Neck injuries and the related pain have a high prevalence and represent an important health problem. To properly diagnose and treat them, practitioners need an accurate system for measuring Cervical Range Of Motion (CROM). This article describes the development and validation of an inexpensive, small (4 cm × 4 cm × 8 cm), light (< 200 g) and easy to use solution for measuring CROM using wearable inertial sensors. The proposed solution has been designed with the clinical practice in mind, after consulting with practitioners. It is composed of: (a) two wearable wireless MEMS-based inertial devices, (b) a recording and report generation software application and (c) a measurement protocol for assessing CROM. The solution provides accurate (none of our results is outside the ROM ranges when compared with previously published results based on an optical tracking device) and reliable measurements (ICC = 0.93 for interrater reliability when compared with an optical tracking device and ICC > 0.90 for test-retest reliability), surpassing the popular CROM instrument’s capabilities and precision. It also fulfills the needs for clinical practice attending to effectiveness, efficiency (4 min from setup to final report) and user’s satisfaction (as reported by practitioners). The solution has been certified for mass-production and use in medical environments.

Background: Robotic devices have been used to rehabilitate walking function after stroke. Although results suggest that post-stroke patients benefit from this non-conventional therapy, there is no agreement on the optimal robot-assisted approaches to promote neurorecovery. Here we present a new robotic therapy protocol using a grounded exoskeleton perturbing the ankle joint based on tacit learning control. Method: Ten healthy individuals and a post-stroke patient participated in the study and were enrolled in a pilot intervention protocol that involved performance of ankle movements following different trajectories via video game visual feedback. The system autonomously modulated task difficulty according to the performance to increase the challenge. We hypothesized that motor learning throughout training sessions would lead to increased corticospinal excitability of dorsi-plantarflexor muscles. Transcranial Magnetic Stimulation was used to assess the effects on corticospinal excitability. Results: Improvements have been observed on task performance and motor outcomes in both healthy individuals and post-stroke patient case study. Tibialis Anterior corticospinal excitability increased significantly after the training; however no significant changes were observed on Soleus corticospinal excitability. Clinical scales showed functional improvements in the stroke patient. Discussion and Significance: Our findings both in neurophysiological and performance assessment suggest improved motor learning. Some limitations of the study include treatment duration and intensity, as well as the non-significant changes in corticospinal excitability obtained for Soleus. Nonetheless, results suggest that this robotic training framework is a potentially interesting approach that can be explored for gait rehabilitation in post-stroke patients.

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Virtual reality (VR) has emerged as a valid addition to conventional therapy in rehabilitation and sports medicine. This has enabled the development of novel and affordable rehabilitation strategies. However, before VR devices can be used in these situations, they must accurately capture the range of motion of the body-segment where they are mounted. This study aims to state the accuracy of the Oculus Touch v2 controller when used to measure the elbow’s motion in the sagittal plane. The controller is benchmarked against an inertial sensor (ENLAZA$$^{\mathrm{TM}}$$ TM ), which has already been validated as a reliable measurement device. We have developed a virtual environment that matches both the Oculus Touch v2 and the inertial sensor orientations using a digital goniometer. We have also collected the orientation measurements given by each system for a set of 17 static angles that cover the full range of normal elbow flexion and hyperextension motion, in 10° intervals from − 10°  (hyperextension) to 150° (flexion). We have applied the intra-rater reliability test to assess the level of agreement between the measurements of these devices, obtaining a value of 0.999, with a 95% confidence interval ranged from 0.996 to 1.000. By analyzing the angle measurement outcomes, we have found that the accuracy degrades at flexion values between 70° and 110°, peaking at 90°. The accuracy of Oculus Touch v2 when used to capture the elbow’s flexion motion is good enough for the development of VR rehabilitation applications based on it. However, the flaws in the accuracy that have been revealed in this experimental study must be considered when designing such applications.

Robotic exoskeletons that induce leg movement have proven effective for lower body rehabilitation, but current solutions offer limited gait patterns, lack stabilization, and do not properly stimulate the proprioceptive and balance systems (since the patient remains in place). Partial body weight support (PBWS) systems unload part of the patient’s body weight during rehabilitation, improving the locomotive capabilities and minimizing the muscular effort. HYBRID is a complete system that combines a 6DoF lower body exoskeleton (H1) with a PBWS system (REMOVI) to produce a solution apt for clinical practice that offers improves on existing devices, moves with the patient, offers a gait cycle extracted from the kinematic analysis of healthy users, records the session data, and can easily transfer the patient from a wheelchair to standing position. This system was developed with input from therapists, and its response times have been measured to ensure it works swiftly and without a perceptible delay.