CNS Open Data
Research GuidesTrend ReportsCompare ToolOpen Datasets

Medical & Academic Disclaimer: CNS Open Data is an academic neuroinformatics platform indexing open research datasets, preprints, and clinical trial pipelines for researchers and data scientists. Content on this site does not constitute medical advice, clinical diagnosis, or treatment recommendations.

CNS Open Data— Open Science Portal for Central Nervous System Research|Research Guides|Trend Reports|Glossary|Ranking|Open Datasets|About|Privacy Policy|Contact
AlzforumOpenNeuroDANDI ArchiveAgora (AMP-AD)
HomeOpen DatasetParkinson's & MovementA Computational Framework for Early Neurological Disorder Screening Using Speech Signals and Embedded System
Zenodo (CERN Open Data)Parkinson's & MovementOpen DatasetFAIR Metadata / API
Commercial Use Allowed - CC-BY-4.0

A Computational Framework for Early Neurological Disorder Screening Using Speech Signals and Embedded System

October 28, 2026
Algahtani, Faris, Sultan
DOI: 10.5281/zenodo.23736466
On This Page:Specs MatrixSummary & AbstractDeep Research BriefData Access & CodeCitations & Related

Study Design & Technical Specifications

Sample Size / Cohort

1 Data Files

Subject / Study Model

CNS Experimental / Clinical Model

Analytical Modalities

Open Research Dataset

Primary Abstract & Repository Description

Source: Zenodo (CERN Open Data)
Interpreting speech signals as nonlinear dynamical systems provides a promising foundation for the early diagnosis of neurological disorders. This research concentrates on Parkinson’s disease and ataxia, conditions in which subtle alterations in speech patterns emerge as early manifestations of neurodegeneration. We introduce a diagnostic framework that integrates deep learning techniques with statistical signal processing, drawing upon concepts from mathematical physics, including energy minimization and stochastic modeling. By conceptualizing speech variability as a dynamic field, the proposed method captures fine-grained perturbations and inherent uncertainty often overlooked by conventional approaches. Validation on well-established Parkinson’s speech datasets reveals enhanced classification accuracy and robustness relative to traditional models. Furthermore, the framework’s computational efficiency facilitates deployment on embedded systems and neuromorphic hardware, enabling real-time, portable applications. In addition to its clinical implications, this work advances the application of physics-informed methodologies to the analysis of complex biomedical sig...
CNS Open Data Deep Research Brief

Editorial Critique, Methodological Value & Reusability Guide

Structured via CNS Domain Knowledge Engine

1. Scientific Context & Premise

Primary Premise (Zenodo (CERN Open Data)): "Interpreting speech signals as nonlinear dynamical systems provides a promising foundation for the early diagnosis of neurological disorders." Within Parkinson's Disease (PD), this work examines Zenodo, Open Dataset, Keywords: Nonlinear Dynamics; Statistical Signal Processing; Gaussian Processes; Speech Signal Modelling; Neurological Disorder Detection. in relation to α-synuclein seed amplification assays (SAA), LRRK2/GBA1 variants, DAT-SPECT, and digital motor kinematics. Authored by Algahtani, Faris, Sultan.

2. Study Architecture & Findings

Study Architecture: Experimental / Clinical CNS Design (1 Data Files) utilizing Open Research Dataset [DOI: 10.5281/zenodo.23736466]. Key reported conclusion: "In addition to its clinical implications, this work advances the application of physics-informed methodologies to the analysis of complex biomedical sig..."

3. Secondary Analysis & Reusability

Secondary Analysis Applications: (1) Cross-referencing Open Research Dataset variables (Zenodo, Open Dataset, Keywords: Nonlinear Dynamics; Statistical Signal Processing; Gaussian Processes; Speech Signal Modelling; Neurological Disorder Detection.) against open repositories in Parkinson's Disease (PD); (2) Benchmarking feature distributions and effect sizes reported in "A Computational Framework for Early Neurological Disorder Screening Using Speech"; (3) Informing cohort stratification and endpoint selection.

4. Methodological Caveats & Governance

Methodological Note: When integrating these Open Research Dataset findings, account for cohort-specific inclusion criteria (1 Data Files), potential site/instrument batch effects, and repository license terms (CC-BY-4.0).

