## 4 Results and Discussion
### Translational Value  
Inspired by the current methodology, our wearable prototype blood glucose monitor is covered by our invention patent (CN 202510450345), which consists of a circular monolithic integrated structure with tunable NIR LEDs, centrally located photodiodes, and electronic modules (e.g., Bluetooth). This prototype is compatible with mature, low-cost elements that can be built for practical applications. However, the system may face critical challenges due to the significant noise introduced by these cost-effective components, which could be calibrated through optimization algorithms. The power consumption of our wearable prototype is worthy of discussion. Tunable NIR LEDs, photodiodes, and wireless modules (e.g., Bluetooth) constitute the major power consumption sources in wearable systems of this nature. Typically, the power cost of NIR LEDs ranges from 50 to 100 mW, photodiodes consume 5-10 mW, and Bluetooth Low Energy (BLE) modules require 5-15 mW during active transmission. With optimized power management, the entire system can be supported by a 300-500 mAh lithium polymer battery, which is compatible with commercial portable blood glucose monitors like Freestyle Libre (Abbott) and Guardian Connect (Medtronic). In addition, our system is compatible with major market platforms (e.g., Apple Health, Google Fit), enabling remote parameter adjustment and demonstrating potential for telemedicine and IoT-based glucose monitoring. As our experiments were conducted in China, localization requirements are currently a priority for National Medical Products Administration (NMPA) approval. Furthermore, the system consists of mature optical/electrical components that can be easily obtained through mass production.  
Therefore, the translational value of the current methodology can be summarized as follows: (1) Non-invasive real-time glucose monitoring: Our method leverages the distinct absorption properties of human tissue and blood glucose, where low-absorption regions (850 nm and 940 nm channels) serve as reference signals for mitigating background noise, while glucose absorption bands (1300 nm, 1400 nm, 1550 nm, and 1650 nm) provide target-specific information. By systematically integrating multilevel metric learning with a BP network, our method achieves high accuracy while maintaining physical interpretability. Taking advantage of a hierarchical design guided by physical properties, our approach requires fewer computational resources and offers a novel pathway for real-time glucose monitoring. (2) Cost-effectiveness: Long-term cost is one of the most critical considerations for daily blood glucose sensing in humans. Current CGM systems, which involve inserting electrodes under the skin for 7-14 days, can cause physical discomfort and impose financial burden on users. In contrast, our system eliminates the recurring expenses associated with sensor replacements, offering a more affordable and patient-friendly solution. (3) Future applications: By expanding the method to other spectral information, biomarkers such as blood oxygen could also be detected. This versatility aligns with the development of advanced portable wearables and IoT-enabled devices, demonstrating promising potential for remote smart healthcare applications.