Although the field of wearable robotic exoskeletons is rapidly expanding, there are several barriers to entry that discourage many from pursuing research in this area, ultimately hindering growth. Chief among these is the lengthy and costly development process to get an exoskeleton from conception to implementation and the necessity for a broad set of expertise. In addition, many exoskeletons are designed for a specific utility and are confined to the laboratory environment, limiting the flexibility of the designed system to adapt to answer new questions and explore new domains. To address these barriers, we present OpenExo, an open-source modular untethered exoskeleton framework that provides access to all aspects of the design process, including software, electronics, hardware, and control schemes. To demonstrate the utility of this exoskeleton framework, we performed benchtop and experimental validation testing with the system across multiple configurations, including hip-only incline assistance, ankle-only indoor and outdoor assistance, hip-and-ankle load carriage assistance, and elbow-only weightlifting assistance. All aspects of the software architecture, electrical components, hip and Bowden-cable transmission designs, and control schemes are freely available for other researchers to access, use, and modify when looking to address research questions in the field of wearable exoskeletons. Our hope is that OpenExo will accelerate the development and testing of new exoskeleton designs and control schemes while simultaneously encouraging others, including those who would have been turned away from entering the field, to explore new and unique research questions.

Lower-limb exoskeletons, regardless of their control strategies, have been shown to alter a user’s gait just by the exoskeleton’s own mass and inertia. The characterization of these differences in joint kinematics and kinetics under exoskeleton-like added mass is important for the design of such devices and their control strategies. In this study, 19 young, healthy participants walked overground at self-selected speeds with six added mass conditions and one zero-added-mass condition. The added mass conditions included +2/+4 lb on each shank or thigh or +8/+16 lb on the pelvis. OpenSim-derived lower-limb sagittal-plane kinematics and kinetics were evaluated statistically with both peak analysis and statistical parametric mapping (SPM). The results showed that adding smaller masses (+2/+8 lb) altered some kinematic and kinetic peaks but did not result in many changes across the regions of the gait cycle identified by SPM. In contrast, adding larger masses (+4/+16 lb) showed significant changes within both the peak and SPM analyses. In general, adding larger masses led to kinematic differences at the ankle and knee during early swing, and at the hip throughout the gait cycle, as well as kinetic differences at the ankle during stance. Future exoskeleton designs may implement these characterizations to inform exoskeleton hardware structure and cooperative control strategies.

To improve exoskeleton designs, it is crucial to understand the effects of the placement of such added mass on a broad spectrum of users. Most prior studies on the effects of added mass on gait have analyzed young adults using discrete point analysis. This study quantifies the changes in gait characteristics of young and middle-aged adults in response to added mass across the whole gait cycle using statistical parametric mapping. Fourteen middle-aged and fourteen younger adults walked during 60 s treadmill trials under nine different loading conditions. The conditions represented full-factorial combinations of low (+3.6 lb), medium (+5.4 lb), and high (+10.8 lb) mass amounts at the thighs and pelvis. Joint kinematics, kinetics and muscle activations were evaluated. The young and middle-aged adults had different responses to added mass. Under pelvis loading, middle-aged adults did not adopt the same kinematic responses as younger adults. With thigh loading, middle-aged adults generally increased knee joint muscle activity around heel strike, which could have a negative impact on joint loading. Overall, as age may impact the user’s response to an exoskeleton, designers should aim to include sensors to directly monitor user response and adaptive control approaches that account for these differences.

Exoskeletons are human-robot interfaces that have enormous potential to assist people with everyday tasks. To improve the design of exoskeletons for use in clinical populations, it is important to further our understanding of how exoskeleton design and control parameters lead to sub-optimal effectiveness. Here we simulated the effect of three factors, gait variability, wearer-exoskeleton delays, and exoskeleton inertia, have on the predicted energy assistance provided by an exoskeleton with a finite-state controller trained on a set of stroke survivors' free walking gait data. Results indicate that larger errors between the wearer's desired ankle trajectory and the exo's estimated ankle trajectory result in statistically large reductions in the actual assistance provided. Specifically lags on the order of even 10 ms can illustrate statistically sub-optimal performance. Likewise subjects that exhibit large gait variability will have a statistical reduction in actual assistance. However, reasonably low exoskeleton inertias are not significant as a factor in terms of sensitivity to wearer assistance. Therefore, to improve cooperative control algorithms for exoskeletons and achieve true assistance based on wearer induced motion, this work implies that designers should prioritize minimizing delays and wearers should train to reduce variability in order to maximize energy savings.