In this study, we describe the mechanical design and control scheme of a quasi-passive knee exoskeleton intended to investigate the biomechanical behavior of the knee joint during interaction with externally applied impedances. As the human knee behaves much like a linear spring during the stance phase of normal walking gait, the exoskeleton implements a spring across the knee in the weight acceptance (WA) phase of the gait while allowing free motion throughout the rest of the gait cycle, accomplished via an electromechanical clutch. The stiffness of the device is able to be varied by swapping springs, and the timing of engagement/disengagement changed to accommodate different loading profiles. After describing the design and control, we validate the mechanical performance and reliability of the exoskeleton through cyclic testing on a mechanical knee simulator. We then describe a preliminary experiment on three healthy adults to evaluate the functionality of the device on both left and right legs. The kinetic and kinematic analyses of these subjects show that the exoskeleton assistance can partially/fully replace the function of the knee joint and obtain nearly invariant moment and angle profiles for the hip and ankle joints, and the overall knee joint and exoskeleton complex under the applied moments of the exoskeleton versus the control condition, implying that the subjects undergo a considerable amount of motor adaptation in their lower extremities to the exoskeletal impedances, and encouraging more in-depth future experiments with the device.

The human knee behaves similarly to a linear torsional spring during the stance phase of walking with a stiffness referred to as the knee quasi-stiffness. The spring-like behavior of the knee joint led us to hypothesize that we might partially replace the knee joint contribution during stance by utilizing an external spring acting in parallel with the knee joint. We investigated the validity of this hypothesis using a pair of experimental robotic knee exoskeletons that provided an external stiffness in parallel with the knee joints in the stance phase. We conducted a series of experiments involving walking with the exoskeletons with four levels of stiffness, including 0%, 33%, 66%, and 100% of the estimated human knee quasi-stiffness, and a pair of joint-less replicas. The results indicated that the ankle and hip joints tend to retain relatively invariant moment and angle patterns under the effects of the exoskeleton mass, articulation, and stiffness. The results also showed that the knee joint responds in a way such that the moment and quasi-stiffness of the knee complex (knee joint and exoskeleton) remains mostly invariant. A careful analysis of the knee moment profile indicated that the knee moment could fully adapt to the assistive moment; whereas, the knee quasi-stiffness fully adapts to values of the assistive stiffness only up to ∼80%. Above this value, we found biarticular consequences emerge at the hip joint.

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In this paper, we explain that the human knee behavior in the weight acceptance phase of gait (first ~40% of gait cycle) resembles that of a linear torsional spring. This led us to study the effects of the assistance provided by a pair of quasi-passive knee exoskeletons, which implement springs in parallel with the knee joints in the weight acceptance phase. Using the exoskeletons in a series of experiments on seven participants, we found that the exoskeleton mildly but non-significantly reduces the metabolic power of walking. We also found that the metabolic power of walking is significantly correlated with both the positive rate of moment generation and positive mechanical power of the lower extremity joints. This suggests that augmenting exoskeletons can aim to reduce both the muscle force and work generation to reduce the metabolic cost of walking.

The ability to track and predict the onset of physiologic fatigue using easily measurable variables is of great importance to both civilian and military activities. In this paper, biomechanical gait variables are used to reconstruct fatigue evolution in subjects walking with a 40 kg load on a level treadmill for two hours. Fatigue is reconstructed in two steps: (1) phase space warping based feature vectors are estimated from gait variable time series; and (2) smooth orthogonal decomposition is used to extract fatigue related trends from these features. These results are verified using independently obtained measures of fatigue from breath-by-breath oxygen consumption (V˙O2) and surface electromyography (EMG) from a set of leg muscles. V˙O2 based measures for some subjects show no discernable trends. However, for a subject showing monotonically increasing oxygen consumption, the reconstructed dominant fatigue variable closely track V˙O2 measure reflecting global systemic fatigue. For the muscles showing variation in EMG-based fatigue measures, the reconstructed fatigue variables also closely track these local muscle trends. The results show that kinematic angles, which are easier quantities to measure in the field, can be used to track and predict the onset of fatigue.