BE Seminars

The Kuranos Project; Monitoring and Analysis of Parkinson's Disease Motor Symptoms Using Wearables - a KT-MA Project

by Dr Lars Varming Joergensen (CERN)

6/2-024 - BE Auditorium Meyrin (CERN)

6/2-024 - BE Auditorium Meyrin


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"Parkinson's Disease (PD) is the second most widespread neuro-degenerative disease with about one million patients in the US and about one and a half million in the EU. The worldwide number of patients is believed to be in the range of five to ten million. The disease mainly affects older people with about 1% of the population above the age of 65 having the disease. There is at present no cure. Thus the medicine available only treats the symptoms. The cause of the disease is thought to be a lack of dopamine in parts of the brain responsible for e.g. muscle control.

Most of the most common symptoms for Parkinson's are motor symptoms with the most well known and recognized being tremors and others being bradykinesia (slowness of movements), diskinesia (sudden uncontrolled movements), rigidity, postural instability, balance and a general reduction of the size of movements  such as e.g. much reduced swinging of the arms while walking. There are also a few non-motor symptoms, most notably constipation and sleeping problems.

However, with such a preponderance of motor symptoms, the majority of which, in our view, ought to be relatively easily measurable and trackable over time. Much to our surprise, there were no devices available on the market to do this. This realization lead to the start of the Kuranos project. The original idea was to build our own devices. However, new models of smart watches hitting the market recently increasingly appeared to have a sensor packages and a battery capacity ever closer to what we would need.

Our idea is now to design a software application running on Apple Watch, FitBit and Garmin collecting as much data on PD as possible. The data would be recorded to two different databases; one for the use by the patient him- or herself together with the attending neurologist, where they can use it to better understand the efficacy of the medication regime the patient is currently on as well as perhaps the progression of the illnessprogression of the disease.

The data would also be submitted in properly anonymized form to a second database where tools from Big Data could be deployed to try to gain new information about details of PD that would only be possible to extract with data from thousands of patients. It is difficult to over-estimate the impact this could have. One could imagine medication taking different times to kick in for different groups of patients. This could then be investigated in terms of the genome.

This analysis of very large dataset is a unique CERN strength and has the potential to uncover a range of new sides to the disease and perhaps even help in the quest to find a cure.

The speaker was diagnosed with Parkinson's Disease in the summer of 2016."

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