Exploring the capability of wireless near infrared spectroscopy as a portable seizure detection device for epilepsy patients

Jeppesen, Jesper; Beniczky, Sándor; Johansen, Peter; Sidenius, Per; Fuglsang-Frederiksen, Anders

doi:10.1016/j.seizure.2015.01.015

Cited by 45 publications

(48 citation statements)

References 21 publications

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“…The authors revealed that frontal generalized spike and wave discharges were associated with moderate oxygenation ten seconds before the discharge, followed by a strong deoxygenation, then a second increase in oxygenation, and a return to baseline [118]. In another study, the hemodynamic changes in the frontal lobe during seizures were only slightly higher than during non-seizure activities [119].…”

Section: Page 18 Of 48mentioning

confidence: 94%

“…The spectrophotometer, typically placed on the forehead [117][118][119], emits light into the tissue from the surface of the scalp, and then collects it from a detector close to the emitter [118].…”

Section: Page 18 Of 48mentioning

confidence: 99%

“…Seizures analyzed with this approach are mainly focal, including focal dyscognitive, focal without impairment of consciousness, and focal with secondary generalization, but also absence seizures [117,119]. One study in temporal lobe seizures found an increase in rSO2 in the preictal period, followed by a decline around seizure onset, and then a postictal increase [117].…”

Section: Page 18 Of 48mentioning

confidence: 99%

“…One of the disadvantages of this system is that the sensor pad might be difficult to wear from a cosmetic point of view, since it must be surrounded by a black cloth so that no external light interferes with the NIRS signal [119]. In addition, one of its biggest challenges is developing a generic algorithm, since there is a huge diversity in hemodynamic changes amongst patients [119].…”

Section: Page 18 Of 48mentioning

confidence: 99%

“…In addition, one of its biggest challenges is developing a generic algorithm, since there is a huge diversity in hemodynamic changes amongst patients [119]. The findings suggest that NIRS might be a noninvasive detection system, at least for focal seizures, with a patient specific algorithm [117].…”

Section: Page 18 Of 48mentioning

confidence: 99%

See 4 more Smart Citations

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

Ulate‐Campos

Coughlin

Gaínza‐Lein

et al. 2016

Seizure

195

166

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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.

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Section: Page 18 Of 48mentioning

confidence: 94%

Section: Page 18 Of 48mentioning

confidence: 99%

Section: Page 18 Of 48mentioning

confidence: 99%

Section: Page 18 Of 48mentioning

confidence: 99%

Section: Page 18 Of 48mentioning

confidence: 99%

See 3 more Smart Citations

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

Ulate‐Campos

Coughlin

Gaínza‐Lein

et al. 2016

Seizure

195

166

View full text Add to dashboard Cite

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Optimal sub‐harmonic injection‐locked MICS band transmitter for wireless CW‐fNIRS systems

Borjkhani

Setarehdan

Sheikhaei

2021

Circuit Theory & Apps

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Portable and wireless functional near-infrared spectroscopy is a growing field of research for real-time monitoring of brain functions. The most critical challenges in this field are the use of low-power and calibrated circuits. A novel transmitter architecture is proposed to overcome these barriers. This transmitter is low power, capable of being calibrated against process variation, and has a better phase noise and spurious-free dynamic range (SFDR) at the antenna. Besides that, the transmitter can be calibrated, which is not seen in similar research. In this transmitter, injection locking and frequency calibration lead to having an optimal and low-power circuit. The circuit is capable of transmitting data with BFSK and OOK modulations in the frequency band of the medical implant communication service (MICS). The transmitter is designed and simulated in a typical CMOS 0.18-μm technology with a 1-V power supply. The transmitter's power consumption is around 146 and 123 μW, equal to 5.92 nJ/bit and 246-630 pJ/bit for BFSK and OOK modulations, respectively. The signal's phase noise at the antenna is almost À109 dBc/Hz at 1-MHz frequency offset.

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Detection of seizures with ictal tachycardia, using heart rate variability and patient adaptive logistic regression machine learning methods: A hospital‐based validation study

Jeppesen,

Lin,

Melo

et al. 2024

Epileptic Disorders

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ObjectiveAutomated seizure detection of focal epileptic seizures is needed for objective seizure quantification to optimize the treatment of patients with epilepsy. Heart rate variability (HRV)‐based seizure detection using patient‐adaptive threshold with logistic regression machine learning (LRML) methods has presented promising performance in a study with a Danish patient cohort. The objective of this study was to assess the generalizability of the novel LRML seizure detection algorithm by validating it in a dataset recorded from long‐term video‐EEG monitoring (LTM) in a Brazilian patient cohort.MethodsIctal and inter‐ictal ECG‐data epochs recorded during LTM were analyzed retrospectively. Thirty‐four patients had 107 seizures (79 focal, 28 generalized tonic–clonic [GTC] including focal‐to‐bilateral‐tonic–clonic seizures) eligible for analysis, with a total of 185.5 h recording. Because HRV‐based seizure detection is only suitable in patients with marked ictal autonomic change, patients with >50 beats/min change in heart rate during seizures were selected as responders. The patient‐adaptive LRML seizure detection algorithm was applied to all elected ECG data, and results were computed separately for responders and non‐responders.ResultsThe patient‐adaptive LRML seizure detection algorithm yielded a sensitivity of 84.8% (95% CI: 75.6–93.9) with a false alarm rate of .25/24 h in the responder group (22 patients, 59 seizures). Twenty‐five of the 26 GTC seizures were detected (96.2%), and 25 of the 33 focal seizures without bilateral convulsions were detected (75.8%).SignificanceThe study confirms in a new, independent external dataset the good performance of seizure detection from a previous study and suggests that the method is generalizable. This method seems useful for detecting both generalized and focal epileptic seizures. The algorithm can be embedded in a wearable seizure detection system to alert patients and caregivers of seizures and generate objective seizure counts helping to optimize the treatment of the patients.

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Exploring the capability of wireless near infrared spectroscopy as a portable seizure detection device for epilepsy patients

Abstract: NIRS did not seem to be a suitable technology for generic seizure detection given the device, settings, and methods used in this study. There are still several challenges to overcome before the NIRS-technology can be used as a home-monitoring seizure detection device.

Cited by 45 publications

References 21 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

Optimal sub‐harmonic injection‐locked MICS band transmitter for wireless CW‐fNIRS systems

Detection of seizures with ictal tachycardia, using heart rate variability and patient adaptive logistic regression machine learning methods: A hospital‐based validation study

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