Non-linear prediction for oesophageal voice analysis.

Med Eng Phys

Department of Information Engineering, University of Pisa, Via Diotisalvi 2, 56126 Pisa, Italy.

Published: December 2002

Herein, non-linear prediction methods are applied to oesophageal voice analysis. The research aims to investigate normal and pathological subjects, in order to improve knowledge of the oesophageal voice behaviour. Analysis is performed in the reconstructed phase space, using both non-linear prediction with local linear approximation and the S-Map method. Preliminary results seem to confirm that in normal subjects a non-linear stable deterministic behaviour takes place, while in pathological subjects the non-linear contribution reduces while the time series becomes unstable.

Download full-text PDF

Source
http://dx.doi.org/10.1016/s1350-4533(02)00063-2DOI Listing

Publication Analysis

Top Keywords

non-linear prediction
12
oesophageal voice
12
voice analysis
8
pathological subjects
8
subjects non-linear
8
non-linear
5
prediction oesophageal
4
analysis non-linear
4
prediction methods
4
methods applied
4

Similar Publications

Diminished salivary cortisol response to mental stress predict all-cause mortality in general population.

J Psychosom Res

December 2024

The Second Clinical Medical College, Jinan University, Shenzhen 518020, China; Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, China; School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China. Electronic address:

Objectives: To characterize individuals with a diminished salivary cortisol response to mental stress, assess its association with all-cause mortality, and quantify the mediating effects of the most relevant and modifiable factors to identify potential target for prevention.

Methods: Data from MIDUS II study with a 16-year follow-up, were used to categorize 1129 participants as responders or non-responders based on the existence of increase in salivary cortisol under mental stress. LASSO-logistics analysis identified the most relevant factors.

View Article and Find Full Text PDF

BioBERT based text mining for incorporating prior knowledge in the inference of genetic network models.

Comput Biol Med

January 2025

Health Innovation and Transformation Centre, Federation University, Victoria, 3842, Australia; BioThink, Queensland, 4020, Australia.

Reconstruction of Gene Regulatory Networks (GRNs) is essential for understanding gene interactions, their impact on cellular processes, and manifestation of diseases, including drug discovery. Among various mathematical and dynamic models used for GRN reconstruction, S-system model, comprising non-linear differential equations, is widely utilised to capture the behaviour of complex biological systems with non-linear and time-dependent interactions. However, as the network size increases, computational demand for network inference grows due to a greater number of estimation parameters, significantly impacting the performance of optimisation algorithms.

View Article and Find Full Text PDF

Background: Despite significant advancements in the development of blood biomarkers for AD, challenges persist due to the complex interplay of genetic and environmental risk factors in AD pathogenesis. Epigenetic processes, including non-coding RNAs and especially microRNAs (miRs), have emerged as important players in the molecular mechanisms underlying neurodegenerative diseases. MiRs have the ability to fine-tune gene expression and proteostasis, and microRNAome profiling in liquid biopsies is gaining increasing interest since changes in miR levels can indicate the presence of multiple pathologies.

View Article and Find Full Text PDF

Basic Science and Pathogenesis.

Alzheimers Dement

December 2024

The Jackson Laboratory, Bar Harbor, ME, USA.

Background: The genetic etiology of late-onset Alzheimer's disease (LOAD) is complex, with over 75 identified loci contributing to disease risk. Recent efforts of the MODEL-AD consortia have yielded several dozen mouse strains harboring variation designed to model LOAD risk alleles. Given the complex genetic architecture of LOAD, developing animal models that combine multiple risk alleles is likely essential to improving the fidelity of these models to human disease.

View Article and Find Full Text PDF

Background: Biomarker cutpoints have received significant importance in AD research. Reliable worsening method based on serial biomarker data has been proposed (Jack et al., 2017 Alz & Dem).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!