## 1 Introduction
The accurate measurement and characterization of limb kinematics are crucial in diagnosing and treating physical and mental disorders resulting from trauma, stroke, or disease [31]. Developing reliable and precise methods to assess limb movement is essential for both clinical and research purposes. Accurate kinematic data provide valuable insights into the pathophysiology of disorders and support clinicians in determining the most effective treatments and therapies for their patients. Therefore, advanced techniques and technologies for kinematic analysis should be prioritized in the medical field. This demand has led to the increasing adoption of smart, wearable devices that are easy to use, minimally invasive, and capable of operating in real-world environments without dependence on external infrastructure. The main contribution of this paper is the joint utilization of two wearable/attachable photonic and wireless systems with high resolution for characterizing the knee gait cycle. This approach allows for the construction of a chart representing wavelength variation versus angular variation, bridging the gap between photonic strain sensing and biomechanical motion estimation. The designed and fabricated system offers numerous advantages in biomedical fields, particularly in physical therapy and athletic assessment applications, due to its high resolution, wireless transmission capability, and ease of application to the targeted body region. It permits the precise measurement, recording, and evaluation of distinct mechanical parameters of limb motion. Primary end-user applications include patients with conditions affecting bones, muscles, and joints, as well as athletes. The system's capability to provide objective measurements of limb motion parameters supports effective diagnosis, therapy, and rehabilitation interventions. Despite advances, there is still a gap in the literature regarding the development of solutions that combine high-resolution photonic and wireless electronic sensors to characterize the knee gait cycle without using complex motion capture systems. While existing research has explored FBG systems and IMU platforms independently, few studies have successfully integrated them into a unified, low-complexity wearable solution validated on multiple subjects. This study aims to develop and validate an innovative system to measure knee-referenced gait cycles using photonic and wireless systems, providing a practical and high-resolution solution for medical and sports applications. The justification for this work lies in the need for more accessible, accurate, and user-friendly monitoring systems for diagnosing and tracking patients in physical therapy and athletic evaluations. The main highlights of this study include (i) an innovative combination of photonic sensors and wireless electronic modules for gait monitoring; (ii) a high resolution with sensors of 10 p.m. and an angular accuracy of 1\({}^{\circ}\); (iii) biomedical applications in physical therapy, rehabilitation, and athletic assessments; and (iv) system testing on individuals with different physical attributes, demonstrating consistency and versatility. The structure of this article is organized as follows: Section 2--Methods: Detailed description of the proposed system, including photonic and wireless components. Section 3--Measurements: Presentation of data obtained from experimental tests with seven volunteers. Section 4--Results and Discussion: Critical analysis of the results and a comparison with previous studies. Section 5--Conclusions: Summary of the main contributions and suggestions for future studies.