Powered transfemoral prostheses offer the potential to improve mobility and quality of life for individuals with amputations. This study aimed to develop and validate an OpenSim model of a subject with a unilateral transfemoral amputation wearing a powered transfemoral prosthesis and to compare the model’s performance with that of a model without prosthesis characteristics. We utilized experimental walking data from a single transfemoral amputee subject to demonstrate the feasibility of the model. Inverse kinematics and inverse dynamics were performed to compare the results using the encoder and current data of the knee and ankle actuators, which served as ground truth. The model with prosthesis characteristics demonstrated a closer match to the actuator data, particularly during the stance phase, suggesting that it better reflects the dynamic features of a real powered prosthesis. However, discrepancies were observed during the swing phase, highlighting the need for further refinements. This study provides valuable insights into the importance of incorporating prosthesis characteristics in biomechanical models to simulate joint behavior accurately. It has implications for the development and assessment of prosthetic devices.

The design of impedance controllers for sloped walking with a transfemoral prosthesis is a complex control problem that generally results in numerous tuning parameters. This study proposes an easy-to-tune sloped walking control scheme. While the ankle is controlled using impedance control, the knee is controlled using a hybrid strategy of impedance control and trajectory tracking. This study derived continuous, nonlinear impedance functions for the ankle and knee joints using optimization. Principal component analysis of the impedance functions revealed trends that can be used to design impedance controllers for any given slope angle. Said trends were further used to establish a tuning regime which was subsequently tested on a transfemoral prosthesis in an emulator study. The generated gait kinematics and kinetics were found to follow the trends of healthy sloped walking data.

Impedance controllers are popularly used in the field of lower limb prostheses and exoskeleton development. Such controllers assume the joint to be a spring-damper system described by a discrete set of equilibria and impedance parameters. These parameters are estimated via a least squares optimization that minimizes the difference between the controller's output torque and human joint torque. Other researchers have used perturbation studies to determine empirical values for ankle impedance. The resulting values vary greatly from the prior least squares estimates. While perturbation studies are more credible, they require immense investment. This paper extended the least squares approach to reproduce the results of perturbation studies. The resulting ankle impedance parameters were successfully tested on a powered transfemoral prosthesis, AMPRO II. Further, the paper investigated the effect of multiple equilibria on the least squares estimation and the performance of the impedance controller. Finally, the paper uses the proposed least squares optimization method to estimate knee impedance.

For amputees, walking on sloped surfaces is one of the most challenging tasks in their daily lives. Unfortunately, designing a prosthesis that can effectively adapt to varying terrain is an ongoing problem. In this paper, we propose a unified control scheme that enables a powered transfemoral prosthesis to perform human-like walking on sloped terrains regardless of the slope and without any knowledge of the upcoming slope. The control scheme implements impedance control and trajectory tracking during the stance and swing phase, respectively. In the impedance control scheme, properly tuned impedance parameters are used to provide a stable and compliant stance phase that adapts to the slope of the ground. During the swing phase, the system is controlled by a Proportional-Derivative (PD) controller to track the desired trajectories based on cubic Bezier polynomials. These trajectories were obtained by solving an offline optimization problem compared to human slope walking data. Any slope walking trajectories can be generated online by using the optimized Bezier coefficients. At the terminal swing phase, a low gain PD controller is utilized to adapt to the unexpected terrains and smoothly track the generated trajectories. The proposed control framework is implemented on a powered transfemoral prosthesis, AMPRO II, on various slopes. The results validate the controller's ability to adapt to terrain inclinations within the range of ± 10°.

To generate a dynamic bipedal walking with foot rolling motion for bipedal robot, hybrid trajectory optimization is capable of planning level walking with great energetic efficiency. However, the direct implementation of this optimization requires different sets of variables to express different active contact constraints, which can be complicated to implement. To simplify the optimization formulation, we propose the generalized contact constraints where the same set of variables are used through all the walking phases. By changing the variable and constraint bounds, different contact constraints for different contact conditions can be generally expressed. The proposed modifications are applied on the bipedal robot AMBER 3, where the optimization results on different terrains are compared and discussed. On the other hand, it is known that a randomized initial guess can be used to solve this optimization, yet its effect on the gaits on different terrains is unclear. As a result, we analyzed the sensitivity of the optimization to a set of randomized initial guesses. The level and downslope walking gaits are also validated via the experiments on AMBER 3.

