Interplay between gait and neuropsychiatric symptoms in Parkinson’s Disease
Parkinson’s Disease (PD) is a neurodegenerative disease which involves both motor and non-motor symptoms. Non-motor mental symptoms are very common among patients with PD since the earliest stage. In this context, gait analysis allows to detect quantitative gait variables to distinguish patients af...
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| Format: | Article |
| Language: | English |
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PAGEPress Publications
2022-06-01
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| Series: | European Journal of Translational Myology |
| Subjects: | |
| Online Access: | https://www.pagepressjournals.org/index.php/bam/article/view/10463 |
| _version_ | 1811345279974113280 |
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| author | Michela Russo Marianna Amboni Antonio Volzone Gianluca Ricciardelli Giuseppe Cesarelli Alfonso Maria Ponsiglione Paolo Barone Maria Romano Carlo Ricciardi |
| author_facet | Michela Russo Marianna Amboni Antonio Volzone Gianluca Ricciardelli Giuseppe Cesarelli Alfonso Maria Ponsiglione Paolo Barone Maria Romano Carlo Ricciardi |
| author_sort | Michela Russo |
| collection | DOAJ |
| description |
Parkinson’s Disease (PD) is a neurodegenerative disease which involves both motor and non-motor symptoms. Non-motor mental symptoms are very common among patients with PD since the earliest stage. In this context, gait analysis allows to detect quantitative gait variables to distinguish patients affected by non-motor mental symptoms from patients without these symptoms. A cohort of 68 PD subjects (divided in two groups) was acquired through gait analysis (single and double task) and spatial temporal parameters were analysed; first with a statistical analysis and then with a machine learning (ML) approach. Single-task variables showed that 9 out of 16 spatial temporal features were statistically significant for the univariate statistical analysis (p-value< 0.05). Indeed, a statistically significant difference was found in stance phase (p-value=0.032), swing phase (p-value=0.042) and cycle length (p-value=0.03) of the dual task. The ML results confirmed the statistical analysis, in particular, the Decision Tree classifier showed the highest accuracy (80.9%) and also the highest scores in terms of specificity and precision. Our findings indicate that patients with non-motor mental symptoms display a worse gait pattern, mainly dominated by increased slowness and dynamic instability.
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| first_indexed | 2024-04-13T20:00:47Z |
| format | Article |
| id | doaj.art-f59354de680a455dba7436b7924633ec |
| institution | Directory Open Access Journal |
| issn | 2037-7452 2037-7460 |
| language | English |
| last_indexed | 2024-04-13T20:00:47Z |
| publishDate | 2022-06-01 |
| publisher | PAGEPress Publications |
| record_format | Article |
| series | European Journal of Translational Myology |
| spelling | doaj.art-f59354de680a455dba7436b7924633ec2022-12-22T02:32:13ZengPAGEPress PublicationsEuropean Journal of Translational Myology2037-74522037-74602022-06-0110.4081/ejtm.2022.10463Interplay between gait and neuropsychiatric symptoms in Parkinson’s DiseaseMichela Russo0Marianna Amboni1Antonio Volzone2Gianluca Ricciardelli3Giuseppe Cesarelli4Alfonso Maria Ponsiglione5Paolo Barone6Maria Romano7Carlo Ricciardi8Department of Electrical Engineering and Information Technologies, University of Naples “Federico II”, NaplesCenter for Neurodegenerative Diseases (CEMAND), Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, Baronissi, SA, Italy; IDC Hermitage-Capodimonte, NaplesCenter for Neurodegenerative Diseases (CEMAND), Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, Baronissi, SAAzienda Ospedaliera Universitaria OO. RR. San Giovanni di Dio e Ruggi d’Aragona, SalernoDepartment of Chemical, Materials and Production Engineering, University of Naples “Federico II”, Naples, Italy; Istituti Clinici Scientifici Maugeri IRCCS, PaviaDepartment of Electrical Engineering and Information Technologies, University of Naples “Federico II”, NaplesCenter for Neurodegenerative Diseases (CEMAND), Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, Baronissi, SADepartment of Electrical Engineering and Information Technologies, University of Naples “Federico II”, NaplesDepartment of Electrical Engineering and Information Technologies, University of Naples “Federico II”, Naples, Italy; Istituti Clinici Scientifici Maugeri IRCCS, Pavia Parkinson’s Disease (PD) is a neurodegenerative disease which involves both motor and non-motor symptoms. Non-motor mental symptoms are very common among patients with PD since the earliest stage. In this context, gait analysis allows to detect quantitative gait variables to distinguish patients affected by non-motor mental symptoms from patients without these symptoms. A cohort of 68 PD subjects (divided in two groups) was acquired through gait analysis (single and double task) and spatial temporal parameters were analysed; first with a statistical analysis and then with a machine learning (ML) approach. Single-task variables showed that 9 out of 16 spatial temporal features were statistically significant for the univariate statistical analysis (p-value< 0.05). Indeed, a statistically significant difference was found in stance phase (p-value=0.032), swing phase (p-value=0.042) and cycle length (p-value=0.03) of the dual task. The ML results confirmed the statistical analysis, in particular, the Decision Tree classifier showed the highest accuracy (80.9%) and also the highest scores in terms of specificity and precision. Our findings indicate that patients with non-motor mental symptoms display a worse gait pattern, mainly dominated by increased slowness and dynamic instability. https://www.pagepressjournals.org/index.php/bam/article/view/10463Gait AnalysisMachine LearningParkinson’s diseaseRehabilitation engineering |
| spellingShingle | Michela Russo Marianna Amboni Antonio Volzone Gianluca Ricciardelli Giuseppe Cesarelli Alfonso Maria Ponsiglione Paolo Barone Maria Romano Carlo Ricciardi Interplay between gait and neuropsychiatric symptoms in Parkinson’s Disease European Journal of Translational Myology Gait Analysis Machine Learning Parkinson’s disease Rehabilitation engineering |
| title | Interplay between gait and neuropsychiatric symptoms in Parkinson’s Disease |
| title_full | Interplay between gait and neuropsychiatric symptoms in Parkinson’s Disease |
| title_fullStr | Interplay between gait and neuropsychiatric symptoms in Parkinson’s Disease |
| title_full_unstemmed | Interplay between gait and neuropsychiatric symptoms in Parkinson’s Disease |
| title_short | Interplay between gait and neuropsychiatric symptoms in Parkinson’s Disease |
| title_sort | interplay between gait and neuropsychiatric symptoms in parkinson s disease |
| topic | Gait Analysis Machine Learning Parkinson’s disease Rehabilitation engineering |
| url | https://www.pagepressjournals.org/index.php/bam/article/view/10463 |
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