New Sensor Technology Can Detect Medication Response Automatically for Parkinson’s Disease Patients

According to a story from EurekAlert!, effective management of Parkinson’s disease can be a serious challenge. Part of the reason that the management of the illness is so difficult is the result of fluctuations in patient response to therapy that can be almost impossible to predict. These fluctuations often require changes into how the patient is treated, but doing this effectively is still quite difficult. However, a new system of sensors linked to a precisely designed algorithm could help solve this issue.

About Parkinson’s Disease

Parkinson’s disease is a type of long term, progressive, degenerative illness that affects the central nervous system. Symptoms tend to develop over a period of years and primarily affect the movement ability and mental state of the patient. The cause of Parkinson’s disease remains a mystery, although there are a number of risk factors that have been identified. These factors include head injuries, pesticide exposure, and certain genetic variants and mutations. About 15 percent of patients have a close relative with the disease, suggesting some genetic connection. Symptoms include slowed movements, poor coordination, trouble walking, shaking, stiffness, abnormal posture, depression, anxiety, inhibited thinking, hallucinations, and dementia. Treatment may involve a number of medications, rehabilitation, and surgical operations. Survival rate varies, but most patients survive around a decade after getting diagnosed. To learn more about Parkinson’s disease, click here.

Motor Fluctuations in Parkinson’s Disease

These fluctuations in treatment response are primarily related to the motor symptoms of Parkinson’s. The vast majority of Parkinson’s disease patients will eventually face this problem; about 50 percent experience these fluctuations within the first three to five years of their diagnosis, but ten years in this number jumps to 80 percent. Treatment decisions related to these fluctuations are usually addressed with clinical evaluations and patient self-reporting, but this is not always reliable.

However, a team of scientists at the Florida Atlantic University’s College of Engineering and Computer Science have developed an algorithm and a system of sensors worn by the patient that can accurately detect the appearance of motor symptom fluctuations in Parkinson’s disease patients. The system uses only two sensors: one on the patient’s most affected ankle and another on the patient’s most affected wrist. A study of the system found that the technology could detect fluctuations with 90.5 percent accuracy on average.

This technology could allow for doctors to tailor their treatment to each patient much more precisely.


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