Background: Crutches are the most common walking aids prescribed to improve mobility in subjects with central nervous system (CNS) lesions. To increase adherence to the appropriate level of crutch usage, providing load-related auditory feedback (aFB) may be a useful approach. We sensorized forearm crutches and developed a custom software to provide aFB information to both user and physical therapist (PhT).Aim: Evaluate aFB effects on load control during gait by a self-controlled case series trial.Methods: A single experimental session was conducted enrolling 12 CNS lesioned participants. Load on crutch was recorded during 10 Meter Walk Test performed with and without aFB. In both cases, crutch load data, and gait speed were recorded. Usability and satisfaction questionnaires were administered to participants and PhTs involved.Results: Reliable data were obtained from eight participants. Results showed that compared to the no FB condition, aFB yielded a significant reduction in the mean load on the crutches during gait (p = 0.001). The FB did not influence gait speed or fatigue (p > 0.05). The experience questionnaire data indicated a positive experience regarding the use of aFB from both participants' and PhTs' perspectives.Conclusion: aFB significantly improves compliance with crutch use and does not affect gait speed or fatigue by improving the load placed on crutches. The FB is perceived by users as helpful, safe, and easy to learn, and does not interfere with attention or concentration while walking. Furthermore, the PhTs consider the system to be useful, easy to learn and reliable.

Since cobots are designed to be flexible, they are frequently repositioned to change the production line according to the needs; hence, their working area (user frame) needs to be often calibrated. Therefore, it is important to adopt a fast and intuitive user frame calibration method that allows even non-expert users to perform the procedure effectively, reducing the possible mistakes that may arise in such contexts. The aim of this work was to quantitatively assess the performance of different user frame calibration procedures in terms of accuracy, complexity, and calibration time, to allow a reliable choice of which calibration method to adopt and the number of calibration points to use, given the requirements of the specific application. This has been done by first analyzing the performances of a Rethink Robotics Sawyer robot built-in user frame calibration method (Robot Positioning System, RPS) based on the analysis of a fiducial marker distortion obtained from the image acquired by the wrist camera. This resulted in a quantitative analysis of the limitations of this approach that only computes local calibration planes, highlighting the reduction of performances observed. Hence, the analysis focused on the comparison between two traditional calibration methods involving rigid markers to determine the best number of calibration points to adopt to achieve good repeatability performances. The analysis shows that, among the three methods, the RPS one resulted in very poor repeatability performances (1.42 mm), while the three and five points calibration methods achieve lower values (0.33 mm and 0.12 mm, respectively) which are closer to the reference repeatability (0.08 mm). Moreover, comparing the overall calibration times achieved by the three methods, it is shown that, incrementing the number of calibration points to more than five, it is not suggested since it could lead to a plateau in the performances, while increasing the overall calibration time.

No abstract