Bioprinting for Tissue Engineering

DermoDose

Dermodose goes in the direction of destroying the communication barriers between doctors and patients with different backgrounds and knowledge.
According to recent studies, 20 to 25% of the global population is affected by skin diseases, making them the 8th leading cause of non-fatal burden worldwide. The most common skin diseases are fungal and bacterial infections, scabies and dermatitis: all of them require medical treatment to be cured.
With Dermodose we have created a simple app to help dermatologists calculating the amount of medication needed, strongly reducing the risk of both overexposure and underexposure. Using DermoDose is simple, straightforward and ensure that every pathology is treated in the most efficient way possible.
First you create an account and provide personal informations as height, gender, age, and weight.
Then you take a picture of the affected area, the infection gets segmentated, and all the inputs are used to determine the amount of dosage needed.
Once you have calcualated the dosage you can directly measure it and apply it on the skin using DermoDose applicator, a precise and intuitive tool that comes with the app.
The app also allows the patient, together with the dermatologist, to track the progress of the infection and adjust the dosage accordingly.

• Python Scripts
• Project Presentation

Energy Efficient Analog Design on Cadence

This short series of design exercises provides a hands-on step by step guide to implement the different building blocks needed to develop a fully autonomous wearable device using Cadence.
Low noise differential amplifiers to ensure proper signal acquisition, DC-DC converter to provide the required power supply for the different modules used by the device with a fine level resolutions, an Phase Locked Loop circuits to generate precise timing signals and enable wireless real-time communication with external devices are implemented and discussed.

Anxiety Detection via heart beat variability

This project explores the use of signal processing and machine learning to detect anxiety by analyzing respiratory and ECG signals. It involves filtering biosignals, extracting heart rate variability features, and employing classifiers to distinguish between anxiety-inducing and non-anxiety-inducing states. Key techniques include Fourier transform, wavelet decomposition, and the comparison of LDA and neural network classifier performance.

• Matlab Scripts
• Project PDFs

Deterministic Chaos

I worked on this project for a whole year when I was in high school (this is why is in italian but feel free to reeach out to me to discuss more) and this project marked the beginning of my journey as an engineer. The goal of the project was to design and build experimental setups that could be used to study deterministic chaos.
In deterministic chaos, seemingly random behavior arises from simple, deterministic equations. Tiny differences in initial conditions lead to vastly different outcomes over time, making long-term prediction impossible. Two different experimental setups were chosen: Lorenz Mill and the three bodies problems. Data recordings and data analysis were performed for both experiments and Lorenz attractor was retrieved in both cases.
The attractor exhibits a complex, butterfly-like shape in three-dimensional phase space, indicating chaotic behavior where trajectories appear to orbit around two distinct wings or lobes without ever exactly repeating themselves.
This proved exactly what deterministic chaos is all about: tiny variations that in the experimental setup are out of our control are enough to completely change the trajectory of the system.

• Project PDFs

Muscle Health Monitoring

This project addresses the challenge of ineffective training often stemming from unbalanced exercise loads, leading to injuries or suboptimal results. We aim to develop a system for real-time monitoring of muscle health to guide users towards their optimal training intensity, thereby reducing injury risk and enhancing workout efficiency.
Our approach focuses on tracking two key biomarkers present in interstitial fluid (ISF): lactate and pH levels. ISF offers a non-invasive and accessible medium for monitoring, with lactate concentrations closely mirroring those in blood, making it ideal for wearable applications. While both lactate (increasing with work intensity) and pH (decreasing with output power) individually indicate muscle fatigue, their combined analysis allows us to account for complex biological pathways and achieve greater accuracy in assessing muscle state.
For effective pH sensing, we identified the critical requirement for the sensor's linear range to align with the physiological pH range of ISF (6 to 8). Based on observed variations during exercise, the sensor necessitates optimal sensitivity around 59 mV/pH unit and high stability, with deviations maintained below 1% over a 24-hour operational lifespan to ensure consistent and precise readings.
In the case of lactate sensing, while blood lactate levels during exercise can range from 0 to 10 mM, our application focuses on tracking the anaerobic threshold. This allows for a less stringent sensitivity requirement, aligning with average state-of-the-art performance around 50 µA/mM/cm². Crucially, the limit of detection (LOD) must be below 10 µM to ensure sensitivity to low lactate concentrations and minimize the impact of noise on measurement accuracy. Furthermore, the sensor's stability should maintain deviations below 5% for reliable performance. The operational lifetime for both sensors is designed to accommodate extended training sessions.
Leveraging existing advancements in biosensing technologies, we explored the state-of-the-art in lactate and pH detection. Microneedle arrays and single-needle approaches have demonstrated efficiency for non-invasive and precise lactate monitoring in ISF, showing strong compatibility with wearable form factors for real-time exercise tracking. While current market solutions like IDRO utilize sweat for lactate monitoring, ISF presents a more direct and potentially reliable medium for our application. Similarly, potentiometric pH sensing has shown significant promise in sweat analysis. Building upon these foundations, our project proposes the adaptation and integration of these sensing methodologies for simultaneous and continuous monitoring of lactate and pH levels in ISF, paving the way for personalized and optimized training regimens.

• Project Presentation

Human Nature Interactions

This paper explores the multifaceted role of insects in human history, tracing their cultural, symbolic, and culinary significance from antiquity to the present day. Once revered as sacred symbols and consumed as delicacies in ancient civilizations, insects gradually became stigmatized in Western societies, particularly during the Middle Ages, where they came to embody decay and disease. Through literature, religious texts, and visual art, the study examines the evolving perception of insects and their reemergence in modern discourse as sustainable food sources. By comparing historical acceptance with contemporary attitudes and global practices, the paper advocates for a gradual reintegration of insects into Western diets, emphasizing cultural sensitivity and sustainability. This interdisciplinary investigation highlights insects not only as nutritional assets but also as enduring symbols reflecting humanity’s shifting relationship with nature.

• Project PDFs