Article
Digitalizing Handwritten Digits of Patients with Parkinson’s Disease Utilizing Consumer Hardware and Open-Source Software
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Authors
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Christopher Gundler
- Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Alexander Johannes Wiederhold
- Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Monika Pötter-Nerger
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| Published: | September 6, 2024 |
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Outline
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Introduction: Parkinson’s disease represents a burdensome condition with complex manifestations. A licensed, standardized paper-based questionnaire is completed by both patients and physicians to monitor the progression and state of the disease. However, integrating the obtained scores into digital systems still poses a challenge.
Methods: Paper-based handwriting is intuitive and an efficient mode of human-computer interaction. Accordingly, we transformed a consumer-grade tablet into a device where an exact digital copy of the disease-specific questionnaire can be filled with the supplied pen. Utilizing a small convolutional neural network directly on the device and trained on MNIST data, we translated the handwritten digits to appropriate LOINC codes and made them accessible through a FHIR-compatible HTTP interface.
Results: When evaluating the usability from a patient-centric point of view, the System Usability Score revealed an excellent rating (SUS = 83.01) from the participants. However, we identified some challenges associated with the magnetic pen and the flat design of the device.
Conclusion: In setups where certified medical devices are not required, consumer hardware can be used to map handwritten digits of patients to appropriate medical standards without manual intervention through healthcare professionals.
The authors declare that they have no competing interests.
The authors declare that an ethics committee vote is not required.
