Week 11: Refine, Refine, Refine!

Hello and welcome back!! I can’t believe we’ve reached the end of my project, but I still have one (maybe two) more blog post to give. This week, I continued testing my hydration-monitoring prototype on my own skin to see whether the results I observed previously were actually reproducible. In earlier trials, I noticed that my humidity readings decreased when I became dehydrated and increased again after rehydrating. While this was exciting, I wanted to make sure it wasn’t just a one-time occurrence or caused by random environmental factors. To do this, I repeated the experiment multiple times over several days while keeping the setup as consistent as possible.

For each trial, I placed the sensors on my elbow, since research papers I previously reviewed suggested that the elbow region provides more stable hydration-related readings due to its skin properties. I measured both humidity and temperature over time while going through normal daily activities. In some trials, I intentionally waited longer before drinking water or exercised beforehand to encourage mild dehydration, while in others I tested after already being hydrated. Throughout the experiments, I recorded the sensor readings and compared how they changed over time.

One thing I noticed was that the overall trends were actually fairly consistent. When I was more hydrated, the skin surface humidity readings tended to stay higher and more stable. When I became dehydrated or exercised without immediately rehydrating, the humidity values gradually decreased and sometimes approached my lower threshold of 40%. After drinking water, the readings usually began to increase again. Even though the exact values varied slightly from day to day, the general pattern stayed similar across trials, which suggests that the device may actually be detecting meaningful hydration-related changes rather than random noise.

At the same time, I also observed how sensitive the readings were to external conditions. Things like room temperature, weather, movement, and even how tightly the sensor rested against my skin could slightly affect the values. This reinforced something I had already started realizing earlier in the project: hydration detection is probably not going to depend on one exact number alone. Instead, it makes more sense to focus on patterns and trends over time. For example, a gradual drop in humidity combined with increased skin temperature may be more useful than just checking whether one value crosses a threshold.

Another important takeaway from this week was that real skin behaves very differently from my gelatin hydrogel models. The gelatin changes slowly and predictably, while human skin is much more dynamic. Sweat production, movement, environmental exposure, and even small physiological changes can all influence the readings. However, this also makes self-testing much more valuable because it allows me to see how the device performs under real-world conditions instead of only controlled laboratory-like setups.

Since this is the second-to-last blog post of the project, I’ve also been reflecting on how much the project evolved from the original idea. Although I was able to create a working proof-of-concept prototype and observe hydration-related trends, the device still requires significant refinement before it could become a truly reliable hydration-monitoring system. Future work could include adding more advanced sensors, improving the calibration process for different users and environments, collecting larger datasets, and using machine learning to better identify dehydration patterns. The physical design of the patch could also be improved to make it smaller, more comfortable, and more wearable for long-term use. Additionally, testing with more people and under more controlled conditions would help validate the accuracy of the system.

While my final blog post will mainly be a reflection on the overall experience rather than introducing new advancements, this week’s testing helped solidify many of the conclusions I reached throughout the project. Overall, this experience taught me that engineering research is rarely a straight path. Many of my original ideas did not work the way I expected, but each obstacle ultimately helped me better understand both the technology and the problem I was trying to solve.