Researchers Explore the Potential of Finger Tapping Patterns in Early Alzheimer’s Diagnosis
In a recent study, neuropsychologists Vincent Koppelmans and Marit Ruitenberg have discovered that finger-tapping patterns could serve as a new biomarker for Alzheimer’s disease. The researchers conducted computer tests on three distinct groups—healthy individuals, those with mild cognitive impairment (MCI), and Alzheimer’s patients—to examine the relationship between finger-tapping speed and regularity and the disease.
HCN Medical Memo
The implications of this study could be significant. Finger-tapping tests could offer a simple, cost-effective, and non-intrusive method for early Alzheimer’s screening, especially when used in conjunction with existing diagnostic tools like PET and MRI scans. This could be particularly useful in primary care settings, allowing for quicker identification and referral of potential Alzheimer’s patients for further neuropsychological testing.
- The study involved 47 healthy individuals, 27 people with MCI, and 26 people with Alzheimer’s.
- Finger-tapping tests were used to measure speed, reaction time, and regularity of taps.
- Alzheimer’s patients exhibited slower and more irregular tapping compared to other groups.
- The study found a consistent relationship between finger-tapping performance and the size of the hippocampus, a crucial brain area for memory.
- Machine learning was employed to classify participants into groups based on finger-tapping patterns, achieving a 70% accuracy rate.
“You could easily administer these tests in a primary care setting as part of early screening. If someone performs poorly on the test and also exhibits other symptoms indicative of Alzheimer’s, they could be referred for neuropsychological testing and possibly a PET scan.”
– Vincent Koppelmans, Neuropsychologist
- The finger-tapping test could be a cost-effective and less intrusive alternative to PET and MRI scans.
- The test could be administered in primary care settings for early screening of Alzheimer’s.
- The study is part of a broader research effort to improve diagnostics through machine learning and motor function profiling.
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