Evidence map›Paper›PMID 35270853›Full record

ArticleSensors (Basel, Switzerland)2022

Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson's Disease.

Alfonso Maria Ponsiglione, Carlo Ricciardi, Francesco Amato, Mario Cesarelli, Giuseppe Cesarelli, Giovanni D'Addio

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alfonso Maria PonsiglioneDepartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.ORCID 0000-0003-1346-515X
Carlo RicciardiDepartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.ORCID 0000-0001-7290-6432
Francesco AmatoDepartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.ORCID 0000-0002-9053-3139
Mario CesarelliDepartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.
Giuseppe CesarelliInstitute of Care and Scientific Research of Telese of ICS Maugeri SPA SB, 82037 Telese Terme, Italy.ORCID 0000-0001-8303-5900
Giovanni D'AddioInstitute of Care and Scientific Research of Telese of ICS Maugeri SPA SB, 82037 Telese Terme, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The impact of neurodegenerative disorders is twofold; they affect both quality of life and healthcare expenditure. In the case of Parkinson's disease, several strategies have been attempted to support the pharmacological treatment with rehabilitation protocols aimed at restoring motor function. In this scenario, the study of upper limb control mechanisms is particularly relevant due to the complexity of the joints involved in the movement of the arm. For these reasons, it is difficult to define proper indicators of the rehabilitation outcome. In this work, we propose a methodology to analyze and extract an ensemble of kinematic parameters from signals acquired during a complex upper limb reaching task. The methodology is tested in both healthy subjects and Parkinson's disease patients (N = 12), and a statistical analysis is carried out to establish the value of the extracted kinematic features in distinguishing between the two groups under study. The parameters with the greatest number of significances across the submovements are duration, mean velocity, maximum velocity, maximum acceleration, and smoothness. Results allowed the identification of a subset of significant kinematic parameters that could serve as a proof-of-concept for a future definition of potential indicators of the rehabilitation outcome in Parkinson's disease.

Indexed as

Parkinson DiseaseStrokeBiomechanical PhenomenaHumansQuality of LifeUpper Extremitybiomedical signal processingkinematic featuresmotion analysisParkinson’s diseasereaching movements

Identifiers

PMID35270853
PMCPMC8915106

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.