Home-Based Hormone Diagnostics
Hormonal health remains one of the most underexplored areas of medicine, particularly in women’s health. The project develops a new, affordable, home-based system that measures hormones in urine in a simple and non-invasive way, empowering women to track their health. It uses fiber optics, spectroscopy, and AI to analyze hormones such as LH, FSH, estrogen, progesterone, cortisol, and serotonin in real time.
Background
Hormones regulate everything from metabolism and reproduction to mood, cognition, and sleep. Yet hormonal health remains one of the least understood areas of medicine. Diagnostics have often been based on male physiology, leaving major knowledge gaps about women’s health.
Current blood tests are accurate but invasive, costly, and provide only a snapshot, failing to capture the true dynamics of hormone levels throughout the day or across different life stages. This makes early detection of conditions such as PCOS, endometriosis, and primary ovarian insufficiency difficult and contributes to persistent gender gaps in healthcare and biomedical data.
Project goals / research focus
The project is developing a new, affordable, home-based system to measure hormones in urine in a simple and non-invasive way. Using fiber optics, spectroscopy, and AI, the system can analyze LH, FSH, estrogen, progesterone, cortisol, and serotonin in real time, enabling continuous monitoring and improved diagnosis of PCOS and endometriosis.
The fiber-optic platform combines a compact light source, sensor module, and sampling kit with AI-based analysis for real-time readouts. The system allows women to understand their hormone balance, track cycle-related changes, and detect deviations linked to stress, metabolic, or endocrine disorders. Anonymized data can be uploaded to a secure database, creating unique longitudinal datasets for research on the interplay between hormones, health, and well-being. The platform is also generalizable for other hormones and biomarkers, offering broader biomedical and societal impact—from women’s health across all life stages to monitoring chronic diseases.
Advancing gender equality
The project uses AI to bridge the gender gap in medical diagnostics, strengthen women’s health and autonomy, and improve the diagnosis of conditions such as PCOS and endometriosis. By replacing invasive, one-off tests with an affordable, recyclable hormone-monitoring solution, it provides continuous, data-driven personal hormone insights, promotes gender-equitable healthcare, and empowers women to track changes in their health and identify hormone-related illnesses and dysfunctions.
Researchers
The project builds on an innovative collaboration between different research areas, combining optical engineering and bioanalytical chemistry.
The project is led by Carlota Canolis (Professor, Department of Applied Physics, SCI), Michel Fokine (Professor, Department of Applied Physics, SCI), and Cecilia Williams (Professor, Department of Protein Research, CBH).
