Recent Study Demonstrates Smartphone App’s Ability to Detect Early Signs of Movement Disorders

According to a story from Parkinson’s News Today, a recent study describes the ability of an innovative smartphone app that uses touch-based input in order to detect the early signs of various motor disorders. The app was originally developed for Huntington’s disease, but it can also be used to detect signs of other neurological illnesses as well that affect movement, such as Parkinson’s disease and Alzheimer’s.

About The App

The capabilities of the app definitely could make it a valuable tool for doctors and could allow patients with movement disorders to be diagnosed and treated earlier in the course of their disease. Many motor disorders are progressive illnesses that get worse over time, so prompt intervention is critical in order to produce the best treatment outcomes.

Such technologies, which monitor abnormalities in movement, have been utilized for years now in researching motor disorders, which can be difficult to distinguish from symptoms alone. In Parkinson’s research for example, wearable sensors have been used in order to monitor and detect subtle tremors, jerky movements, and postural changes. The primary innovation of this app is that no wearable sensors are necessary in order for meaningful diagnostic evidence to be gathered.

The app involves three different touch-based tasks in which the patient must touch an indicated target on the screen with one or more of their fingers. The app detects the trajectory of the patients fingers, the accuracy of their touch, and the duration of their response times. Patients with neurological disorders that affect movement are generally unable to complete these tasks with the same accuracy and speed as a healthy person.

Although the app is fully functional on a smartphone, the researchers recommend using the program on devices with larger screens and high resolution displays.

The study tested the app with 11 Huntington’s disease patients and an equal number of healthy controls. The app was able to distinguish between the patients and the controls and could also predict if a patient was at high risk of for rapid progression of Huntington’s disease symptoms. The app was able to identify symptoms with 86.4 percent accuracy.

This study was originally published in the IEEE Journal of Biomedical and Health Informatics and can be found here.


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