Photoplethysmographic evaluation of generalized tonic-clonic seizures.
GTCS
PPG
autonomic
biosensor
epilepsy
seizure
Journal
Epilepsia
ISSN: 1528-1167
Titre abrégé: Epilepsia
Pays: United States
ID NLM: 2983306R
Informations de publication
Date de publication:
08 2020
08 2020
Historique:
received:
30
11
2019
revised:
02
06
2020
accepted:
05
06
2020
pubmed:
12
7
2020
medline:
23
1
2021
entrez:
12
7
2020
Statut:
ppublish
Résumé
Photoplethysmography (PPG) is an optical technique measuring variations of blood perfusion in peripheral tissues. We evaluated alterations in PPG signals in relationship to the occurrence of generalized tonic-clonic seizures (GTCSs) in patients with epilepsy to evaluate the feasibility of seizure detection. During electroencephalographic (EEG) long-term monitoring, patients wore portable wristband sensor(s) on their wrists or ankles recording PPG signals. We analyzed PPG signals during three time periods, which were defined with respect to seizures detected on EEG: (1) baseline (>30 minutes prior to seizure), (2) preseizure period, and (3) postseizure period. Furthermore, we selected five random control segments during seizure-free periods. PPG features, including frequency, amplitude, duration, slope, smoothness, and area under the curve, were automatically calculated. We used a linear mixed-effect model to evaluate changes in PPG features between different time periods in an attempt to identify signal changes that detect seizures. We prospectively enrolled 174 patients from the epilepsy monitoring unit at Boston Children's Hospital. Twenty-five GTCSs were recorded from 13 patients. Data from the first recorded GTCS of each patient were included in the analysis. We observed an increase in PPG frequency during pre- and postseizure periods that was higher than the changes during seizure-free periods (frequency increase: preseizure = 0.22 Hz, postseizure = 0.58 Hz vs changes during seizure-free period = 0.05 Hz). The PPG slope decreased significantly by 56.71 nW/s during preseizure periods compared to seizure-free periods. Additionally, the smoothness increased significantly by 0.22 nW/s during the postseizure period compared to seizure-free periods. Monitoring of PPG signals may assist in the detection of GTCSs in patients with epilepsy. PPG may serve as a promising biomarker for future seizure detection systems and may contribute to future seizure prediction systems.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1606-1616Subventions
Organisme : Epilepsy Research Fund
Pays : International
Informations de copyright
© 2020 International League Against Epilepsy.
Références
Murray WB, Foster PA. The peripheral pulse wave: information overlooked. J Clin Monit. 1996;12:365-77.
Zijlmans M, Flanagan D, Gotman J. Heart rate changes and ECG abnormalities during epileptic seizures: prevalence and definition of an objective clinical sign. Epilepsia. 2002;43:847-54.
Ulate-Campos A, Coughlin F, Gainza-Lein M, Fernandez IS, Pearl PL, Loddenkemper T. Automated seizure detection systems and their effectiveness for each type of seizure. Seizure. 2016;40:88-101.
Poh MZ, Loddenkemper T, Reinsberger C, et al. Autonomic changes with seizures correlate with postictal EEG suppression. Neurology. 2012;78:1868-76.
Tamilia E, Formica D, Scaini A, Taffoni F. An automated system for the analysis of newborns' oral-motor behavior. IEEE Trans Neural Syst Rehabil Eng. 2016;24:1294-303.
Tamilia E, Delafield J, Fiore S, Taffoni F. An automatized system for the assessment of nutritive sucking behavior in infants: a preliminary analysis on term neonates. Conf Proc IEEE Eng Med Biol Soc. 2014;2014:5752-5.
Balasubramanian S, Melendez-Calderon A, Burdet E. A robust and sensitive metric for quantifying movement smoothness. IEEE Trans Biomed Eng. 2012;59:2126-36.
Allen J. Photoplethysmography and its application in clinical physiological measurement. Physiol Meas. 2007;28:R1-39.
Devinsky O. Effects of seizures on autonomic and cardiovascular function. Epilepsy Curr. 2004;4:43-6.
Challoner AV, Ramsay CA. A photoelectric plethysmograph for the measurement of cutaneous blood flow. Phys Med Biol. 1974;19:317-28.
Jespersen LT, Pedersen OL. The quantitative aspect of photoplethysmography revised. Heart Vessels. 1986;2:186-90.
Cejnar M, Kobler H, Hunyor SN. Quantitative photoplethysmography: Lambert-Beer law or inverse function incorporating light scatter. J Biomed Eng. 1993;15:151-4.
Delamont RS, Walker MC. Pre-ictal autonomic changes. Epilepsy Res. 2011;97:267-72.
Jansen K, Varon C, Van Huffel S, Lagae L. Peri-ictal ECG changes in childhood epilepsy: implications for detection systems. Epilepsy Behav. 2013;29:72-6.
Arends J, Thijs RD, Gutter T, et al. Multimodal nocturnal seizure detection in a residential care setting: a long-term prospective trial. Neurology. 2018;9:e2010-9.
Mayer H, Benninger F, Urak L, Plattner B, Geldner J, Feucht M. EKG abnormalities in children and adolescents with symptomatic temporal lobe epilepsy. Neurology. 2004;63:324-8.
Schernthaner C, Lindinger G, Pötzelberger K, Zeiler K, Baumgartner C. Autonomic epilepsy-the influence of epileptic discharges on heart rate and rhythm. Wien Klin Wochenschr. 1999;111:392-401.
van Andel J, Ungureanu C, Aarts R, Leijten F, Arends J. Using photoplethysmography in heart rate monitoring of patients with epilepsy. Epilepsy Behav. 2015;45:142-5.
Vandecasteele K, De Cooman T, Gu Y, et al. Automated epileptic seizure detection based on wearable ECG and PPG in a hospital environment. Sensors (Basel). 2017;17:2338.
Nitzan M, Turivnenko S, Milston A, Babchenko A, Mahler Y. Low-frequency variability in the blood volume and in the blood volume pulse measured by photoplethysmography. J Biomed Opt. 1996;1:223-9.
Ansakorpi H, Korpelainen JT, Huikuri HV, Tolonen U, Myllyla VV, Isojarvi JI. Heart rate dynamics in refractory and well controlled temporal lobe epilepsy. J Neurol Neurosurg Psychiatry. 2002;72:26-30.
Tomson T, Ericson M, Ihrman C, Lindblad LE. Heart rate variability in patients with epilepsy. Epilepsy Res. 1998;30:77-83.
Thayer JF, Yamamoto SS, Brosschot JF. The relationship of autonomic imbalance, heart rate variability and cardiovascular disease risk factors. Int J Cardiol. 2010;141:122-31.
Lotufo PA, Valiengo L, Bensenor IM, Brunoni AR. A systematic review and meta-analysis of heart rate variability in epilepsy and antiepileptic drugs. Epilepsia. 2012;53:272-82.
Measuring respiration rate with multi-band plethysmography. 2017 [cited 2018 May 25]. Available from http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220170164884%22.PGNR.&OS=DN/20170164884&RS=DN/20170164884