Abstract
AbstractParkinson’s Disease (PD) is a neurodegenerative movement disease affecting over 6 million people worldwide. Current diagnosis is based on clinical and observational criteria only, resulting in a high misdiagnosis rate. Approximately 75% of people with PD have hand tremor, which can precede clinical diagnosis by up to 6 years. Previous studies have shown that early PD can be accurately detected from keystroke features while typing, and this study investigated whether tremor can be detected as well. Typing data from 76 subjects, with and without PD, including 27 with PD and 15 with tremor, was analysed and showed that hand tremor in PD can be detected from keystroke features. This novel technique has not been used before and was able to achieve an overall sensitivity of 67% and a specificity of 80% and was also able to differentiate PD tremor from essential tremor. This means that the diagnosis of early PD through typing can achieve the clinical requirement of at least two cardinal features being present (bradykinesia and tremor). Less than half a page of typing is needed, the technique does not require any specialised equipment, and can take place in the patient’s home as they type normally on a computer.
Publisher
Cold Spring Harbor Laboratory
Cited by
2 articles.
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1. Detection of Parkinson’s disease with keystroke data;Computer Methods in Biomechanics and Biomedical Engineering;2023-08-21
2. Machine Learning Methods for Managing Parkinson’s Disease;Learning and Analytics in Intelligent Systems;2020