Applications
Application of the Month: 3D Printed Pen for Diagnosing Parkinson’s Disease
Parkinson’s disease (PD) is a neurodegenerative disorder that affects an estimated 10 million people worldwide, and it is the second most common neurodegenerative disease after Alzheimer’s. Still, for a condition that is so widespread, it is difficult to diagnose. There&hel
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Parkinson’s disease (PD) is a neurodegenerative disorder that affects an estimated 10 million people worldwide, and it is the second most common neurodegenerative disease after Alzheimer’s. Still, for a condition that is so widespread, it is difficult to diagnose. There are no lab or imaging tests that can confirm a diagnosis, although certain tests, like MRIs or blood tests, can support the diagnosis as PD or rule out other conditions that mimic PD. Instead, the disease requires a “clinical” diagnosis, which means that a doctor considers a patient’s history, symptoms and physical exam to determine if they have it. However, these methods are often inefficient and lack objective, quantitative standards.
A team of researchers at the University of California, Los Angeles (UCLA) is trying to develop an alternative: a 3D printed diagnostic pen. Signs of PD look different for everyone, and common symptoms include (but are not limited to) tremors, slowness of movement and rigidity. Handwriting is a process that combines cognitive, perceptual and fine motor skills, all of which are affected by PD. By analyzing handwriting patterns, users could gain critical insights and quantitative biometric markers for diagnosis.

Parkinson’s Disease patient writing with 3D printed pen (Photo Credit: Jun Chen via The Guardian)
A 3D Printed Upgrade
The UCLA researchers are not the first to think of a diagnostic pen for PD. In fact, conventional handwriting analysis tools like digital tablets have been widely used. These tools specialize in tracking handwriting trajectories and analyzing the resulting handwriting traces, but they often overlook the motor symptoms that occur during writing. Additionally, these tools are costly and complex to set up, creating a challenge for broad implementation and use in non-clinical settings. The researchers also had low-income countries in mind, knowing that they face limited access to subspecialty resources for PD diagnosis, as well as an insufficient number of neurologists.




