Evidence map›Paper›PMID 31161372›Full record

ArticleJournal of medical systems2019

Diagnosis of Delusion and Hallucination from Schizophrenia Patient Using RADWT.

K Tamilarasi, A Jawahar, G Senthilkumar, N R Shanker

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2019. 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

4 authors.

K TamilarasiRajalakshmi Engineering College, Rajalakshmi Nagar, Thandalam, Chennai, India. tamilarasi.k@rajalakshmi.edu.in.
A JawaharSSN College of Engineering, Old Mahabalipuram Road, Kalavakkam, Tamilnadu, India.
G SenthilkumarPanimalar Engineering College, Chennai, India.
N R ShankerAalim Muhammed Salegh College of Engineering, I.A.F, Avadi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, early detection of schizophrenia types such as hallucination and delusion propose through the high Q-factor of RADWT in EEG signal acquired during the cognitive task of the patient. The earlier diagnose obtains from the energy distribution of the EEG signal in the high resolution via optimum tuning in dilation factor,which influences the Q-factor, redundancy and ringing in the EEG signal. The early detection of type of schizophrenia prevents the illness progression and lifelong disease. In existing clinical trial, the psych clinician diagnose only the schizophrenia disease through the standard DSM screening question and Prodromal signs checklist according to the standard of American Psychiatric Association. Furthermore, clinician tries to diagnose the disease through brain imaging and EEG signal. However, procedure in the diagnosis of Schizophrenia possible only in the acute stage, minimum after 2 years of illness progression and still sub classification of the type of schizophrenia is a challenging task. In the proposed system, we acquire EEG signal during the three conditions such as reverse counting of the number, screening questions (DSM), and eye rest state with a distance of 1-m part of the clinician and patient to analyse cognitive behaviour. From the result of 25 patients EEG, signal during cognitive task show the different sub band energy pattern in RADWT to distinguish hallucination and delusion patient exactly for 21 patients and provide 84% of accuracy in sub-classification of type schizophrenia.

Indexed as

SchizophreniaAlgorithmsDelusionsHallucinationsHumansPattern Recognition, AutomatedThyroid GlandUltrasonographyECGHallucinationRADWTSchizophrenia

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.