Machine Learning Analysis Of The Tapping Test And The Archimedean Spiral For The Differential Diagnosis Of Essential Tremor And Parkinson's Disease.
In clinical practice, it is sometimes difficult to establish whether a patient's tremor is due to Parkinson's disease or essential tremor. The distinction is crucial as the health implications differ significantly between the two conditions. Therefore, the present study aims to develop a diagnostic method based on machine learning techniques to help differentiate whether a patient's tremor is due to one condition or the other. To achieve this, 110 patients with tremor, correctly diagnosed with either Parkinson's disease or essential tremor, will participate. They will undergo two diagnostic tests (tapping test and Archimedean spiral) to capture data that can be processed using machine learning techniques.
• Possibility to collaborate in the necessary evaluations.
• Follow-up in the specialized consultation of Movement Disorders at the Neurology Service of Hospital Sant Camil-Consorci Sanitari Alt Penedes i Garraf.
• Legal capacity to provide informed consent.
• Signature of informed consent for study inclusion, either by the participant themselves or by their legal representative.
• Participant with criteria from Group 1 or 2:
⁃ Group 1:
• Confirmed diagnosis of tremor due to Parkinson's disease, clinically established, based on the diagnostic criteria of the Movement Disorders Society, and additionally:
• Tremor associated with bradykinesia of any duration.
• Confirmatory clinical diagnosis of tremor due to Parkinson's disease (stages 1 to 2 of Hoehn and Yahr) by the neurologist responsible for the participant's follow-up.
⁃ Group 2:
• Confirmed diagnosis of essential tremor, based on the criteria of the Movement Disorders Society, and additionally:
• Positional tremor plus kinetic and/or resting tremor with follow-up in outpatient neurology consultations for at least 3 years without a change in diagnosis.
• Absence of bradykinesia.