AI-Enabled Wearable Patches Reveal Undetected Hormone Disruption in Infertility

Unexplained infertility, diagnosed when routine evaluations identify no clear cause, affects 15–30% of couples and often leaves patients with limited options. Standard testing typically captures hormone levels at single time points, even though reproductive hormones fluctuate throughout the day and across the menstrual cycle. As a result, clinically relevant disruptions in hormone timing may go undetected. To address this gap, researchers have developed AI-enabled wearable patches and rhythm analytics that continuously track endocrine patterns.

Investigators from Oxford University and New Anglia University created an AI-enabled wearable skin sensor patch and an analysis metric called Endocrine Rhythm Integrity (ERI). The patch captures reproductive hormone signals repeatedly over several days. ERI evaluates whether hormones change with correct timing and coordination rather than as isolated values.

In a study of 102 men aged 22–38 in Georgia and the United States with normal morning total testosterone (12–35 nmol/L), levels were recorded every 15 minutes for four days. Symptomatic participants showed significantly disrupted testosterone rhythms despite normal laboratory values, which correlated with reduced sperm concentration and symptoms of androgen deficiency. 

A second study of 312 women aged 18–22 with regular cycles found that lower ERI scores predicted unexplained infertility and were associated with higher implantation failure. Results were presented at the 28th European Congress of Endocrinology in Prague.

“Our AI-driven rhythm analyses were significantly better at identifying subclinical reproductive dysfunction than conventional testing, suggesting that both female and male endocrine disorders may not simply be disorders of hormone quantity, but rather disorders of hormonal timing, synchronization and biological rhythm,” said Dr. Tinatin Kutchukhidze of Oxford University and New Anglia University.

"We aim to move fertility care toward predictive, rhythm-based reproductive medicine, where clinicians can identify dysfunction earlier, personalize interventions and improve outcomes before infertility becomes clinically evident," said Dr. Kutchukhidze.

Related Links
European Society of Endocrinology
Oxford University
New Anglia University