed the use of multiple consecutive strides and the combination of muscles to improve the detection rate and estimated the related acquisition times of diminishing returns. To conclude on possible limitations of EMG for HITL optimization, EMG drift was evaluated during the Warmup and the experiment. Detection rates highly increased for the combination of multiple consecutive strides and the combination of multiple muscles. EMG drift was largest during Warmup and at the beginning of each weight session. The results suggest using EMG feedback of multiple involved muscles and from at least 10 consecutive strides (5.5 s) to benefit from the increases in detection rate in HITL optimization. In combination with up to 20 excluded acclimatization strides, after changing the assistance condition, we advise exploring about 16.5 s of walking to obtain reliable EMG-based feedback. To minimize the negative impact of EMG drift on the detection rate, at least 6 min of Warmup should be performed and breaks during the optimization should be avoided. Future studies should investigate additional feedback variables based on EMG, methods to reduce their variability and drift, and should apply the outcomes in HITL optimization with lower limb wearable robots

Joint power, joint work and lower limb muscle activity for transitions between level walking and stair ambulation at three inclinations

To enhance human mobility, training interventions and assistive lower limb wearable robotic designs must draw insights from movement tasks from daily life. This study aimed to analyze joint peak power, limb and joint work, and muscle activity of the lower limb during a series of stair ambulation conditions. We recruited 12 subjects (25.4±4.5 yrs, 180.1±4.6 cm, 74.6±7.9 kg) and studied steady gait and gait transitions between level walking, stair ascent and stair descent for three staircase inclinations (low 19°, normal 30.4°, high 39.6°). Our analysis revealed that joint peak power, limb and joint work, and muscle activity increased significantly compared to level walking and with increasing stair inclination for most of the conditions analyzed. Transition strides had no increased requirements compared to the maxima found for steady level walking and steady stair ambulation. Stair ascent required increased lower limb joint positive peak power and work, while stair descent required increased lower limb joint negative peak power and work compared to level walking. The most challenging condition was high stair inclination, which required approximately thirteen times the total lower limb joint positive and negative net work during ascent and descent, respectively. These findings suggest that training interventions and lower limb wearable robotic designs must consider the major increases in lower limb joint and muscle effort during stair ambulation, with specific attention to the demands of ascent and descent, to effectively improve human mobility

Combined estimation of gait phase and stair slope utilizing time history data

Improving the quality of life for people with amputations through active prostheses requires appropriate knowledge of the locomotion task and gait phase of the user. A shank mounted Inertial Measurement Unit based estimation method for stair slope is presented in conjunction with an improved gait phase estimation. In contrast to prior work only one Artificial Neural Network is used for the estimation of stair slope and gait phase for all three locomotion tasks and transitions between them. Utilizing past measurements should give more information to an estimation method without the need of additional sensors. By implementing a time window of 60 samples of prior measurements the gait phase and slope estimation could be improved by around 37 % and 38 % respectively comparing mean squared errors of the complete test dataset

Darmstadt stair ambulation dataset including level walking, stair ascent, stair descent and gait transitions at three stair heights

The Darmstadt stair ambulation dataset was collected to improve the control and assistance of wearable lower limb robotics. It contains the kinematics, kinetics and electromyographic data (EMG) for transitions between level walking and stair ascent, and between stair ascent and level walking. Further, it contains the data for transitions in between level walking and stair descent, and between stair descent and level walking. Twelve physically unimpaired male subjects with a mean age of 25.4 yrs and a mean weight of 74.6 kg participated in the experiments. A motion capture system was used to capture the body kinematics. Seven force plates were used in two setups to collect the ground reaction forces of eleven strides for the stair ascent and of eleven strides for the stair descent transitions. The center of pressure, the center of mass, joint angles and angular velocities were determined. Further, inverse dynamics were used to determine the lower limb joint moments and the lower limb joint power. Sixteen EMG sensors were used to collect the muscle activity of twelve muscles. As each EMG sensor also contains an inertial measurement unit (IMU), including 3D-Gyroscope, 3D-Accelerometer and 3D-Magnetometer, they were also used to capture the lower limb kinematics in parallel to the motion capture system. Stair ambulation was performed at three stair slopes. The data is provided at different processing levels including raw to fully processed data. The attached documentation will provide details about the data acquisition, the data processing and the provided data structure and format.Version 1.

Lower limb joint biomechanics-based identification of gait transitions in between level walking and stair ambulation

Lower limb exoskeletons and lower limb prostheses have the potential to reduce gait limitations during stair ambulation. To develop robotic assistance devices, the biomechanics of stair ambulation and the required transitions to level walking have to be understood. This study aimed to identify the timing of these transitions, to determine if transition phases exist and how long they last, and to investigate if there exists a joint-related order and timing for the start and end of the transitions. Therefore, this study analyzed the kinematics and kinetics of both transitions between level walking and stair ascent, and between level walking and stair descent (12 subjects, 25.4 yrs, 74.6 kg). We found that transitions primarily start within the stance phase and end within the swing phase. Transition phases exist for each limb, all joints (hip, knee, ankle), and types of transitions. They have a mean duration of half of one stride and they do not last longer than one stride. The duration of the transition phase for all joints of a single limb in aggregate is less than 35% of one stride in all but one case. The distal joints initialize stair ascent, while the proximal joints primarily initialize the stair descent transitions. In general, the distal joints complete the transitions first. We believe that energy- and balance-related processes are responsible for the joint-specific transition timing. Regarding the existence of a transition phase for all joints and transitions, we believe that lower limb exoskeleton or prosthetic control concepts should account for these transitions in order to improve the smoothness of the transition and to thus increase the user comfort, safety, and user experience. Our gait data and the identified transition timings can provide a reference for the design and the performance of stair ambulation- related control concepts