Characteristics of motion signal profiles of tonic-clonic, tonic, hyperkinetic, and motor seizures extracted from nocturnal video recordings.

IF 1.9 4区 医学 Q3 CLINICAL NEUROLOGY
Petri Ojanen, Csaba Kertész, Jukka Peltola
{"title":"Characteristics of motion signal profiles of tonic-clonic, tonic, hyperkinetic, and motor seizures extracted from nocturnal video recordings.","authors":"Petri Ojanen, Csaba Kertész, Jukka Peltola","doi":"10.1002/epd2.20284","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>In this study, characteristics of signal profiles formed by motion, oscillation, and sound signals were analyzed to evaluate generalizability and variability in a single patient setting (intra-patient variability) and between patients (inter-patient variability). As a secondary objective, the effect of brivaracetam intervention on signal profiles was explored.</p><p><strong>Methods: </strong>Patient data included 13 hyperkinetic seizures, 65 tonic seizures, 13 tonic-clonic seizures, and 138 motor seizures from 11 patients. All patients underwent an 8-week monitoring, and after a 3-week baseline, brivaracetam was initiated. Motion, oscillation, and sound features extracted from the video were used to form signal profiles. Variance of signals was calculated, and combined median and quartile visualizations were used to visualize the results. Similarly, the effect of intervention was visualized.</p><p><strong>Results: </strong>Hyperkinetic motion signals showed a rapid increase in motion and sound signals without oscillations and achieved low intra-patient variance. Tonic component created a recognizable peak in motion signal typical for tonic and tonic-clonic seizures. For tonic seizures, inter-patient variance was low. Motor signal profiles were varying, and they did not form a generalizable signal profile. Visually recognizable changes were observed in the signal profiles of two patients.</p><p><strong>Significance: </strong>Video-based motion signal analysis enabled the extraction of motion features characteristic for different motor seizure types which might be useful in further development of this system. Tonic component formed a recognizable seizure signature in the motion signal. Hyperkinetic and motor seizures may have not only significantly different motion signal amplitude but also overlapping signal profile characteristics which might hamper their automatic differentiation. Motion signals might be useful in the assessment of movement intensity changes to evaluate the treatment effect. Further research is needed to test generalizability and to increase reliability of the results.</p>","PeriodicalId":50508,"journal":{"name":"Epileptic Disorders","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epileptic Disorders","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/epd2.20284","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: In this study, characteristics of signal profiles formed by motion, oscillation, and sound signals were analyzed to evaluate generalizability and variability in a single patient setting (intra-patient variability) and between patients (inter-patient variability). As a secondary objective, the effect of brivaracetam intervention on signal profiles was explored.

Methods: Patient data included 13 hyperkinetic seizures, 65 tonic seizures, 13 tonic-clonic seizures, and 138 motor seizures from 11 patients. All patients underwent an 8-week monitoring, and after a 3-week baseline, brivaracetam was initiated. Motion, oscillation, and sound features extracted from the video were used to form signal profiles. Variance of signals was calculated, and combined median and quartile visualizations were used to visualize the results. Similarly, the effect of intervention was visualized.

Results: Hyperkinetic motion signals showed a rapid increase in motion and sound signals without oscillations and achieved low intra-patient variance. Tonic component created a recognizable peak in motion signal typical for tonic and tonic-clonic seizures. For tonic seizures, inter-patient variance was low. Motor signal profiles were varying, and they did not form a generalizable signal profile. Visually recognizable changes were observed in the signal profiles of two patients.

Significance: Video-based motion signal analysis enabled the extraction of motion features characteristic for different motor seizure types which might be useful in further development of this system. Tonic component formed a recognizable seizure signature in the motion signal. Hyperkinetic and motor seizures may have not only significantly different motion signal amplitude but also overlapping signal profile characteristics which might hamper their automatic differentiation. Motion signals might be useful in the assessment of movement intensity changes to evaluate the treatment effect. Further research is needed to test generalizability and to increase reliability of the results.

从夜间视频记录中提取的强直阵挛、强直、过度运动和运动性癫痫发作的运动信号特征。
研究目的本研究分析了由运动、振荡和声音信号形成的信号轮廓特征,以评估在单个患者环境下(患者内变异性)和患者之间(患者间变异性)的普遍性和变异性。作为次要目标,还探讨了利伐沙坦干预对信号曲线的影响:患者数据包括 11 名患者的 13 次过度运动性发作、65 次强直性发作、13 次强直阵挛发作和 138 次运动性发作。所有患者均接受了为期 8 周的监测,并在 3 周基线后开始服用溴伐他汀。从视频中提取的运动、振荡和声音特征被用于形成信号曲线。计算信号的方差,并使用综合中位数和四分位数可视化方法将结果可视化。同样,还对干预效果进行了可视化:结果:过度运动信号显示运动和声音信号迅速增加,没有振荡,患者内部方差较小。强直成分在强直和强直-阵挛发作时会产生一个可识别的典型运动信号峰值。对于强直性发作,患者之间的差异较小。运动信号轮廓各不相同,没有形成一个普遍的信号轮廓。在两名患者的信号轮廓中观察到了视觉上可识别的变化:意义:基于视频的运动信号分析能够提取出不同运动性癫痫发作类型的运动特征,这可能有助于该系统的进一步开发。强直成分在运动信号中形成了可识别的癫痫发作特征。过度运动性癫痫发作和运动性癫痫发作不仅运动信号振幅明显不同,而且信号轮廓特征也有重叠,这可能会妨碍它们的自动区分。运动信号可能有助于评估运动强度的变化,从而评价治疗效果。还需要进一步的研究来检验其通用性并提高结果的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Epileptic Disorders
Epileptic Disorders 医学-临床神经学
CiteScore
4.10
自引率
8.70%
发文量
138
审稿时长
6-12 weeks
期刊介绍: Epileptic Disorders is the leading forum where all experts and medical studentswho wish to improve their understanding of epilepsy and related disorders can share practical experiences surrounding diagnosis and care, natural history, and management of seizures. Epileptic Disorders is the official E-journal of the International League Against Epilepsy for educational communication. As the journal celebrates its 20th anniversary, it will now be available only as an online version. Its mission is to create educational links between epileptologists and other health professionals in clinical practice and scientists or physicians in research-based institutions. This change is accompanied by an increase in the number of issues per year, from 4 to 6, to ensure regular diffusion of recently published material (high quality Review and Seminar in Epileptology papers; Original Research articles or Case reports of educational value; MultiMedia Teaching Material), to serve the global medical community that cares for those affected by epilepsy.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信