Evidence map›Paper›PMID 37486475›Full record

ArticleAdvances in experimental medicine and biology2023

A Sensor-Based Platform for Early-Stage Parkinson's Disease Monitoring.

Marios G Krokidis, Themis P Exarchos, Aristidis G Vrahatis, Christos Tzouvelekis, Dimitrios Drakoulis, Foteini Papavassileiou, Panagiotis Vlamos

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Article in Advances in experimental medicine and biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Marios G KrokidisBioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu, Greece. mkrokidis@ionio.gr.
Themis P ExarchosBioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu, Greece.
Aristidis G VrahatisBioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu, Greece.
Christos TzouvelekisBioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu, Greece.
Dimitrios DrakoulisTelesto Technologies, Athens, Greece.
Foteini PapavassileiouTelesto Technologies, Athens, Greece.
Panagiotis VlamosBioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu, Greece. vlamos@ionio.gr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biosensing platforms have gained much attention in clinical practice screening thousands of samples simultaneously for the accurate detection of important markers in various diseases for diagnostic and prognostic purposes. Herein, a framework for the design of an innovative methodological approach combined with data processing and appropriate software in order to implement a complete diagnostic system for Parkinson's disease exploitation is presented. The integrated platform consists of biochemical and peripheral sensor platforms for measuring biological and biometric parameters of examinees, a central collection and management unit along with a server for storing data, and a decision support system for patient's state assessment regarding the occurrence of the disease. The suggested perspective is oriented on data processing and experimental implementation and can provide a powerful holistic evaluation of personalized monitoring of patients or individuals at high risk of manifestation of the disease.

Indexed as

Parkinson DiseaseHumansSoftwareBiosensorsDecision support systemParkinson’s diseasePeripheral sensorsUPDRSWearable devices

Identifiers

PMID37486475

What OpenQuestion holds

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Registered trials

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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.