Related CNS Open Data Research Playbooks & Methodology Guides
Parkinson's Disease (PD) Open Data Guide: Alpha-Synuclein Assays, Basal Ganglia LFP & Cohort Harmonization
11 min read • Open Playbook
Open Neuroscience Data Governance Guide: CC0, CC-BY, Data Use Agreements (DUA) & Privacy Compliance
10 min read • Open Playbook

Data Access, Reproducibility & Analysis Starter Guide

FAIR Open Science & Clinical Metadata Verification Protocol

FAIR Metadata / API

Quick Data Access & Structured Export

Open the primary repository directly or download structured metadata (JSON / CSV) in one click.

Open Primary Data (Zenodo (CERN Open Data))Download Data

This resource is indexed under FAIR (Findable, Accessible, Interoperable, and Reusable) open-science metadata standards, enabling programmatic cross-referencing across Europe PMC, Semantic Scholar, ClinicalTrials.gov, and CNS Open Data.

Programmatic Data Retrieval (Python Starter Code & Recommended SDKs)

Python Quickstart: Query Europe PMC & Semantic Scholar Metadata

# Fetch structured bibliographic & open-access data via Europe PMC REST API
import urllib.request
import urllib.parse
import json

query = "DOI:\"10.5281/zenodo.23736466\""
url = f"https://www.ebi.ac.uk/europepmc/webservices/rest/search?query={urllib.parse.quote(query)}&format=json&resultType=core"

with urllib.request.urlopen(url, timeout=10) as response:
    payload = json.loads(response.read().decode("utf-8"))
    results = payload.get("resultList", {}).get("result", [])
    if results:
        record = results[0]
        print("Title:", record.get("title"))
        print("Journal / Source:", record.get("journalTitle") or record.get("bookOrReportDetails"))
        print("Cited By Count:", record.get("citedByCount", 0))

Recommended Open-Source Software & SDKs

NiBabelPython SDK

Read and write access to NIfTI, GIFTI, and BIDS neuroimaging file formats in Python.

Scanpy (scverse)Python / AnnData

Scalable Python toolkit for analyzing AnnData (.h5ad) single-cell gene expression matrices.

Standardized 4-Step Workflow & Governance Checklist

Standardized Acquisition & Preprocessing Workflow

1. Programmatic Metadata & Full-Text OA Retrieval

Query Europe PMC or Crossref REST APIs using the persistent DOI/URL to retrieve structured XML full text, supplementary tables, and grant links.

2. Study Design & Cohort Eligibility Screening

Extract sample size, inclusion/exclusion criteria, and primary outcome endpoints for systematic review (PRISMA) inclusion.

3. Data Availability & Supplementary Repository Linkage

Locate accession numbers (GEO, SRA, OpenNeuro, DANDI, Zenodo, Figshare) referenced in the Data Availability section.

4. Citation Graph & Replication Tracking

Monitor supporting and contrasting citations over time to verify whether key findings have been independently replicated.

Reproducibility & Governance Checklist

  • Verify whether the source is a peer-reviewed journal publication or an unrefereed preprint before clinical citation.
  • Check supplementary data licenses (CC-BY / CC0) when extracting figures or summary statistics for meta-analyses.
  • Cross-reference NCT clinical trial identifiers when evaluating therapeutic efficacy or biomarker endpoints.

Tags & Modalities

Open Research Dataset#Zenodo#Open Dataset#Keywords: Nonlinear Dynamics; Statistical Signal Processing; Gaussian Processes; Speech Signal Modelling; Neurological Disorder Detection.

Bibliometrics, Peer-Review Status & Citation Export

Cross-referenced via Semantic Scholar, Europe PMC & bioRxiv

1. Citation Metrics & Context Breakdown

0
Total Citations
0
Influential Citations

Citation Context Breakdown

Citation intent breakdown (Supporting vs. Contrasting) is currently accumulating in Semantic Scholar for this record. Researchers reusing this resource should cite the primary DOI/URL using the standardized formats below.

2. Peer-Review Validation & Revision History

Verified Publication / Open Dataset Record

Metadata and license integrity verified against primary repository records.

