Parkinson's breakthrough: Home monitor could give better targeted help

It has new software which can detect a side-effect of treatment that causes involuntary jerking movements, it was revealed last night.

Prolonged exposure to the dopamine replacement drugs used to treat Parkinson’s can lead to dyskinesia – involuntary jerking and spasms of the body.

Researchers at Heriot-Watt University in Edinburgh said the software reliably detects the condition.

They are now using their findings to develop a home monitor that will help clinicians adapt and improve treatment.

Dr Michael Lones, associate professor of computer science at Heriot-Watt, said: “The problem is that, as Parkinson’s disease worsens over time, the dose required to treat the motor features increases.

“That increases the risk of inducing dyskinesia or making it more severe and prolonged for patients.

“Patients don’t see their clinicians that frequently and medication only changes at regular review periods.

“So it is very difficult for clinicians to know when dyskinesia is occurring. “A better solution would be a portable device that identifies and monitors dyskinesia while patients are at home and going about day-to-day life, broadcasting data to their clinicians through mobile technology.”

The motor features of Parkinson’s, such as tremor and postural instability, are caused by a lack of the chemical dopamine. About 90 per cent of patients treated with dopamine replacement drugs over 10 years reported dyskinesia symptoms.

Dr Lones and his team carried out two clinical studies with 23 patients who had all displayed evidence of dyskinesia.

“The clinical studies allowed us to capture and mine data about how patients move and used those to build models,” Dr Lones said.

“We developed our algorithm to make as few assumptions as possible. With traditional analysis, you make assumptions about what a movement looks like. If it doesn’t look like exactly that, you won’t detect it.

“The algorithm works by building a mathematical equation that describes patterns of acceleration which are characteristic of dyskinesia.

“The system then uses this equation to discriminate periods of dyskinesia from other movements, relaying this information to clinicians.”

They can then “adapt a patient’s medication as necessary and more effectively manage the side-effects, which currently reduce the quality of life for a great number of patients”.

The research was done in collaboration with York University and Leeds Teaching Hospitals NHS Trust.