Towards a personalised approach in monitoring people with Parkinson's disease

A wearable device tracks every step, stumble, and shuffle of a person with Parkinson’s disease, feeding the data into a computer that spots patterns invisible to the human eye. Doctors currently assess Parkinson’s progression using brief clinic visits and subjective rating scales. These snapshots miss day-to-day fluctuations in mobility and fail to distinguish between different subtypes of the disease. The project combines digital mobility outcomes from wrist-worn sensors with clinical scores and a brain-imaging technique called phosphorus magnetic resonance spectroscopy (31P-MRS), which measures energy metabolism in cells. Together, these data could reveal which patients are likely to decline rapidly and which might respond better to specific treatments. If the approach works, neurologists could shift from one-size-fits-all care to personalised treatment plans based on real-world movement data. Patients might receive therapies earlier, when they are most effective, and avoid drugs that will not help their particular disease subtype. The research also lays groundwork for remote monitoring systems that could reduce the need for frequent hospital visits—a practical benefit for people with limited mobility or who live far from specialist centres.