Most individuals who experience a stroke exhibit several sensorimotor impairments that limit their independence in everyday activities. Hemiparetic gait is frequently characterized by reduced knee flexion in swing due to knee stiffness or muscle weakness and knee hyperextension or knee buckling in the stance phase. Recently, unilateral-powered orthoses have been designed to overcome the limitations of the passive knee-ankle-foot orthoses. This study presents a unilateral Active Knee Orthosis Exoskeleton, AKO-$\beta$, endowed with a series elastic actuator and designed to assist the knee in flexion and extension movements. The paper describes the system mechatronic design and its characterization on the bench, the control system, and pilot experiments with three post-stroke participants. The device has a weight of 1.78 kg on the user's leg, with a lateral encumbrance of 76 mm. The pilot experiments aimed to verify the effects of the exoskeleton assistance in hemiparetic gait patterns. When walking with the device, participants on average increased the knee flexion on the paretic side by 18.70 deg (+44.9%) during swing and decreased knee hyperextension in stance by 4.50 deg, compared to walking without it. Overall, when walking with the exoskeleton, subjects showed improved Gait Variable Score of the paretic knee profile by 37.5% compared to walking without it. The temporal and spatial gait symmetry indexes did not show clear changes, although an improvement in symmetry was observed in two of the three participants. These preliminary results suggest the potential benefits of the unilateral Active Knee Orthosis exoskeleton to enhance and restore mobility in individuals with hemiparetic gait.

Lower-limb exoskeletons are wearable devices whose main purposes are human rehabilitation and bilateral locomotion assistance. In particular, there is a growing interest for their use to symmetrize the gait of hemiparetic patients. This often consists in using the kinematics of the less affected side as a reference for the most affected one. In this work, we followed this approach to design a symmetrization algorithm using the formalism of motor primitives, i.e. a low-dimensional set of signals that provide the desired assistance through their combination. The amount of variables to be stored in memory is thus intrinsically limited, and this framework is particularly adapted to include other modes of assistance and/or transitions between locomotion tasks. In this paper, we report the preliminary validation of this newly developed algorithm with a hip exoskeleton and a single participant replicating hemiparetic walking. Results show that the algorithm effectively managed to reduce both temporal and spatial gait asymmetry.

Lower-limb exoskeletons are robotic devices that can provide assistance to human locomotion. Since they are expected to be used in ecological environments, their control strategy should handle different kinds of daily-life situations. Taking inspiration from the human neuromuscular system - and particularly from the socalled motor primitives - may help in adapting the type of delivered assistance to different locomotion tasks. In this work, we validated the combination of simplified primitives and a musculoskeletal model for assisting healthy subjects with a hip exoskeleton. This framework showed adaptation to the user's gait for different slope inclinations, although its effects on the subject's speed and their perceived effort showed no significant improvement compared to wearing the device in transparent mode.

For a lower limb exoskeleton, accurate and continuous estimation of the gait phase in real time is a fundamental requirement to provide a well-tailored assistive action at the proper time in the gait cycle (GC). This article presents a new gait phase estimator for a portable hip exoskeleton based on discrete wavelet transform (DWT) and adaptive oscillators. The algorithm is capable of continuously tracking the gait phase and identifying the relevant biomechanical gait events online, i.e., heel strike (HS) and toe-off (TO). The proposed method exploits only the hip joint angle signals measured by hip encoders, avoiding the need to use additional sensors to those already built in the exoskeleton. The novel phase estimator has been benchmarked against a state-of-the-art method, based on the maximum flexion angle (MFA), with pressure-sensitive insoles used as the reference ground truth for the event detection. To validate the method, two experimental activities were carried out. Experiments conducted with eight healthy subjects walking on a treadmill at different speeds, with and without hip assistance, demonstrated that the DWT-based method outperformed the MFA method in all operative conditions, reducing the rms of the phase reset error by 64.0% in assistive mode, and identifying the HS and TO events with low delay (0.4% and 1.1% GC, respectively, for HS and TO). Experiments carried out with three transfemoral amputees showed similar performance, paving the way for clinical applications of the method.