New research from scientists at the State University of São Paulo, Brazil, highlights the value of gait measurement in identifying Parkinson’s and shows how new technologies can help diagnose the condition.
Could a machine learning algorithm that measures step help detect parkinson’s progression? The answer, according to a team of researchers in Brazil, it could be so.
Parkinson’s can be difficult to diagnose, particularly in the early stages, because there are no specific test for the condition. Now, scientists from the State University of São Paulo (UNESP) turned to artificial intelligence to address this problem. The findings of his study were published in the journal Gait and Posture.
Measurement of Parkinson’s progression
Study participants included 63 people living with Parkinson’s and an equal number control group. Everyone in the study was over 50 years old.
As an initial step, the researchers established four gait-related characteristics that are key to identifying Parkinson’s: step length, speed, step width and gait consistency.
“We choose step parameters as the key criteria because gait disturbances appear early in Parkinson’s disease and worsen over time.” commented Fabio Augusto Barbieri, professor at UNESP and co-author of the study, “and also because they do not correlate with physiological parameters such as age, height and weight.”
The team also created two machine learning models: one to identify the severity of the condition and another designed to help diagnose it. A special motion capture camera was then used to measure the gait of each study participant. These measures were analyzed and compared between the two groups.
According to the researchers, the models were found to identify the condition with an accuracy rate of approximately 84.6%. So what could that mean for people with Parkinson’s?
“We could significantly reduce the probability of diagnostic error by combining clinical assessment with artificial intelligence,” Barbieri said.
For more information on the latest parkinson’s researchvisit the Parkinson’s Europe website.
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