3D-printed magnetoelastic smart pen may help diagnose Parkinson’s

Yearly, tens of 1000’s of individuals with indicators of Parkinson’s illness go unnoticed till the incurable neurodegenerative situation has already progressed.

Motor signs, corresponding to tremors or rigidity, typically emerge solely after vital neurological injury has occurred. By the point sufferers are identified, greater than half of their dopamine-producing neurons could already be misplaced. This type of diagnostic delay can restrict remedy choices and sluggish progress on early-stage interventions.

Whereas there are present checks to detect biomarkers of Parkinson’s, together with cell loss within the mind and inflammatory markers in blood, they usually require entry to specialists and dear tools at main medical facilities, which can be out of attain for a lot of.

Led by Jun Chen, an affiliate professor of bioengineering on the UCLA Samueli College of Engineering, researchers have developed a seemingly easy but efficient software: a wise, self-powered magnetoelastic pen that might assist detect early indicators of Parkinson’s by analyzing an individual’s handwriting.

The extremely delicate diagnostic pen, described in a UCLA-led examine and revealed as a canopy story within the June difficulty of Pure Chemical Engineering, incorporates a smooth, silicon magnetoelastic tip and ferrofluid ink—a particular liquid containing tiny magnetic particles. When the pen’s tip is pressed towards a floor or moved within the air, the pen converts each on-surface and in-air writing motions into high-fidelity, quantifiable indicators by way of a coil of conductive yarn wrapped across the pen’s barrel. Though not meant for writing, the pen is self-powered leveraging modifications within the magnetic properties of its tip and the dynamic circulation of the ferrofluid ink to generate information.

To check the pen’s diagnostic potential, the crew carried out a pilot examine with 16 contributors, three of whom had Parkinson’s illness. The pen recorded detailed handwriting indicators, which have been then analyzed by a neural community skilled to detect motor patterns related to the illness. The mannequin was in a position to distinguish contributors with Parkinson’s from wholesome people with a median accuracy of 96.22%.

“Detection of delicate motor signs unnoticeable to the bare eye is essential for early intervention in Parkinson’s illness,” mentioned Chen, who’s the examine’s corresponding creator. “Our diagnostic pen presents an inexpensive, dependable and accessible software that’s delicate sufficient to select up delicate actions and can be utilized throughout massive populations and in resource-limited areas.”

The researchers anticipate that this pen might rework early detection of Parkinson’s and different neurodegenerative situations. Slightly than ready for signs to change into disruptive, major care physicians or geriatric specialists might administer a fast handwriting check throughout routine visits and use the information to tell earlier referrals or remedy.

Wei Wang, a professor who holds the Leonard Kleinrock Time period Chair in Laptop Science, and Tune Li, a chancellor’s professor in bioengineering, are additionally authors on the paper. Different authors embrace graduate college students Guorui Chen, Zhaoqi Duan, Kamryn Scott and Xun Zhao; analysis scientists Zeyang Liu; and postdoctoral students Trinny Tat and Yihao Zhou—all members of Chen’s Bioelectronics Analysis Group. They have been joined by graduate pupil Junkai Zhang, who is suggested by Wang. Chen can also be a member of the California NanoSystems Institute at UCLA.