Machine learning can detect the presence of Mild cognitive impairment in patients affected by Parkinson’s Disease

Ricciardi, Carlo; Amboni, Marianna; Santis, Chiara De; Ricciardelli, Gianluca; Improta, Giovanni; D’Addio, Giovanni; Cuoco, Sofia; Picillo, Marina; Barone, Paolo; Cesarelli, Mario

doi:10.1109/memea49120.2020.9137301

Cited by 28 publications

(31 citation statements)

References 29 publications

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“…Before the trials, all participants were trained to walk at a normal pace, at their usual speed, without any suggestion on prioritizing walking or calculating. Further details on the procedure are described elsewhere ( 14 , 15 ).…”

Section: Methodsmentioning

confidence: 99%

“…Values are given in mean ± standard deviation unless otherwise specified. PSP phenotypes did not differ for years of education (p = 0.905) 15. RAWLT, the Rey auditory verbal learning test; BJLO, Benton's Judjement of Line Orientation; M, men; MOCA, Montreal Cognitive Assessment battery; N, number; PSP-RS, Progressive Supranuclear Palsy with Richardson's syndrome; TMT, Trial Making Test; vPSP, the other variant syndromes of Progressive Supranuclear Palsy; W, women.…”

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confidence: 99%

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Gait Analysis in Progressive Supranuclear Palsy Phenotypes

et al. 2021

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The objective of the present study was to describe gait parameters of progressive supranuclear palsy (PSP) phenotypes at early stage verifying the ability of gait analysis in discriminating between disease phenotypes and between the other variant syndromes of PSP (vPSP) and Parkinson's disease (PD). Nineteen PSP (10 PSP-Richardson's syndrome, five PSP-parkinsonism, and four PSP-progressive gait freezing) and nine PD patients performed gait analysis in single and dual tasks. Although phenotypes showed similar demographic and clinical variables, Richardson's syndrome presented worse cognitive functions. Gait analysis demonstrated worse parameters in Richardson's syndrome compared with the vPSP. The overall diagnostic accuracy of the statistical model during dual task was almost 90%. The correlation analysis showed a significant relationship between gait parameters and visuo-spatial, praxic, and attention abilities in PSP-Richardson's syndrome only. vPSP presented worse gait parameters than PD. Richardson's syndrome presents greater gait dynamic instability since the earliest stages than other phenotypes. Computerized gait analysis can differentiate between PSP phenotypes and between vPSP and PD.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

Gait Analysis in Progressive Supranuclear Palsy Phenotypes

et al. 2021

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“…The choice of "k" is therefore very important as if it is too small, the classification could be "blind" in the sense that important instances could be not considered in the classification process; on the other hand, if "k" is too large very distant instances could be included in the evaluation even if they are very dissimilar with respect to the test sample. In [122], kNN are used for detecting the presence of MCI in PD patient. Spatio-temporal features are evaluated in three different conditions: normal gait, motor dual task and cognitive dual task.…”

Section: B Instance-based Methodsmentioning

confidence: 99%

“…RF exhibits the overall highest accuracy of 86.4%, but also GBT achieves an accuracy of 84% that can be considered a good result especially considering the high level of complexity. A similar complex problem is considered in [122], where the aim is to differentiate between PD patients with and without MCI. Furthermore, single gait task and dual task conditions (motor and cognitive) are compared.…”

Section: Decision Tree Random Forest Gradient Boosted Treementioning

confidence: 99%

Human Gait Analysis in Neurodegenerative Diseases: A Review

Cicirelli

Impedovo

Dentamaro

et al. 2022

IEEE J. Biomed. Health Inform.

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This paper reviews the recent literature on technologies and methodologies for quantitative human gait analysis in the context of neurodegnerative diseases. The use of technological instruments can be of great support in both clinical diagnosis and severity assessment of these pathologies. In this paper, sensors, features and processing methodologies have been reviewed in order to provide a highly consistent work that explores the issues related to gait analysis. First, the phases of the human gait cycle are briefly explained, along with some nonnormal gait patterns (gait abnormalities) typical of some neurodegenerative diseases. The work continues with a survey on the publicly available datasets principally used for comparing results. Then the paper reports the most common processing techniques for both feature selection and extraction and for classification and clustering. Finally, a conclusive discussion on current open problems and future directions is outlined.

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“…Gait analysis has been employed for different objectives in PD patients, including the investigation of pathophysiological mechanisms underpinning the disease, evaluation of treatment outcomes, automatic recognition of PD symptoms, and implementation of algorithms for PD diagnosis and staging [11][12][13][14] . In addition, gait analysis has been used to explore the association between specific gait patterns and specific symptoms of PD, such as mild cognitive impairment 15,16 and freezing of gait 17 .…”

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Gait analysis may distinguish progressive supranuclear palsy and Parkinson disease since the earliest stages

Amboni

Ricciardi

Picillo

et al. 2021

Sci Rep

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Progressive supranuclear palsy (PSP) is a rare and rapidly progressing atypical parkinsonism. Albeit existing clinical criteria for PSP have good specificity and sensitivity, there is a need for biomarkers able to capture early objective disease-specific abnormalities. This study aimed to identify gait patterns specifically associated with early PSP. The study population comprised 104 consecutively enrolled participants (83 PD and 21 PSP patients). Gait was investigated using a gait analysis system during normal gait and a cognitive dual task. Univariate statistical analysis and binary logistic regression were used to compare all PD patients and all PSP patients, as well as newly diagnosed PD and early PSP patients. Gait pattern was poorer in PSP patients than in PD patients, even from early stages. PSP patients exhibited reduced velocity and increased measures of dynamic instability when compared to PD patients. Application of predictive models to gait data revealed that PD gait pattern was typified by increased cadence and longer cycle length, whereas a longer stance phase characterized PSP patients in both mid and early disease stages. The present study demonstrates that quantitative gait evaluation clearly distinguishes PSP patients from PD patients since the earliest stages of disease. First, this might candidate gait analysis as a reliable biomarker in both clinical and research setting. Furthermore, our results may offer speculative clues for conceiving early disease-specific rehabilitation strategies.

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Machine learning can detect the presence of Mild cognitive impairment in patients affected by Parkinson’s Disease

Cited by 28 publications

References 29 publications

Gait Analysis in Progressive Supranuclear Palsy Phenotypes

Gait Analysis in Progressive Supranuclear Palsy Phenotypes

Human Gait Analysis in Neurodegenerative Diseases: A Review

Gait analysis may distinguish progressive supranuclear palsy and Parkinson disease since the earliest stages

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