Recent work has shown that exoskeletons controlled through data-driven methods can dynamically adapt assistance to various tasks for healthy young adults. However, applying these methods to populations with neuromotor gait deficits, such as post-stroke hemiparesis, is challenging. This is due not only to high population heterogeneity and gait variability but also to a lack of post-stroke gait datasets to train accurate models. Despite these challenges, data-driven methods offer a promising avenue for control, potentially allowing exoskeletons to function safely and effectively in unstructured community settings. This work presents a first step towards enabling adaptive plantarflexion and dorsiflexion assistance from data-driven torque estimation during post-stroke walking. We trained a multi-task Temporal Convolutional Network (TCN) using collected data from four post-stroke participants walking on a treadmill ($R^2$ of $0.74 \pm 0.13$). The model uses data from three inertial measurement units (IMU) and was pretrained on healthy walking data from 6 participants. We implemented a wearable prototype for our ankle torque estimation approach for exoskeleton control and demonstrated the viability of real-time sensing, estimation, and actuation with one post-stroke participant.

Background: Lower limb exoskeletons can enhance quality of life, but widespread adoption is limited by the lack of frameworks to assess their biomechanical and human-robot interaction effects, which are essential for developing adaptive and personalized control strategies. Understanding impacts on kinematics, muscle activity, and HRI dynamics is key to achieve improved usability of wearable robots. Objectives: We propose a systematic methodology evaluate an ankle exoskeleton's effects on human movement during walking and load-carrying (10 kg front pack), focusing on joint kinematics, muscle activity, and HRI torque signals. Materials and Methods: Using Xsens MVN (inertial motion capture), Delsys EMG, and a unilateral exoskeleton, three experiments were conducted: (1) isolated dorsiflexion/plantarflexion; (2) gait analysis (two subjects, passive/active modes); and (3) load-carrying under assistance. Results and Conclusions: The first experiment confirmed that the HRI sensor captured both voluntary and involuntary torques, providing directional torque insights. The second experiment showed that the device slightly restricted ankle range of motion (RoM) but supported normal gait patterns across all assistance modes. The exoskeleton reduced muscle activity, particularly in active mode. HRI torque varied according to gait phases and highlighted reduced synchronization, suggesting a need for improved support. The third experiment revealed that load-carrying increased GM and TA muscle activity, but the device partially mitigated user effort by reducing muscle activity compared to unassisted walking. HRI increased during load-carrying, providing insights into user-device dynamics. These results demonstrate the importance of tailoring exoskeleton evaluation methods to specific devices and users, while offering a framework for future studies on exoskeleton biomechanics and HRI.

Humans rely on ankle torque to maintain standing balance, particularly in the presence of small to moderate perturbations. Reductions in maximum torque (MT) production and maximum rate of torque development (MRTD) occur at the ankle with age, diminishing stability. Ankle exoskeletons are powered orthotic devices that may assist older adults by compensating for reduced muscle force and power production capabilities. They may also be able to assist with ankle strategies used for balance. However, no studies have investigated the effect of such devices on balance in older adults. Here, we model the effect ankle exoskeletons have on stability in physics-based models of healthy young and old adults, focusing on the mitigation of age-related deficits such as reduced MT and MRTD. We show that an ankle exoskeleton moderately reduces feasible stability boundaries in users who have full ankle strength. For individuals with age-related deficits, there is a trade-off. While exoskeletons augment stability in low velocity conditions, they reduce stability in some high velocity conditions. Our results suggest that well-established control strategies must still be experimentally validated in older adults.

Exoskeleton devices impose kinematic constraints on a user's motion and affect their stability due to added mass but also due to the simplified mechanical design. This paper investigates how these constraints resulting from simplified mechanical designs impact the gait kinematics and stability of users by wearing an ankle exoskeleton with changeable degree of freedom (DoF). The exoskeleton used in this paper allows one, two, or three DoF at the ankle, simulating different levels of mechanical complexity. This effect was evaluated in a pilot study consisting of six participants walking on a straight path. The results show that increasing the exoskeleton DoF results in an improvement of several metrics, including kinematics and gait parameters. The transition from 1 DoF to 2 DoF is shown to have a larger effect than the transition from 2 DoF to 3 DoF for an ankle exoskeleton. However, an exoskeleton with 3 DoF at the ankle featured the best results. Increasing the number of DoF resulted in stability values closer the values when walking without the exoskeleton, despite the added weight of the exoskeleton.

Locomotion is a primary task for human beings and an essential component for a rich quality of life. There might be diverse (neurological or muscular) causes that limit the locomotion ability in humans, especially the efficiency and effectiveness of gait. Among all multi-body segments and muscles involved in walking, those related to the ankle joint are major contributors to perform the required mechanical work (Moltedo et al., 2018; Conner et al., 2022; Vaughan et al., 1999). Over the last decades, wearable assistive ankle-foot orthoses (AAFOs) have been developed and applied to assist ankle motion in humans. The main aim of these devices is to either reinforce and enhance the mobility in able-bodied subjects (Moltedo et al., 2018), or to restore, assist or rehabilitate lost functions of people with motor disorders (Moltedo et al., 2018; Alam et al., 2014; Bayón et al., 2023; Shorter et al., 2013). Despite the end goal to be achieved with the AAFO, a major distinction between these devices can be made according to their working principle. Passive AAFOs are those devices that rely on passive elements such as dampers or springs to store and release energy during gait, containing no control or electronics. Quasi-passive (or semi-active) AAFOs use computer control to adjust the performance of a passive element, and sometimes also hold a small motor to modulate their stiffness.

Leo Medrano, a PhD student in the Neurobionics Lab at the University of Michigan, tests out an ankle exoskeleton on a two-track treadmill. Researchers were able to give the exoskeleton user direct control to tune its behavior, allowing them to find the right torque and timing settings for themselves. To transform human mobility, exoskeletons need to interact seamlessly with their user, providing the right level of assistance at the right time to cooperate with our muscles as we move. To help achieve this, University of Michigan researchers gave users direct control to customize the behavior of an ankle exoskeleton. Not only was the process faster than the conventional approach, in which an expert would decide the settings, but it may have incorporated preferences an expert would have missed.

Couch potatoes trying to get in shape could one day be helped along their fitness journey by an ankle exoskeleton that makes it easier and less tiring to run. The robotic device attaches to the ankle of joggers and was found in lab tests to slash energy expenditure by 14 per cent when compared to standard running shoes. It was created by robotics experts at Stanford University and funded in part by sporting behemoth Nike. The engineers behind the project say the equipment currently only works on a treadmill and when the device is hooked up to a machine via cables. However, they are working to make the exoskeleton portable and lightweight and easy to integrate into future running equipment.