The Cable Assistive Rehabilitation Elbow Exoskeleton is an active arm assistance device for in-home rehabilitation for individuals who suffered a traumatic brain injury, such as stroke, that experienced elbow flexion/extension impairment. A robotic elbow exoskeleton can provide ongoing therapeutic treatment to retrain arm movement functionality to perform activities of daily living. Providing an accessible, lightweight robotic exoskeleton is an ongoing challenge for wearable devices. Our proposed elbow exoskeleton introduces a cable-driven design using a bidirectional, dual pulley system mated with a high torque motor and a custom 17.5:1 planetary gearbox manufactured using high strength engineering stereolithography resin material. The cable-driven dual pulley system transfers the rotary motion to actuate an arm brace for elbow joint flexion and extension. Benchtop experiments demonstrated a maximum output torque of 26 Nm while lifting a 1 kg object. Results exceeded the minimum joint torque and velocity requirement to carry out day-to-day lifting activities. The designed actuation system provided a transmission mass reduction of 39% compared to conventional actuators, lowered overall cost by applying rapid fabrication techniques, and provided formability for a compact elbow exoskeleton design. In all, the system weighs less than 8.5 kg that can translate the unit to an in-home rehabilitation device.

A mechanical phase variable represents human gait progression that can parameterize the joint kinematic trajectories for lower-limb prostheses control. Current phase variables uses unactuated states, such as the human thigh angle and its derivative or integral, to compute the thigh phase angle to estimate gait phase during stride. With time-dependent states, the phase variable can potentially produce abnormal behavior for the prosthesis controller when the user instantaneously changes speed or inclination. We propose a probabilistic-based approach that uses a maximum likelihood estimation technique from only the thigh angle to derive a holonomic phase variable for a continuous gait phase estimation. Since it does not depend on a time-wise parameter (either derivative or integral), the phase variable can respond to instantaneous changes (e.g., unwanted disturbances) during locomotion. We evaluated the proposed phase variable algorithm across various walking speeds using able-bodied subject datasets, and introduced start and stop transitions to evaluate robustness for non-rhythmic behaviors. The analysis demonstrates a probabilistic adaptation for correcting gait phase abnormalities that can drive locomotion progression for lower-limb prostheses control.

Although there has been recent progress in control of multi-joint prosthetic legs for periodic tasks such as walking, volitional control of these systems for non-periodic maneuvers is still an open problem. In this paper, we develop a new controller that is capable of both periodic walking and common volitional leg motions based on a piecewise holonomic phase variable through a finite state machine. The phase variable is constructed by measuring the thigh angle, and the transitions in the finite state machine are formulated through sensing foot contact together with attributes of a nominal reference gait trajectory. The controller was implemented on a powered knee-ankle prosthesis and tested with a transfemoral amputee subject, who successfully performed a wide range of periodic and non-periodic tasks, including low- and high-speed walking, quick start and stop, backward walking, walking over obstacles, and kicking a soccer ball. The proposed approach is expected to provide better understanding of volitional motions and lead to more reliable control of multi-joint prostheses for a wider range of tasks.

Control systems for powered prosthetic legs typically divide the gait cycle into several periods with distinct controllers, resulting in dozens of control parameters that must be tuned across users and activities. To address this challenge, this paper presents a control approach that unifies the gait cycle of a powered knee-ankle prosthesis using a continuous, user-synchronized sense of phase. Virtual constraints characterize the desired periodic joint trajectories as functions of a phase variable across the entire stride. The phase variable is computed from residual thigh motion, giving the amputee control over the timing of the prosthetic joint patterns. This continuous sense of phase enabled three transfemoral amputee subjects to walk at speeds from 0.67 to 1.21 m/s and slopes from -2.5 to +9.0 deg. Virtual constraints based on task-specific kinematics facilitated normative adjustments in joint work across walking speeds. A fixed set of control gains generalized across these activities and users, which minimized the configuration time of the prosthesis.

This paper presents the experimental validation of a novel control strategy that unifies the entire gait cycle of a powered knee-ankle prosthetic leg without the need to switch between controllers for different periods of gait. Current control methods divide the gait cycle into several sequential periods each with independent controllers, resulting in many patient-specific control parameters and switching rules that must be tuned for a specific walking speed. The single controller presented is speed-invariant with a minimal number of control parameters to be tuned. A single, periodic virtual constraint is derived that exactly characterizes the desired actuated joint motion as a function of a mechanical phase variable across walking cycles. A single sensor was used to compute a phase variable related to the residual thigh angle's phase plane, which was recently shown to robustly represent the phase of non-steady human gait. This phase variable allows the prosthesis to synchronize naturally with the human user for intuitive, biomimetic behavior. A custom powered knee-ankle prosthesis was designed and built to implement the control strategy and validate its performance. A human subject experiment was conducted across multiple walking speeds (1 to 3 miles/hour) in a continuous sequence with the single phase-based controller, demonstrating its adaptability to the user's intended speed.