Academic Journal
Sequence-based dynamic handwriting analysis for Parkinson’s disease detection with one-dimensional convolutions and BiGRUs
| العنوان: | Sequence-based dynamic handwriting analysis for Parkinson’s disease detection with one-dimensional convolutions and BiGRUs |
|---|---|
| المؤلفون: | Diaz, Moises, Moetesum, Momina, Siddiqi, Imran, Vessio, Gennaro |
| المساهمون: | Diaz, Moise, Moetesum, Momina, Siddiqi, Imran, Vessio, Gennaro |
| سنة النشر: | 2021 |
| المجموعة: | Università degli Studi di Bari Aldo Moro: CINECA IRIS |
| مصطلحات موضوعية: | Parkinson’s disease, Dynamic handwriting analysis, Recurrent neural networks, Computer-aided diagnosis |
| الوصف: | Parkinson’s disease (PD) is commonly characterized by several motor symptoms, such as bradykinesia, akinesia, rigidity, and tremor. The analysis of patients’ fine motor control, particularly handwriting, is a powerful tool to support PD assessment. Over the years, various dynamic attributes of handwriting, such as pen pressure, stroke speed, in-air time, etc., which can be captured with the help of online handwriting acquisition tools, have been evaluated for the identification of PD. Motion events, and their associated spatio-temporal properties captured in online handwriting, enable effective classification of PD patients through the identification of unique sequential patterns. This paper proposes a novel classification model based on one-dimensional convolutions and Bidirectional Gated Recurrent Units (BiGRUs) to assess the potential of sequential information of handwriting in identifying Parkinsonian symptoms. One-dimensional convolutions are applied to raw sequences as well as derived features; the resulting sequences are then fed to BiGRU layers to achieve the final classification. The proposed method outperformed state-of-the-art approaches on the PaHaW dataset and achieved competitive results on the NewHandPD dataset. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/wos/WOS:000614253700005; volume:168; firstpage:114405; journal:EXPERT SYSTEMS WITH APPLICATIONS; https://hdl.handle.net/11586/343189 |
| DOI: | 10.1016/j.eswa.2020.114405 |
| الاتاحة: | https://hdl.handle.net/11586/343189 https://doi.org/10.1016/j.eswa.2020.114405 |
| Rights: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.5F44B659 |
| قاعدة البيانات: | BASE |
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