Our groundbreaking research found multiday cycles (such as weekly, monthly, seasonal and other multiday periods) were common for people with epilepsy, leading to breakthrough technology to track individual seizure risk. However, multiday rhythms are more widespread, affecting other systems, 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.
Our disease hubs research how multiday cycles may impact neurological, neurodegenerative and psychiatric disorders and cardiovascular diseases. By understanding mechanisms of physiological rhythms, we aim to empower patients and their clinicians to optimise their health by proactively timing treatment to align with their inherent cycles.
Our research program brings together leading researchers in engineering, neuroscience, bioinformatics and other disciplines at The University of Melbourne in partnership with hospitals and industry to revolutionise understanding of human physiology. We are building digital health tools to enable therapeutic strategies that precisely target individual risk patterns and address diseases that may be modulated by multiday rhythms. As case examples, the program focusses on the following areas:
- Epilepsy: Tracking seizure cycles to improve monitoring and treatment of epilepsy;
- Psychiatry: Identification of multiday rhythms and risk in psychiatric disorders;
- Cognition: A publicly accessible web app to identify, understand, and forecast multiday rhythms and study their effects on human function and performance;
- Genetics: Identifying genetic markers underpinning multiday rhythms (a collaboration with Bahlo Lab, the Walter & Eliza Hall Institute);
- Cardiology: Exploration of multiday heart rate cycles and cardiovascular disease symptoms.
Capabilities
The team has capabilities in neural engineering, software development, and circular statistics with a strong focus on capturing rhythmic biomarkers from physiological data, including brain activity, neuroimaging, autonomic signals (i.e., heart rate, skin conductance), and hormone samples. Our approach to tracking multiday rhythms is applicable to general populations and for modelling of episodic disease symptoms (i.e., seizures, arrhythmias, depression)
Key capabilities:
- 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 development of forecasting (risk tracking) algorithms
Impact
- World-first mobile app to track seizure risk with international ‘My Seizure Gauge’ consortium
- Discovery of multiday chronotypes and launch of web app (rhythmo.me)
- Prime Ministers Prize for New Innovators (2022)
Facilities
- Software (mobile/wearable/web) and high-performance computing
- Faraday shielded room for neural recordings
- Extensive facilities for testing human physiology
More information:
Program Leader
karolyp@unimelb.edu.au