Detection of Focal Epileptic Seizure Using NIRS Signal Based on Discrete Wavelet Transform

Modir, Aslan; Khalilzadeh, Mohammad A.; Gorji, Ali

doi:10.15171/icnj.2017.03

Cited by 3 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…PPG amplitude decreases when arterial BP considerably increases because of increase in sympathetic tone [33]. Modir [16] used HR, DT, CT, area time, and amplitude features from PPG morphology to detect seizure. All the features extracted were evaluated using t-test for the determination of the significant difference between the features with seizure condition.…”

Section: Photoplethysmogram Waveformmentioning

confidence: 99%

“…This research also need to scale the parameters with respect to HR, although the variation in PW parameters cannot be fully explained by HR. PPG signal can be used in detecting or predicting epileptic attack, and information on epilepsy is available in the dynamic of this signal [16]. The contrast of using photodiode and receiver was to ensure that sensitivity towards ambient light was minimal as possible for the receiver to maximally receive light from the photodiode.…”

Section: Photoplethysmogram Waveformmentioning

confidence: 99%

See 1 more Smart Citation

Methods of Extracting Feature from Photoplethysmogram Waveform for Non-Invasive Diagnostic Applications

Hafifah

Nayan

2020

Int. J. Onl. Eng.

View full text Add to dashboard Cite

<p>This paper presents a bibliographical survey of recently-published research on different techniques to extract feature from photoplethysmogram (PPG). These techniques and approaches have been implemented for better accuracy in detecting diseases. Moreover, several aspects in analyzing PPG waveform are discussed on the techniques in feature extraction, parameters involved and performance comparisons. This review will serve as a comparative study and reference for researches working on PPG waveform in health care applications.</p>

show abstract

Section: Photoplethysmogram Waveformmentioning

confidence: 99%

Section: Photoplethysmogram Waveformmentioning

confidence: 99%