Since the 1960s, research into the medical applications of wearable robots has been fueled by a growing need for assistive technologies that can help individuals impacted by musculoskeletal disorders such as sarcopenia independently manage common activities of daily living while maintaining their natural physical capacities. While contemporary research has demonstrated promising developments, the usefulness of exoskeletons in everyday settings remains limited due to design factors that include the limited practicality of existing battery technologies, the need for actuators exhibiting a high output torque-to-weight ratio, a need for modular designs that are minimally disruptive to wearers, and the need for control systems that can actively work in sync with a user. To explore potential solutions to some of these limiting factors, a novel ankle exoskeleton prototype supporting ankle plantarflexion during gait was developed under a design approach that seeks to optimize actuator performance. The actuation system featured in this prototype consists of a custom dual-action linear actuator that can provide mechanical assistance to both ankles via a single BLDC motor and an underlying Bowden cable system. The metric ball screw and BLDC motor implemented in the linear actuator were selectively chosen to minimize the motor torque and current required to assist wearers impacted by a degree of muscle weakness under an assistance-as-needed design paradigm. The prototype additionally features an array of force sensing resistors for tracking gait progression and exploring potential user-based control strategies for synchronizing the exoskeleton actuator with a wearer's gait. Performance analysis for this prototype was conducted with the goal of quantifying the exoskeleton's force output, actuator settling time, and the control system's ability to track gait and identify key events in the gait cycle. The preliminary findings of this experimental analysis support the viability of the actuator's dual-action concept and gait progression tracking system as a starting ground for future developments that build on a similar design optimization approach. / Master of Science / Healthy aging and good physical health are characterized in part by one's ability to self-manage a core set of daily living tasks, one of the most prominent of which is gait. Relative to existing assistive technologies such as wheelchairs, exoskeletons provide the unique benefit of providing active mechanical support while encouraging users to rely on their natural physical capabilities. While recent technological developments in the field of wearable robots show promise, the viability of exoskeletons in an everyday setting remains constrained in part by three underlying design factors: the limited practicality of existing battery technologies, a need for actuators that can satisfactorily balance a high force output with weight, and a need for control strategies that can properly synchronize wearable robots with users. The ankle exoskeleton prototype introduced in this thesis is a portable, energetically autonomous wearable device that supports ankle plantarflexion during the push-off stages of the gait cycle. The design for this prototype seeks to optimize actuator performance and features a novel dual-action linear actuator that provides walking support to both ankles using a single DC motor. The exoskeleton additionally features an array of contact sensors that track the user's progression throughout the gait cycle and allow for the examination of potential control strategies for synchronizing the actuator with the wearer's gait. Performance analysis conducted for this prototype quantifies the exoskeleton's force output, approximates the actuator's settling time between steps, and assesses the control system's ability to track gait and synchronize with a wearer. The findings from these performance evaluation experiments support the viability of the actuator's dual-action concept and gait progression tracker as a foundation for future developments that build on a similar design optimization approach.

Ankle exoskeletons are designed to help people with movement weakness to restore the walking ability . However, people with gait pathology, for instance, drop foot, usually have difficulties in lifting the front part of foot during gait. Thus, different from health subjects, both plantarflexion and dorsiflexion assistance are needed for them to walk better. The purpose of this thesis is to implement an EMG-­driven control strategy for a cable­driven ankle exoskeleton while exploring the use of reinforcement learning in exoskeleton control. The work uses an EMG­-driven musculoskeletal model to predict ankle joint torque. The model uses EMG signals from 4 lower­-limb muscles related to plantarflexion and dorsiflexion to obtain ankle torque and stiffness. The dynamic model for an ankle exoskeleton is built for simulation. The reinforcement learning controller is designed for the ankle exoskeleton tracking the desired ankle joint torques. Based on simulation results, two main conclusions can be drawn, one is that the proposed control strategy can provide precise torque assistance; the other is that using reinforcement learning to track the desired assistive trajectories is effective. / Ankel exoskeletons är utformade för att hjälpa människor med rörelsessvaghet att återställa gångförmågan. Men personer med gångpatologi, till exempel faller fot, har vanligtvis svårt att lyfta den främre delen av foten under gång. Således, annorlunda än hälsoämnen, behövs både plantarflexion- och dorsiflexionshjälp för att de ska kunna gå bättre. Syftet med denna avhandling är att implementera en EMG­-driven kontrollstrategi för ett kabeldrivet vristexoskelet samtidigt som man utforskar användningen av förstärkningsinlärning vid exoskeletskontroll. Arbetet använder en EMG­-driven muskuloskeletal modell för att förutsäga fotledets vridmoment. Modellen använder EMG-­signaler från 4 nedre extremiteter muskler relaterade till plantarflexion och dorsiflexion för att uppnå vridmoment och styvhet. Den dynamiska modellen för ett fotoskeleton är byggd för simulering. Förstärkningsinlärningskontrollern är utformad för fotledets exoskelett som spårar önskade vridmoment i fotleden. Baserat på simuleringsresultat kan två huvudsakliga slutsatser dras, en är att den föreslagna kontrollstrategin kan ge exakt momenthjälp; den andra är att det är effektivt att använda förstärkningslärande för att spåra de önskade hjälpbanorna.