This paper presents the development of temperature sensors based on fiber Bragg gratings (FBGs) embedded in 3D-printed structures made of different materials, namely polylatic acid (PLA) and thermoplastic polyurethane (TPU). A numerical analysis of the material behavior and its interaction with the FBG sensor was performed through the finite element method. A simple, fast and prone to automation process is presented for the FBG embedment in both PLA and TPU structures. The temperature tests were made using both PLA- and TPU-embedded FBGs as well as an unembedded FBG as reference. Results show an outstanding temperature sensitivity of 139 pm/°C for the FBG-embedded PLA structure, which is one of the highest temperature sensitivities reported for FBG-based temperature sensors in silica fibers. The sensor also shows almost negligible hysteresis (highest hysteresis below 0.5%). In addition, both PLA- and TPU-embedded structures present high linearity and response time below 2 s. The results presented in this work not only demonstrate the feasibility of developing fully embedded temperature sensors with high resolution and in compliance with soft robot application requirements, but also show that the FBG embedment in such structures is capable of enhancing the sensor performance.

We report the application of fiber Bragg grating (FBG) arrays in polymer optical fibers for the quasi-distributed displacement and torque sensing in a series elastic actuator's spring. The arrays were inscribed in cyclic transparent optical polymer fiber through the direct-write, plane-by-plane inscription method using a femtosecond laser. Two arrays with four FBGs each were positioned on a rotary spring, and a numerical analysis using the finite-element method was performed to evaluate the sensors' behavior under different loading conditions. Experimental tests were performed on the spring, and the results show that the FBGs responses follow the predicted numerical simulations. In addition, a Kalman filter was applied on the response of the FBGs for sensor fusion, leading to a more accurate torque estimation, where the relative error for the torque estimation was improved by a factor of 7. Furthermore, transverse forces were applied on the predefined points of the spring in order to show the ability of the quasi-distributed sensor approach to identify external mechanical disturbances on the spring.

Currently, Social Assistive Robotics (SAR) is widely explored in different areas and scenarios. In cardiac rehabilitation, SAR has been recently implemented as a tool to improve the quality of the procedures and support patients to boost their performance. As cardiac rehabilitation comprises numerous sessions, such systems must guarantee to be effective in the long term. Therefore, to achieve this goal, it is important to understand how users, namely patients and clinicians who mostly know the needs and the therapy environment, perceive this technology. In this context, this paper presents the assessment of the attitudes towards a social robot in order to evaluate the expectation of potential new users, and perception of users who interacted with the social robot during a period of 18 weeks performing cardiac rehabilitation. A total of 43 participants (28 patients and 15 clinicians) were included in the study, and acceptance and perception factors were evaluated through a modified UTAUT questionnaire model and open discussion sessions. Results show that 75% of patients have positive thoughts regarding the usefulness, utility, safety, and trust perceived of a social robot, and 80% of clinicians consider that the robot is a useful tool for cardiac rehabilitation. Similarly, a more positive perception was noticed after the users interacted with the robot. Furthermore, this perception study allows the enhancement of the social model of interaction in the future, aiming to provide a more natural interaction trough personalized features, increasing social abilities and engagement of the users during the therapy.

Cardiovascular disease is the leading cause of death in the world. A program of cardiac rehabilitation (CR) is related to physical activities or exercises to regain the optimal quality of life. CR relies on the necessity to evaluate, control and supervise a patient's status and progress. This work has two objectives: on the one hand, provide a tool for clinicians to assess the patient's status during CR. On the other hand, there is evidence that robots can motivate patients during therapeutic procedures. Our sensor interface explores the possibility to integrate a robotic agent into cardiac therapy. This work presents an exploratory experiment for on-line assessment of typical CR routines.

This paper presents the development and validation of a polymer optical-fiber strain-gauge sensor based on the light-coupling principle to measure axial deformation of elastic tendons incorporated in soft actuators for wearable assistive robots. An analytical model was proposed and further validated with experiment tests, showing correlation with a coefficient of R = 0.998 between experiment and theoretical data, and reaching a maximum axial displacement range of 15 mm and no significant hysteresis. Furthermore, experiment tests were carried out attaching the validated sensor to the elastic tendon. Results of three experiment tests show the sensor’s capability to measure the tendon’s response under tensile axial stress, finding 20.45% of hysteresis in the material’s response between the stretching and recovery phase. Based on these results, there is evidence of the potential that the fiber-optical strain sensor presents for future applications in the characterization of such tendons and identification of dynamic models that allow the understanding of the material’s response to the development of more efficient interaction-control strategies.