An algorithm combined with a sensor-based system can effectively detect ON and OFF state patterns in patients with Parkinson’s disease (PD), according to researchers from Florida Atlantic University’s (FAU) College of Engineering and Computer Science, published their study in Medical Engineering and Physics.
Often, the medication ON and OFF motor fluctuates in PD patients, a complication which arises in half of those diagnosed with PD within three to five years, and in 80% diagnosed within ten years. These fluctuations are an integral part of managing PD as they require continuous adjustments in treatment such as changing the frequency and dosage of medication or switching deep brain stimulation parameters. This new combined system is designed to detect ON and OFF state patterns in PD patients using two wearable motion sensors that are positioned on the patient’s most affected ankle and wrist.
In this study, researchers used the sensors to aggregate movement signals while patients performed a series of daily activities such as walking or getting dressed while their PD medications were either in ON or OFF phases. The algorithm was developed to use approximately 15% of the data from four living activities and tested on the remaining data. At which point, data from the two sensors provided researchers with objective measures as opposed to a patient diary or self-report.
Discerning Medication Responses
According to the study results, the algorithm discerned the medication response of PD patients’ daily routines with an average accuracy rate of 90.5% to 94.2% sensitivity, and 85.4% specificity. Based on those results, the researchers noted that their “approach is novel because it is customized to each patient rather than a ‘one-size-fits-all’ approach and can continuously detect and report medication ON and OFF states as patients perform different daily routine activities,” said Behnaz Ghoraani, PhD, senior author, an assistant professor in FAU’s Department of Computer and Electrical Engineering and Computer Science, and a fellow of FAU’s Institute for Sensing and Embedded Network Systems (I-SENSE) and FAU’s Brain Institute (I-BRAIN), in a press release. “Once the algorithm is trained, it can readily be used as a passive system to monitor medication fluctuations without relying on patient or physician engagement.”
— Medical Xpress (@physorg_health) April 17, 2019
“There is a great need for a technology-based system to provide reliable and objective information about the duration in different medication phases for patients with Parkinson’s disease that can be used by the treating physician to successfully adjust therapy,” said Stella Batalama, PhD, dean of FAU’s College of Engineering and Computer Science. “The research that professor Ghoraani and her collaborators are doing in this field could considerably improve both the delivery of care and the quality of life for the millions of patients who are afflicted by this debilitating neurodegenerative disease.”