# Non-Invasive Glucose Measurement Technique Based on Time-of-Flight
## 5 Discussion and Future Work  
Based on the above results, the developed sensing method shows promise in the measurement of glucose in aqueous solutions, based on the change in the optical properties. The developed sensor allowed for the detection of glucose changes based on the change in the Time-of-Flight of light through a sample using relatively inexpensive, off-the-shelf components. The results of the sensor show a correlation between the measured value and the sample glucose concentration. The error margins are relatively high, but it should be possible to improve these with further fine tuning of the different sensor variables and circuit design. The authors consider the developed sensor to be at TRL3--the sensor demonstrates basic functionality under in a research environment; however, further work is needed. Future work on this TRL3 sensor should begin with an experimental design, integrating both in vitro and in vivo testing stages alongside direct comparisons to benchmark equipment. To this end, experiments will be structured to include baseline readings, dynamic environmental exposures, and testing in the presence of potential interferers. The sensor could be tested on a lipid emulsion to simulate skin optical properties (as has been tried by [PERSON] et al. with good results [18]). The sensing element used has multiple parameters that should be further adjusted to improve the sensor response--initial values based on datasheet recommendations were used in this work. These parameters could also affect the sensor response in different environments. After reaching a well defined state for the sensor parameters, experimentation should be expanded to include live biological specimens or human subjects (where applicable) to finally observe the sensor's behavior in a biological matrix and revealing any potential effects by other biological materials, response time variations, and other sensor-material interactions. Initial work has already been conducted to verify that the LED wavelength and light emitted are sufficient to achieve an acceptable penetration depth (using data and skin models from [PERSON] et al. and [PERSON] et al. [19; 20]). An additional experimental modification is the wavelenght used. Further work should increase the spectrum of wavelengths used--there have been promising results from using wavelengths in the NIR region between 1200 nm up to 2500 nm [21]. To address this, revised  
Figure 12: Averaged sensor output (phase channel scaled by amplitude channel) for different glucose concentrations. versions of the sensor presented here are currently being designed that will operate in this region. Such sensors will probably have a decreased area of measurement, but will be based on the same principle. The authors are currently in the process of evaluating these updated sensing elements and optimizing the accompanying circuit design to enhance the sensor's stability and sensitivity. However, LEDs of sufficiently high speed and photodiodes of a likewise high sensitivity able to operate in these wavelengths are prohibitively expensive when compared with devices tuned for wavelengths less than 1000 nm. Thus, while such a research direction could prove beneficial regarding the sensor operation, it should be heavily weighted with the current implementation, which is very low cost--with a complete sensor package costing about 100 EUR at the time of writing. On the processing side, future work should focus on refining the quality of image-based data by employing advanced noise reduction algorithms. Adding to that, it is also important that the data processing workflow is further expanded and optimized or even improved upon. The moving average algorithm currently used, while effective in certain scenarios, has limitations and may not fully optimize noise reduction while preserving essential information.