The University of Melbourne

Rhythms in Physiology Lab

We're unravelling the mechanisms of multiday cycles in the brain, heart and body, to inform personalised disease management and optimise health.

Our Research Meet the Team

About RiPL

Beating to a different rhythm

Our groundbreaking research found multiday cycles (weekly, monthly, seasonal and other periods) are common in people with epilepsy, leading to breakthrough technology for tracking individual seizure risk. But multiday rhythms are more widespread than that, affecting other systems too, like the heart.

RiPL integrates multimodal, multiscale data (implanted, wearable and mobile devices, physiological and genetic sampling) to understand why multiday rhythms modulate diverse biological systems and drive increased risk of disease symptoms. As part of the Graeme Clark Institute's digital health theme, we bring together researchers in engineering, neuroscience, bioinformatics, in partnership with hospitals and industry, to revolutionise how we understand human physiology.

Research Themes

Where multiday cycles matter

By understanding the mechanisms behind physiological rhythms, we aim to empower patients and clinicians to optimise health by timing treatment to align with individual cycles.

Epilepsy

Tracking seizure cycles to improve monitoring and treatment of epilepsy.

Psychiatry

Identification of multiday rhythms and risk in psychiatric disorders.

Cognition

A public web app to identify, understand and forecast multiday rhythms and their effect on human function and performance.

Genetics

Identifying genetic markers underpinning multiday rhythms, in collaboration with the Bahlo Lab at WEHI.

Cardiology

Exploring multiday heart rate cycles and their link to cardiovascular disease symptoms.

Capabilities

What we bring to a collaboration

Strong capabilities in neural engineering, software development and circular statistics, with a focus on capturing rhythmic biomarkers from physiological data: brain activity, neuroimaging, autonomic signals and hormone samples.

Wearable software integration and signal analysis
Development of mobile & web apps for clinical applications
Circular statistics and data science for rhythmic time series
Neuroimaging (EEG, TMS)

Assessment of cognitive and behavioural functions
Longitudinal human studies and clinical trials
Bayesian statistical inference and forecasting (risk tracking) algorithms
Faraday-shielded room for neural recordings and high-performance computing

Impact

Research that reaches patients

World-first

Mobile app to track seizure risk, built with the international 'My Seizure Gauge' consortium.

Rhythmo

Public web app and Python package built on our discovery of multiday chronotypes.

Translation

2022 Prime Minister's Prize for New Innovators.