Evidence map›Paper›PMID 39796823›Full record

ArticleSensors (Basel, Switzerland)2024

A Novel Real-Time Threshold Algorithm for Closed-Loop Epilepsy Detection and Stimulation System.

Liang-Hung Wang, Zhen-Nan Zhang, Chao-Xin Xie, Hao Jiang, Tao Yang, Qi-Peng Ran, Ming-Hui Fan, I-Chun Kuo, Zne-Jung Lee, Jian-Bo Chen and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

13 authors.

Liang-Hung WangThe Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.ORCID 0000-0002-2115-8902
Zhen-Nan ZhangThe Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.
Chao-Xin XieThe Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.ORCID 0009-0001-8734-6439
Hao JiangThe Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.
Tao YangThe Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.
Qi-Peng RanThe Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.
Ming-Hui FanThe Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.
I-Chun KuoCollege of Biological Science and Engineering, Fuzhou University, Fuzhou 350108, China.
Zne-Jung LeeSchool of Advanced Manufacturing, Fuzhou University, Quanzhou 362200, China.ORCID 0000-0002-8791-9276
Jian-Bo ChenDepartment of Information and Telecommunications Engineering, Ming Chuan University, Taoyuan 32023, Taiwan.ORCID 0000-0002-3096-9395
Tsung-Yi ChenDepartment of Electronic Engineering, Feng Chia University, Taichung 40724, Taiwan.
Shih-Lun ChenThe Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan.ORCID 0000-0002-4079-9350
Patricia Angela R AbuThe Department of Information Systems and Computer Science, Ateneo de Manila University, Quezon City 1108, Philippines.ORCID 0000-0002-8848-6644

Funding

National Natural Science Foundation of China 61971140
6 · The paper itself

Abstract

Epilepsy, as a common brain disease, causes great pain and stress to patients around the world. At present, the main treatment methods are drug, surgical, and electrical stimulation therapies. Electrical stimulation has recently emerged as an alternative treatment for reducing symptomatic seizures. This study proposes a novel closed-loop epilepsy detection system and stimulation control chip. A time-domain detection algorithm based on amplitude, slope, line length, and signal energy characteristics is introduced. A new threshold calculation method is proposed; that is, the threshold is updated by means of the mean and standard deviation of four consecutive eigenvalues through parameter combination. Once a seizure is detected, the system begins to control the stimulation of a two-phase pulse current with an amplitude and frequency of 34 μA and 200 Hz, respectively. The system is physically designed on the basis of the UMC 55 nm process and verified by a field programmable gate array verification board. This research is conducted through innovative algorithms to reduce power consumption and the area of the circuit. It can maintain a high accuracy of more than 90% and perform seizure detection every 64 ms. It is expected to provide a new treatment for patients with epilepsy.

Indexed as

AlgorithmsElectric Stimulation TherapyEpilepsyElectric StimulationElectroencephalographyHumansSeizuresSignal Processing, Computer-AssistedASICclosed loopelectrical stimulationepilepsy detectionfeature extraction

Identifiers

PMID39796823
PMCPMC11723055

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.