Medical Devices for the Management of Patients with Epilepsy

Authors

  • João Carrola Costa Departamento de Neurociências Clínicas e Saúde Mental, Faculdade de Medicina da Universidade do Porto, Porto, Portugal https://orcid.org/0009-0004-5494-5605
  • Leonor Dias Departamento de Neurociências Clínicas e Saúde Mental, Faculdade de Medicina da Universidade do Porto, Porto, Portugal; Serviço de Neurologia, Centro Hospitalar Universitário São João, Porto, Portugal https://orcid.org/0000-0002-2763-9440
  • Marta Carvalho Departamento de Neurociências Clínicas e Saúde Mental, Faculdade de Medicina da Universidade do Porto, Porto, Portugal; Serviço de Neurologia, Centro Hospitalar Universitário São João, Porto, Portugal https://orcid.org/0000-0001-6972-9287

DOI:

https://doi.org/10.46531/sinapse/AR/230038/2024

Keywords:

Brain-Computer Interfaces, Epilepsy/diagnosis, Epilepsy/therapy, Machine Learning, Seizures/diagnosis, Wearable Electronic Devices

Abstract

The increasing number of medical devices developed and marketed towards management of patients with epilepsy reflects the growing interest in translating technological advances and knowledge about epilepsy into better healthcare for this population. The objective of this narrative literature review is to analyze the available options of medical devices for detecting, treating, and recording epileptic seizures, and their potential clinical application. The included articles were selected from the PubMed database using the query “(Epilepsy[MeSH Terms]) AND (SUDEP)) AND (Medical Device)) AND (English[Language])”. The detection of epileptic seizures is essential for early intervention and to optimize the therapy for each patient. In outpatient settings, this detection is further challenging due to their unpredictability. Traditionally electroencephalography is the direct detection method used in a hospital environment. Indirect methods, such as electrocardiogram, photoplethysmography, oximeter, electrodermal activity, accelerometer, and electromyography, have shown potential for detecting seizures in the outpatient setting. Several medical devices have been developed based on the mentioned methods, with the aim of providing patients with solutions they can use in their daily lives. Behind-the-ear EEG, wristbands, armbands and bed sensors are some of the designs available. Equipped with different features, these devices can answer the need for early seizure detection and improve patients’ and caregivers’ quality of life. There are also devices available for the treatment of epileptic seizures. Through neuromodulation techniques such as vagus nerve stimulation, deep brain stimulation, and responsive neurostimulation, these devices are presented as solutions for patients with refractory epilepsy not eligible for ressective surgery. Patients with epilepsy have several apps available online for proper recording of seizures. These apps help doctors optimize therapy based on clinical evolution. The wide range of devices available creates the opportunity to personalize the approach to patient’s specific needs. Understanding each device’s characteristics can help clinicians improve management of patients with epilepsy.

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References

Thijs RD, Surges R, O’Brien TJ, Sander JW. