Related Experiment Video
Updated: Jul 27, 2025
19:44
A Tactile Automated Passive-Finger Stimulator TAPS
Published on: June 3, 2009
13.8K
A First Methodological Development and Validation of ReTap: An Open-Source UPDRS Finger Tapping Assessment Tool Based
Jeroen G V Habets1, Rachel K Spooner2, Varvara Mathiopoulou1
1Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité Universitaetsmedizin Berlin, 10117 Berlin, Germany.
Sensors (Basel, Switzerland)
|June 10, 2023
Summary
This study introduces ReTap, an open-source tool that uses accelerometry to automatically score Parkinson's disease (PD) bradykinesia via finger tapping. ReTap accurately predicts clinical scores, offering a reliable method for symptom assessment.
Area of Science:
- Neurology
- Biomedical Engineering
- Data Science
Background:
- Bradykinesia is a primary symptom of Parkinson's disease (PD), and its accurate measurement is crucial for treatment evaluation.
- Current clinical assessments of bradykinesia, like finger tapping, are often subjective and lack precision for tracking daily symptom fluctuations.
- Existing automated tools for bradykinesia scoring are proprietary and not ideal for capturing intraday variations.
Purpose of the Study:
- To develop and validate ReTap, an open-source software tool for the automated prediction of finger tapping scores in people with Parkinson's disease (PwP).
- To assess the reliability and accuracy of ReTap in quantifying bradykinesia using index finger accelerometry data.
- To provide an accessible and objective method for measuring finger tapping performance, aiding in PD management.
Main Methods:
- Collected 10-second index finger tapping data from 37 people with Parkinson's disease (PwP) during routine clinical visits.
- Utilized accelerometry to analyze kinematic features from 350 tapping sessions.
- Developed and validated the ReTap tool for automated prediction of Unified Parkinson's Disease Rating Scale (UPDRS) scores based on extracted kinematic features.
Main Results:
- ReTap successfully identified tapping blocks in over 94% of recorded sessions.
- The tool extracted clinically relevant kinematic features from each finger tap.
- ReTap accurately predicted expert-rated UPDRS scores significantly better than chance in a validation dataset (n=102).
- ReTap-predicted scores showed a positive correlation with expert ratings in over 70% of individual subjects in the holdout dataset.
Conclusions:
- ReTap offers a validated, open-source solution for objective and accessible finger tapping assessment in Parkinson's disease.
- The tool can provide reliable bradykinesia scores, suitable for both clinical settings and remote patient monitoring.
- ReTap has the potential to enhance the detailed, open-source analysis of bradykinesia and improve PD management.
