Parkinson’s is neurodegenerative brain disease that affects almost 5 million people worldwide, and is second only to Alzheimer’s in global prevalence. Researchers have studied the causes, analysed the symptoms and have refined advanced genomics and proteomics techniques to create increasingly sophisticated cellular profiles of Parkinson’s disease pathology — all to little avail. Part of the problem, some have argued, is that the methodologies used to study the disease have barely changed since it was first described by Dr. James Parkinson in 1817.

However, The Michael J. Fox Foundation for Parkinson’s Research (MJFF) and Intel Corporation announced earlier today a collaboration to detect patterns in the progression of the disease by analysing the data collected from wearable technologies — essentially, monitoring devices that can track a patient’s symptoms throughout the day.

The devices are capable of tracking a whole range of symptoms, such as gait, hand tremors, and sleep patterns. Unlike the traditional method that encourages patients to manually log their symptoms — requiring an incredible amount of time and effort — the wearable technologies can collect 300 observations a second.

With this data, the team at Intel use their expertise to create algorithms that effectively analyze these datasets and identify important patterns. Having these algorithms at their disposal, medical researchers at the Michael J. Fox Foundation can then choose which algorithms to apply to a particular patient’s compilation of data — thereby tailoring the technology to individual cases, and exercising their medical expertise to extract meaningful information.

As the company describe:

“To analyze the volume of data, Intel developed a big data analytics platform that integrates a number of software components including Cloudera CDH* — an open-source software platform that collects, stores, and manages data. The data platform is deployed on a cloud infrastructure optimized on Intel(R) architecture, allowing scientists to focus on research rather than the underlying computing technologies. The platform supports an analytics application developed by Intel to process and detect changes in the data in real time. By detecting anomalies and changes in sensor and other data, the platform can provide researchers with a way to measure the progression of the disease objectively.”

The hope is that such a platform will soon be able to store other types of data — such as patient, genome, and clinical trial data — as well as incorporate more advanced technologies, like machine learning and graph analytics. As Todd Sherer, PhD, CEO of The Michael J. Fox Foundation emphasizes, the potential for these technologies to revolutionize current approaches to Parkinson’s is staggering:

“Nearly 200 years after Parkinson’s disease was first described by Dr. James Parkinson in 1817, we are still subjectively measuring Parkinson’s disease largely the same way doctors did then…Data science and wearable computing hold the potential to transform our ability to capture and objectively measure patients’ actual experience of disease, with unprecedented implications for Parkinson’s drug development, diagnosis and treatment.”

Currently, the project has been tested on a trial group of 25 participants, and is being prepared for mass use. A smartphone app, with which patients can add notes to their records, is also in the process of development.

Read the press release here

(Image Credit: A Health Blog)

Previous post

Data Scientists and Chief Data Officers - Fact or Fad?

Next post

Big Data, Small Budgets- Data Science on the US Election Campaign Trail