Quantitative movement analysis differentiates focal seizures characterized by automatisms

Rémi, Jan; Cunha, João Paulo Silva; Vollmar, Christian; Topçuoğlu, Özgür Bilgin; Meier, A; Ulowetz, S.; Beleza, Pedro; Noachtar, Soheyl

doi:10.1016/j.yebeh.2011.01.020

Cited by 28 publications

(37 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Seizure types that can be captured by video include focal, hypermotor, myoclonic, and clonic [93][94][95]98]. Myoclonic seizures are detected with good sensitivity and specificity with a marker-based system based on spatio-temporal interest points [95].…”

Section: Video Detection Systemsmentioning

confidence: 99%

See 1 more Smart Citation

Automated seizure detection systems and their effectiveness for each type of seizure

Ulate‐Campos

Coughlin

Gaínza‐Lein

et al. 2016

Seizure

189

166

View full text Add to dashboard Cite

Epilepsy affects almost 1% of the population and most of the approximately 20-30% of patients with refractory epilepsy have one or more seizures per month. Seizure detection devices allow an objective assessment of seizure frequency and a treatment tailored to the individual patient. A rapid recognition and treatment of seizures through closed-loop systems could potentially decrease morbidity and mortality in epilepsy. However, no single detection device can detect all seizure types. Therefore, the choice of a seizure detection device should consider the patient-specific seizure semiologies. This review of the literature evaluates seizure detection devices and their effectiveness for different seizure types. Our aim is to summarize current evidence, offer suggestions on how to select the most suitable seizure detection device for each patient and provide guidance to physicians, families and researchers when choosing or designing seizure detection devices. Further, this review will guide future prospective validation studies.

show abstract

Section: Video Detection Systemsmentioning

confidence: 99%

“…For clonic seizures there are some studies with ACM and video detection [96]. For hypermotor seizures ACM, sEMG, and video have demonstrated good detection rates [38, 86,98]. For myoclonic seizures ACM and video had good detection rates [85,95].…”

Section: Page 24 Of 48mentioning

confidence: 99%

Automated seizure detection systems and their effectiveness for each type of seizure

Ulate‐Campos

Coughlin

Gaínza‐Lein

et al. 2016

Seizure

189

166

View full text Add to dashboard Cite

show abstract

“…We did not consider seizure reporting from vagus nerve [17] or brain stimulation [59] or systems that require permanent surgeries or EEG systems that can be burdensome for patients during longterm use [11,16]. In addition we only reviewed systems that published sufficient statistics for comparing precision and recall [10,43,54].…”

Section: Evaluating Supporting Technologiesmentioning

confidence: 99%

Seizure reporting technologies for epilepsy treatment: A review of clinical information needs and supporting technologies

Bidwell

Khuwatsamrit

Askew

et al. 2015

Seizure

View full text Add to dashboard Cite

This review surveys current seizure detection and classification technologies as they relate to aiding clinical decision-making during epilepsy treatment. Interviews and data collected from neurologists and a literature review highlighted a strong need for better distinguishing between patients exhibiting generalized and partial seizure types as well as achieving more accurate seizure counts. This information is critical for enabling neurologists to select the correct class of antiepileptic drugs (AED) for their patients and evaluating AED efficiency during long-term treatment. In our questionnaire, 100% of neurologists reported they would like to have video from patients prior to selecting an AED during an initial consultation. Presently, only 30% have access to video. In our technology review we identified that only a subset of available technologies surpassed patient self-reporting performance due to high false positive rates. Inertial seizure detection devices coupled with video capture for recording seizures at night could stand to address collecting seizure counts that are more accurate than current patient self-reporting during day and night time use.

show abstract

“…In addition, large amounts of data can be collected based on videoEEG measurements. Auto mated motion tracking of short video clips from ictal videoEEG showed more than 90% of sensitivity and specificity for focal motor seizure 18,19) . However, during daily activity, the patient may be invisible, as when he or she is under a blanket.…”

Section: ) Videomentioning

confidence: 99%

Non-EEG Seizure Detection Using Wearable Device

노병호¹

2017

journalofthekoreanchildneurologysociety

View full text Add to dashboard Cite

Electroencephalography (EEG) is the gold standard for seizure detection. However, EEG systems are usually expensive and require well-trained technicians for data acquisition. Detection of seizures is important in patients with refractory epilepsy, especially when the seizure is prolonged and unwitnessed. Sudden unexpected death in epilepsy (SUDEP) is an important problem in patients with refractory epile psy be cause the risk of SUDEP decreases the quality of life. There are several alterna tives to EEG systems that are used to detect seizure-related pathophysiological changes. Measurements of heart rate and heart rate variability can be used to detect seizurerelated cardiologic phenomena. Respiratory signals obtained based on respiration rate and respiratory chest and abdominal movements may also be used for seizure detection. Ictal movements can be detected using video analysis or wearable devices, such as accelerometers and gyroscopes. In addition, electrodermal activity (EDA) measurements are currently under investigation as a way to alert others to an ictal period. Although these technologies have limitations, they are affordable and easily wearable. They are thus appropriate for use in patients during daily activity. These devices may be potentially useful to detect the occurrence of unwitnessed seizures, and to increase the quality of life.

show abstract

Quantitative movement analysis differentiates focal seizures characterized by automatisms

Cited by 28 publications

References 22 publications

Automated seizure detection systems and their effectiveness for each type of seizure

Automated seizure detection systems and their effectiveness for each type of seizure

Seizure reporting technologies for epilepsy treatment: A review of clinical information needs and supporting technologies

Non-EEG Seizure Detection Using Wearable Device

Contact Info

Product

Resources

About