The global prevalence of stress and its far-reaching impact on well-being has spurred the pursuit of innovative solutions for physiological and stress monitoring. Existing methods, whereas informative, often lack cost-efficiency, daily usefulness, real-time capabilities, or user comfort. This study introduces a novel approach using a low-cost wearable polymeric optical fiber (POF) sensor to classify stress in 12 healthy individuals (seven women and five men) using the Trial Social Stress Test (TSST) method for stress induction. The study’s methodology involves validating the POF sensor’s physiological measurement, comparing it with a fiber Bragg Grating (FBG)-based sensor and with an electrocardiogram (ECG) commercial sensor, and subsequent making a stress classification approach using a Bagged Decision Tree Classifier (BDTC). To the authors’ knowledge, this is the first work implementing POF and FBG sensors in stress detection. The results showcase the POF sensor’s proficiency in capturing pulse and respiration signals, aligning closely with established monitoring sensors. The tested classification algorithm with the POF sensor exhibits an accuracy of 92.37% in the validation stage and 84.75%, recall of 79.41%, precision of 93.10%, and F-score of 85.71%. These results demonstrate the POF sensor’s potential to be a reliable stress indicator. Also, considering the reduction in the size of the optical interrogation system for the POF sensor compared to FBG interrogation systems, the proposed sensor can be used in complete wearable systems. For future work, the sensor will be improved in terms of TRL and tested in real-scenario applications.

Understanding the differences in ventilatory responses during exercise between patients with fibromyalgia and those with other chronic pain disorders is crucial for developing effective therapeutic interventions, especially in exercise to identify the better physical therapy prescription. Both populations face unique challenges that impact their ability to engage in physical activity; yet, the underlying physiological responses can vary significantly. In this context, the methodology of this study entailed conducting a comparative analysis of the ventilatory response during exercise in patients with fibromyalgia and those with other chronic pain disorders. The experimental protocol included a total of 31 participants (n = 13 diagnosed with fibromyalgia and n = 18 diagnosed with other chronic pain conditions). All participants completed a stress test, where the ventilatory parameters were measured in three stages (i.e., resting, incremental exercise, and recovery). The results revealed significant differences ($p<0.05$) in ventilatory responses between both groups. Patients with fibromyalgia exhibited reduced time for the aerobic threshold and a higher respiratory frequency in the anaerobic threshold compared to those with other chronic pain disorders. Furthermore, fibromyalgia patients demonstrated higher values in the ventilatory coefficient during the test and in the recovery stage. In conclusion, these differences underscore the need for tailored exercise programs that specifically address the unique ventilatory challenges faced by fibromyalgia patients to improve their physical function and overall quality of life.

Optical fiber sensors have been validated for physiological measurement as a potential device for smart textiles and wearable sensors. Also, developing sensors with Polymeric Optical Fiber (POF) shows promising applications in dynamic and real scenarios, as low-cost alternatives. Furthermore, the functioning of POF sensors can be used in no-skin contact applications, such as in highly skin-sensitive children with Autism Spectrum Disorder (ASD) during therapies. On the other hand, Dog-Assisted Therapy (DAT) is a stress-reducing method and has been studied to identify its influence on improving therapies and stress-related events. This work presents a case study in three weekly DAT sessions focused on speech therapy in a subject with ASD. A validated low-cost POF sensor was used in this first dynamic physiological measurement scenario. The analysis of five Heart Rate Variability (HRV) variables was made to compare the participant’s physiological status before and during the DAT. The obtained pulse signal showed the dynamic movements affecting the signal but being able to obtain the pulse peaks. The physiological comparison showed a difference in the mean peakto-peak time interval when the child was interacting with the dog than previous to the interaction in Session 1 and Session 2 (p-value<0.05). Also, an improvement in phonological consciousness was obtained, increasing by eight points after the three weeks of therapy. This case study showed the potential use of POF sensors in dynamic environments, and for wearable or smart textiles for children with ASD.