Epileptic seizure detection using micro sensor

Tonpe, Snehal V.; Adhav, Yashwant G.; Joshi, Atul

doi:10.1109/iccsp.2017.8286441

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…Whilst Ribeiro et al (2016) [33] used the wearable device from ACM and embedded sensors by applying machine learning algorithms obtained KNN 99% and C4.5 & PART 98% and there was no valuable variation at the results between KNN, PART, and C4.5… An experiment showed that the user of wearable accelerometer sensor was found very efficiently with a limited number of false alarms (Tonpe et al, 2017) [34]. Also Kusmakar et al (2017) [35] used wearable ACM sensors and their results showed that the sensitivity was 23% with 0:72=24h.…”

Section: Researches Based On Acmmentioning

confidence: 99%

Wearable Detection Systems for Epileptic Seizure: A review

Alwindawi

Uçan

Morad³

2020

alkej

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The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head. Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal. The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple body signals, new algorithm methods, and detection devices that are commercially available. As a result, the reviewing process shows that there are many research articles that have covered wearable seizure detection systems that based on body signals. The more effective monitoring and detection seizure system is the system that uses multi-body signals, is highly comfortable and has low power consumption.

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Section: Researches Based On Acmmentioning

confidence: 99%

Wearable Detection Systems for Epileptic Seizure: A review

Alwindawi

Uçan

Morad³

2020

alkej

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“…This technique is used a wearable tracking tool which consisted of an accelerometer and a microcontroller. The accelerometer detected movement even as the microcontroller anticipated the seizure and if a seizure prevalence changed into showed then the microcontroller brought on an audio-video alarm [40]. QiYuan et al, (2017) proposed a unique technique predicated on the weighted ELM for seizure detection.…”

Section: Review Of Classification and Similarity Measure Based Approachesmentioning

confidence: 99%

Detection and Classification Methods for EEG Epileptic Seizures

Panda¹

2019

IJATCSE

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Epilepsy is the maximum common brain disease which has been spreading largely around the arena. It takes place because of excessive or synchronous strange activities in human brain. To degree the electric seizure pastime of mind many technology and techniques had been developed. Nearly 80% of people with epilepsy stay in low-and center-earnings countries. It is estimated that as much as 70% of people residing with epilepsy should stay seizure-free if well diagnosed and handled. The chance of premature demise in humans with epilepsy becomes three times more than for the overall population. Three quarters of people with epilepsy living in low-profits nations do now not get the remedy they want. In many parts of the arena, human beings with epilepsy be afflicted by stigma and discrimination. Epilepsy is characterized by means of surprising bursts of extra energy in the mind, manifesting as recurrent seizures. Epilepsy continues to be now not properly understood whilst compared with other neurological disorders. This paper provides an overview of detection and classification era for the reason of EEG seizure. Time frequency transforms and system learning plays an important function in extracting meaningful facts. The overall performance of detection and classification techniques of the researchers is the primary focus of the paper.

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Epileptic seizure detection using micro sensor

Cited by 2 publications

References 7 publications

Wearable Detection Systems for Epileptic Seizure: A review

Wearable Detection Systems for Epileptic Seizure: A review

Detection and Classification Methods for EEG Epileptic Seizures

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