Objective In recent years, various devices for monitoring lower limb movement have emerged. Electrical sensors are susceptible to electromagnetic interference, while visual signals are affected by light intensity. Fiber Bragg Grating (FBG) sensors, on the other hand, have been widely adopted due to their excellent linearity, high sensitivity, flexibility, and strong anti-interference characteristics. During lower limb movement, the forces on the toes and heels of the foot continuously change, and the forces on the calf and thigh also fluctuate. However, research on the integrated monitoring of foot, calf, and thigh movements remains limited. Therefore, the development of a lower limb exoskeleton monitoring device is significant.

Methods This study first established a theoretical model based on kinematics and verified its feasibility through theoretical analysis and simulation. Subsequently, a lower limb exoskeleton and its monitoring sensor unit were designed. Calibration experiments were conducted on the lower limb sensor unit using a tensile testing machine. The force sensitivities of all sensing units were obtained above 9.9 pm/N, and the goodness of fit values were all above 0.9906, demonstrating that the sensing units possess excellent monitoring performance. The exoskeleton provides support for the wearer, and the sensor unit integrated within it successfully monitors lower limb movements. After the volunteer wore the exoskeleton, motion monitoring experiments were conducted. The resulting data showed periodic changes, consistent with the conclusions drawn from the theoretical model and simulation analysis. The device features a simple power system that provides a certain level of assistance. Furthermore, the system includes an upper-level computer to analyze the monitored data and provide warning feedback based on the movement state.

Results and Discussions In the theoretical model, as the angles of the three segments of the lower limb increase, the wavelength of the corresponding sensor units either increases or decreases. The relationship between step length and step height in the simulation analysis aligns with theoretical predictions. Additionally, dynamic analysis of the simplified structure further verified the accuracy of the step length-step height relationship. Finally, experimental data from the volunteer wearing the exoskeleton exhibited periodic changes, with stable mean values and standard deviations for the lower limb regions. The error between the theoretical and actual step length-step height was approximately 10%. The average value of the lower limb gait rhythm index (J) was 0.9379. These results confirm that the lower limb exoskeleton monitoring device meets monitoring requirements without negatively impacting the monitoring process and can accurately track the volunteer's lower limb movements. From a technical perspective, this study has made significant progress in sensing unit design and system integration. The advantages of FBG sensors lie not only in their high sensitivity and anti-interference capability but also in their suitability for multi-point synchronous monitoring due to their distributable embeddability and wavelength-encoding characteristics. In this system, by arranging sensing units at corresponding positions on the sole, ankle joint, knee joint, and thigh, a monitoring network covering key lower limb movement nodes was constructed. This distributed layout can capture the biomechanical changes during various phases of the gait cycle, providing multidimensional data for gait analysis and motor dysfunction assessment. In terms of system integration, the exoskeleton structure not only serves as a carrier for the sensing units but its mechanical design also fully considers ergonomics and movement adaptability. Lightweight hinge structures are used at the joints to reduce movement constraints while ensuring support stiffness. The power system employs lightweight electric actuators that primarily provide assistive torque during the gait propulsion phase, reducing the wearer's walking energy expenditure. When gait abnormalities (such as foot dragging or excessively high left-right asymmetry) or sudden force changes are detected, the system can provide alerts through sound or interface flashes, possessing preliminary gait anomaly warning capabilities.

Conclusions Looking at the application prospects, this FBG-based lower limb exoskeleton monitoring device holds potential not only for motion analysis or assistance in healthy populations but also, and more importantly, in the field of rehabilitation medicine. It can provide objective and continuous gait parameter monitoring for patients after lower limb surgery or those with post-stroke sequelae, helping rehabilitation therapists quantitatively assess recovery progress. Furthermore, it could potentially integrate with functional electrical stimulation or robotic-assisted training to form an intelligent rehabilitation training system. Additionally, in specialized operational fields (such as firefighting or loaded marching), this technology could be used to monitor operators' fatigue states and prevent sports injuries. In summary, this study successfully designed and validated a lower limb exoskeleton monitoring device integrated with FBG sensing technology. The device achieves synchronous, anti-interference monitoring of multi-part lower limb movements with reliable data, while the exoskeleton structure provides a certain level of assistance during monitoring. The experimental results confirm their effectiveness, laying a solid foundation for subsequent research. Future work will focus on algorithm optimization, system lightweighting and portability, as well as clinical validation and functional expansion for specific application scenarios, aiming to ultimately transition the device from a laboratory prototype to a practical product.