A neurologist or specialist never treats over 40% of patients with Parkinson’s, often because they have difficulty traveling or live too far from healthcare centers. And when patients are evaluated based on testing their motor skills and cognitive functions during clinic visits, the results can be skewed by the day-to-day fluctuation of the disease, making clinical diagnosis very difficult. To address these issues, researchers from MIT have developed an in-home device that can monitor a patient’s movement and gait speed, which doctors can use to evaluate Parkinson’s severity, the progression of the disease, and the patient’s response to medication.
The science and other stuff to know
The device, roughly the size of a Wi-Fi route, gathers data passively by employing radio signals that bounce off the patient as they roam around their house. It creates a ‘human radar’ that can track the movement of a person in a room. Radio waves always travel at the same speed, so the time it takes for the signals to reflect the device indicates how the person is moving.
Additionally, the device incorporates a machine-learning classifier that can distinguish the precise radio signals bouncing off the patient even when other people are strolling around the room. Another perk for the patient is that they don’t need extra gear or to change their behavior. It passively collects the patient’s movements and then computes their gait.
Parkinson’s disease is the second fastest-growing neurodegenerative disease after Alzheimer’s. More than 10 million people worldwide are currently living with the disease, and it affects almost six per 1,000 people aged 45 and over in the U.S., according to the Parkinson’s Foundation.
In the MIT study, researchers showed that by using machine-learning devices to gather data about a patient, a clinician could track Parkinson’s progression and medication response more effectively than in regular, in-clinic evaluations.
In addition, a clinician could use these data to adjust medication dosage more effectively and accurately with the device. It is essential because drugs used to treat disease symptoms can cause serious side effects if a patient gets a high dosage.
The device is still in development, but researchers believe that it has the potential to transform the way Parkinson’s is diagnosed and monitored. This research also represents a great step forward in using passive sensing for long-term health monitoring of chronic diseases.
In the last few years, there’s been a spike in smart devices that support at-home patient care, as well as innovations focused on Parkinson’s disease. From genetically engineered tomatoes that grow medicine for Parkinson’s disease to an assistive robot that detects and prevents falls, especially in the elderly, the future of healthcare looks green.