: Handwriting skills could be highly impaired in patients affected by Parkinson's disease (PD), and for this reason its analysis had always been considered relevant. In handwriting assessment, Archimedes spiral drawing is one of the most proposed tasks, due to its peculiar shape and ease of execution. In the last decades, digitizing tablets had been widely employed for the evaluation of the spiral performance, providing a cheap and non-invasive way to gather quantitative information, to be combined with the classical clinical examination. Despite this advantage, such approach cannot easily be adopted in an unsupervised scenario and lacks the natural feel of the traditional pen-and-paper approach. This work aims at overcoming these limitations by employing a smart ink pen, designed to write on paper and instrumented with inertial and force sensors, to automatically collect data related to spiral drawing execution of PD patients (n=30) and age-matched healthy controls (n=30). From the raw data, several time and frequency domains features were extracted and compared between the groups. The statistical analysis revealed some significant differences, showing less smooth acceleration and force profiles for PD patients. However, given the heterogeneous symptoms presented by the PD cohort, a detailed analysis of exemplifying PD patients was conducted, showing the ability of Archimedes spiral drawing to capture and quantify PD characteristic features.Clinical Relevance- Among the first clinical manifestations of the pathology, handwriting impairment appears in PD patients. It is often underestimated and not investigated properly. This easy-to-use tool could be very useful as a large-scale screening, but also for treatment efficacy evaluation and for the identification of PD subgroups.

A smart ink pen for spiral drawing analysis in patients with Parkinson's disease

Toffoli, Simone;Lunardini, Francesca;Parati, Monica;De Maria, Beatrice;Ferrante, S
2021-01-01

Abstract

: Handwriting skills could be highly impaired in patients affected by Parkinson's disease (PD), and for this reason its analysis had always been considered relevant. In handwriting assessment, Archimedes spiral drawing is one of the most proposed tasks, due to its peculiar shape and ease of execution. In the last decades, digitizing tablets had been widely employed for the evaluation of the spiral performance, providing a cheap and non-invasive way to gather quantitative information, to be combined with the classical clinical examination. Despite this advantage, such approach cannot easily be adopted in an unsupervised scenario and lacks the natural feel of the traditional pen-and-paper approach. This work aims at overcoming these limitations by employing a smart ink pen, designed to write on paper and instrumented with inertial and force sensors, to automatically collect data related to spiral drawing execution of PD patients (n=30) and age-matched healthy controls (n=30). From the raw data, several time and frequency domains features were extracted and compared between the groups. The statistical analysis revealed some significant differences, showing less smooth acceleration and force profiles for PD patients. However, given the heterogeneous symptoms presented by the PD cohort, a detailed analysis of exemplifying PD patients was conducted, showing the ability of Archimedes spiral drawing to capture and quantify PD characteristic features.Clinical Relevance- Among the first clinical manifestations of the pathology, handwriting impairment appears in PD patients. It is often underestimated and not investigated properly. This easy-to-use tool could be very useful as a large-scale screening, but also for treatment efficacy evaluation and for the identification of PD subgroups.
2021
43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
978-1-7281-1179-7
Acceleration
Handwriting
Humans
Ink
Physical Examination
Parkinson Disease
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1193919
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