TremorSoft: an decision support application for differential diagnosis between Parkinson’s disease and essential tremor
A cost-effective, non-invasive, and easy-to-use tool is presented that uses the 6-axis inertial sensor of the smartphone or a specific wearable sensor, boosted by machine learning, to support early differential diagnosis of Parkinson’s disease and Essential Tremor. A dedicated web server helps extra...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/395042 |
| Acceso en línea: | https://hdl.handle.net/2117/395042 https://dx.doi.org/10.1016/j.softx.2023.101393 |
| Access Level: | acceso abierto |
| Palabra clave: | Smartphones Machine learning Mobile application Inertial sensor Tremor assessment Aprenentatge automàtic Telèfons intel·ligents Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
| Sumario: | A cost-effective, non-invasive, and easy-to-use tool is presented that uses the 6-axis inertial sensor of the smartphone or a specific wearable sensor, boosted by machine learning, to support early differential diagnosis of Parkinson’s disease and Essential Tremor. A dedicated web server helps extract the kinematic indexes from the recorded signals, implement the machine learning models and return the resulting classification to the App. Thus, clinicians can use this App as a support tool in the clinic, contributing to performing motor evaluations in the uncertain and undecided stages of the diseases and promoting appropriate, fast, and timely therapeutic responses. |
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