3. Standardized Academic Citation & BibTeX Export

Selected Format (APA)
Algahtani, Faris & Sultan (2026). A Computational Framework for Early Neurological Disorder Screening Using Speech Signals and Embedded System. Zenodo (CERN Open Data). https://doi.org/10.5281/zenodo.23736466
BibTeX Entry (LaTeX / Reference Managers)
@misc{faris2026zeno,
  title = {A Computational Framework for Early Neurological Disorder Screening Using Speech Signals and Embedded System},
  author = {Algahtani, Faris and Sultan},
  year = {2026},
  journal = {Zenodo (CERN Open Data)},
  howpublished = {\url{https://zenodo.org/records/23736466}},
  doi = {10.5281/zenodo.23736466},
  note = {CNS Open Data: parkinson}
}

Related Parkinson's & Movement Research & Datasets

Explore All Datasets
Open DatasetOpenNeuro

OpenNeuro ds003505: Dopaminergic Striato-Cortical Circuit Connectivity in Parkinson’s Disease during Motor Execution

This open-access 3T fMRI dataset evaluates striato-cortical circuit connectivity across 72 Parkinsonian patients and controls under levodopa ON vs. OFF states. Complete with behavioral logs, it offers foundational data for modeling dopaminergic network dynamics in motor execution.

3/12/2026Read Analysis
Open DatasetDANDI Archive

Dandiset 000026: Subthalamic Nucleus Local Field Potentials (LFP) and Beta-Band Dynamics in Parkinson’s Patients

High-density intraoperative and chronically implanted deep brain stimulation (DBS) electrode recordings during motor resting and movement states from 34 patients with idiopathic PD.

4/18/2026Read Analysis
PreprintbioRxiv (Neuroscience)

Focal drug uncaging for the precise control of endogenous nicotinic receptors in behaving mice

Nicotinic acetylcholine receptors shape diverse brain functions, including reward, aversion, and pain, but dissecting their roles in vivo requires drug delivery with spatiotemporal precision that conventional pharmacology cannot provide. Here we establish in vivo photopharmacology of endogenous nico...

10/8/2026Read Analysis
PreprintmedRxiv (Neurology)

Peripheral immunoinflammatory markers and clinical correlations in Parkinson's disease patients carrying LRRK2 G2385R and R1628P variants

Peripheral inflammation in Parkinsons disease (PD) remains poorly characterised among carriers of Asian-prevalent LRRK2 G2385R and R1628P variants. We investigated plasma immunoinflammatory markers (i.e., IL-6, TNF-, CCL2, CX3CL1, CCL5, and VCAM-1) via multiplex immunoassay in 240 participants: PD-G...

9/22/2026Read Analysis
PreprintmedRxiv (Neurology)

Continuous High-Frequency Smartwatch Sensor Telemetry Predicts Parkinson’s Motor Fluctuation Subtypes

A 24-month longitudinal cohort of 650 Parkinson’s patients monitored with wrist-worn IMU accelerometer arrays establishes automated machine learning scores correlating with MDS-UPDRS Part III subscores.

10/31/2026Read Analysis
PreprintbioRxiv (Neuroscience)

Pharmacological Inhibition of mTORC1 Reduces Neural Death and Damage Volume After MCAO by Modulating Microglial Reactivity

Preclinical evaluation of novel mTORC1 inhibitors in neurodegenerative models demonstrating reduced neuroinflammation.

10/30/2026Read Analysis

Active Clinical Trials & Pipeline in Parkinson's & Movement

View Clinical Pipeline
MJFF-PPMI-41MJFF

Five-Year Disease Progression in Synuclein Seeding Positive Sporadic Parkinson's Disease.

The Michael J. Fox Foundation
MJFF-PPMI-41MJFF

Increased Serum Neurofilament Light Chain Levels in Parkinson's Disease Patients Carrying the p.A53T SNCA Mutation: Data from the Parkinson's Progression Markers Initiative Study.

The Michael J. Fox Foundation
MJFF-PPMI-40MJFF

Safety and Feasibility of Serial Lumbar Punctures: Long-term Results from the Parkinson's Progression Markers Initiative.

The Michael J. Fox Foundation

Related Data & Resources

Open Datasets

Explore Related Datasets

Find neuroimaging or multi-omics datasets relevant to this topic.

Clinical Trials

View Clinical Pipeline

Check investigational drugs, clinical trials, and clinical guidelines.

Academic Research & Medical Information Disclaimer

This page provides structured scientific metadata, methodological critiques, and open-data reusability guidelines intended strictly for neuroscience researchers and data scientists. It does not constitute medical advice, clinical diagnosis, or treatment recommendations.

Was this resource helpful?

Help improve data curation by sharing your feedback.

Open SourceDownload Data