2006
DOI: 10.1590/s0004-282x2006000600004
|View full text |Cite
|
Sign up to set email alerts
|

Residual signal auto-correlation to evaluate speech in Parkinson’s disease patients

Abstract: -Objective: To evaluate the maximum residual signal auto-correlation also known as pitch amplitude (PA) values in patients with Parkinson's disease (PD) patients. Method: The signals of 21 Parkinson's patients were compared with 15 healthy individuals, divided according age and gender. Results:S t a t i s t i c a l d i ff e rence was seen between groups for PA, 0.39 for controls and 0.25 for PD. Normal value threshold was set as 0.3; (p<0.001). In the Parkinson's group 80.77%, and in the control group only 12.… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
5
0

Year Published

2016
2016
2021
2021

Publication Types

Select...
2
2
1

Relationship

0
5

Authors

Journals

citations
Cited by 8 publications
(5 citation statements)
references
References 14 publications
0
5
0
Order By: Relevance
“…Studies have shown that PD can be detected in its incipient phase [8]. Statistical techniques were used to evaluate the residual signal auto-correlation in Parkinson's disease patients and significant differences in pitches amplitude between patients and the healthy group was identified [9].…”
Section: Related Workmentioning
confidence: 99%
“…Studies have shown that PD can be detected in its incipient phase [8]. Statistical techniques were used to evaluate the residual signal auto-correlation in Parkinson's disease patients and significant differences in pitches amplitude between patients and the healthy group was identified [9].…”
Section: Related Workmentioning
confidence: 99%
“…where d is the displacement of the sample points used to compute the radius difference. 5 The following three features are computed based on the relative tremor r r…”
Section: Feature Extractionmentioning
confidence: 99%
“…Expert systems based on machine learning techniques have been employed to this purpose, showing promising results [3]. Generally, these works are signal analysis-oriented, which means one can use the patient's voice to assess the level of the illness [4,5], since the voice capability is gradually compromised by PD. Little et al [4], for instance, presented a dataset composed of biomedical voice measurements from 31 male and female subjects, of which 23 patients were diagnosed with PD and 8 were healthy subjects.…”
Section: Introductionmentioning
confidence: 99%
“…However, most of the previous works considered signal analysis from patient's voice [17,23] as PD causes voice disorder. Few of the studies were based on MRI images [20,21].…”
Section: Literature Reviewmentioning
confidence: 99%