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In this paper, we present the design, control, and preliminary evaluation of the Symbitron exoskeleton, a lower limb modular exoskeleton developed for people with a spinal cord injury. The mechanical and electrical configuration and the controller can be personalized to accommodate differences in impairments among individuals with spinal cord injuries (SCI). In hardware, this personalization is accomplished by a modular approach that allows the reconfiguration of a lower-limb exoskeleton with ultimately eight powered series actuated (SEA) joints and high fidelity torque control. For SCI individuals with an incomplete lesion and sufficient hip control, we applied a trajectory-free neuromuscular control (NMC) strategy and used the exoskeleton in the ankle-knee configuration. For complete SCI individuals, we used a combination of a NMC and an impedance based trajectory tracking strategy with the exoskeleton in the ankle-knee-hip configuration. Results of a preliminary evaluation of the developed hardware and software showed that SCI individuals with an incomplete lesion could naturally vary their walking speed and step length and walked faster compared to walking without the device. SCI individuals with a complete lesion, who could not walk without support, were able to walk with the device and with the support of crutches that included a push-button for step initiationOur results demonstrate that an exoskeleton with modular hardware and control allows SCI individuals with limited or no lower limb function to receive tailored support and regain mobility.

This work was devoted to preliminary test the Achilles ankle exoskeleton and its NeuroMuscular Controller (NMC) with a test pilot affected by incomplete spinal cord injury. The customization of the robot controller, i.e. a subject-specific tailoring of the assistance level, was performed and a 10-session training to optimize human-robot interaction was finalized. Results demonstrated that controller tuning was in line with the functional clinical assessment. NMC adapted to the variable walking speed during the training and the test pilot was successfully trained in exploiting robotic support and also improved his performance in terms of walking speed and stability. After the training, a higher speed could also be achieved during free walking and hence a slight unexpected rehabilitation effect was evidenced.

Powered exoskeletons are among the emerging technologies claiming to assist functional ambulation. The potential to adapt robotic assistance based on specific motor abilities of incomplete spinal cord injury (iSCI) subjects, is crucial to optimize Human-Robot Interaction (HRI). Achilles, an autonomous wearable robot able to assist ankle during walking, was developed for iSCI subjects and utilizes a NeuroMuscular Controller (NMC). NMC can be used to adapt robotic assistance based on specific residual functional abilities of subjects. The main aim of this pilot study was to analyze the effects of the NMC-controlled Achilles, used as an assistive device, on chronic iSCI participants’ performance, by assessing gait speed during 10-session training of robot-aided walking. Secondary aims were to assess training impact on participants’ motion, clinical and functional features and to evaluate subjective perspective in terms of attitude towards technology, workload, usability and satisfaction. Results showed that 5 training sessions were necessary to significantly improve robot-aided gait speed on short paths and consequently to optimize HRI. Moreover, the training allowed participants who initially were not able to walk for 6 minutes, to improve gait endurance during Achilles-aided walking and to reduce perceived fatigue. Improvements were obtained also in gait speed during free walking, thus suggesting a potential rehabilitative impact, even if Achilles-aided walking was not faster than free walking. Participants’ subjective evaluations indicated a positive experience

In this study, our goal was to improve the standing balance of people with a spinal cord injury by using a wearable exoskeleton that has ankle and knee actuation in the sagittal plane. Three test-pilots that have an incomplete spinal cord injury wore the exoskeleton and tried to maintain standing balance without stepping while receiving anteroposterior pushes. Two balance controllers were tested: One providing assistance based on the subject's body sway and one based on the whole body momentum. For both controllers, the balance performances of the test-pilots wearing the exoskeleton were assessed based on the center of mass kinematics and compared to the condition in which the device did not provide any assistance. One of the test-pilots was not able to maintain balance without assistance, but could withstand small pushes when any of the balance controllers was implemented. For this test-pilot the recovery time and sway amplitude hardly varied with the type of balance controller that was used. For the other two test-pilots the recovery time and the sway amplitude were smallest using the body sway controller. In conclusion, the wearable exoskeleton with balance controller was able to improve the balance performance of the test-pilots by reducing the recovery time after a perturbation and by enabling one of the test-pilots to maintain balance, who could not maintain balance by himself.

A novel fully wearable system based on a smart wristband equipped with stretchable strain gauge sensors and readout electronics have been assembled and tested to detect a set of movements of a hand crucial in rehabilitation procedures. The high sensitivity of the active devices embedded on the wristband do not need a direct contact with the skin, thus maximizing the comfort on the arm of the tester. The gestures done with the device have been auto-labeled by comparing the signals detected in real-Time by the sensors with a commercial infrared device (Leap motion). Finally, the system has been evaluated with two machine-learning algorithms Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), reaching a reproducibility of 98% and 94%, respectively.