Mobility aids such as canes, crutches, and walkers are widely used among the elderly and people with poor balance as a means for physical support to improve balance during walking. Advances in technology have led to the development of robotic walking aids which can provide active physical support and navigation by incorporating sensors and actuators in conventional walking aids. These devices have shown great potentials in enhancing mobility; however, few studies have employed the functionality to detect user's posture or have investigated the feedback approaches to augment this information. Thus, it is important for those with impaired balance not to just be passively supported by mobility aids but to also actively be engaged in correcting their posture. In this paper, we introduce the concept of a sensory augmentation walker that can provide real-time directional information via skin stretch feedback to the user. The design and the user study of perceiving directions on a novel skin stretch handle are presented. Results show that the directional cues rendered by skin stretch feedback can be accurately perceived by all healthy young subjects (n = 8) at their fingertips, while the palm is shown to be a less effective location for perceiving this kind of feedback. Positive feedback about the benefits in helping people with improper posture is also reported. Based on the results of this pilot study, a full system for improving balance performance in elderly or people with impaired balance will be undertaken.

Trajectory optimization with direct collocation are widely used in various bipedal walking studies, from dynamic simulation in biomechanics to efficient bipedal walking motion generation with multiple contact domains. Although the latter has gained popularity, most of the approaches in this field in general rely on pre-determined contact sequence (domains). This motivates us to use trajectory optimization through contact for generating an efficient and human-like walking gait, because this approach can automatically generate the contact sequence by solving a nonlinear program (NLP) with complementary constraints. However, in this approach the initial guess affects the result significantly, and the direct collocation with Euler method may not be accurate enough for the system dynamics. Therefore, we propose a modified framework and constraints to improve the generated results. We used a zero moment point (ZMP)-based flat-feet walking gait as an initial guess. We also show how to add virtual components like springs at ankle joints to alter the behavior of the resultant walking gait. In addition, considering the one-sided springs at the passive toe joints of the bipedal robot AMBER 3, additional complementary constraints are introduced for a better match of the full dynamics. The results of our modified approach with different constraint conditions are presented and discussed.

Physical interactions between human and machine are essential in facilitating effective physical therapy training programs. Nowadays, physical training largely involves robotic assistive devices or wearable haptics. In this study, we propose a lightweight wearable sensory augmentation device using skin stretch feedback to provide individuals with additional sensory cues during balance training. The goals of this study are i) to determine the effectiveness of the proposed novel system in improving the dynamic stability of healthy individuals and ii) to test the efficacy of additional cutaneous cues in substituting for missing visual feedback in said healthy subjects. The entire system comprises of a haptic wristband, a visual display, and a force platform. The haptic wristband provides real-time skin stretch feedback at the dorsal side of the wrist in response to user's postural sway. Center of pressure (COP) was displayed on a screen and users were asked to move the COP to a target position displayed on the screen by controlling their body posture in the sagittal plane. Results showed that subjects could complete the tasks when they received both visual feedback and skin stretch feedback by shifting their weights. When visual feedback was subsequently removed, subjects successfully interpreted the tactile cues at the wrist from the skin stretch device and completed the tasks. Larger sample size, diverse groups, and longitudinal studies are needed to demonstrate the effectiveness of the proposed device as a balance rehabilitation tool.

Powered transfemoral prostheses are robotic systems that aim to restore the mobility of transfemoral amputees by mimicking the functionalities of healthy human legs. The advantage of using a powered prosthetic device is the enhanced performance on various terrains. One of the most frequent terrain found during daily locomotion (other than flat ground) is the surface with slope. In this work, we introduce a framework to generate upslope walking gaits automatically utilizing an online algorithmic formulation. This approach is inspired from analyzing human gait characteristics during upslope walking. In particularly, it is found that the ankle and knee trajectories of upslope walking share a similar pattern with flat ground walking during the middle section (from 20% to 80%) of one step. This observation motivates us to propose an approach of blending the first portion of nominal flat ground gaits with a set of cubic splines to achieve upslope gaits. Importantly, parameters of these cubic splines are solved using an online optimization, which gives the users ability to traverse in different terrains without using any intention detection algorithm. For the last portion of a step, an impedance controller with low gains is considered upon the contact of prosthetic legs to the ground, which allows the users to step onto unknown terrains. The proposed framework is validated on a custom transfemoral prosthesis AMPRO II with showing automatic motion switches between flat ground and upslope walking.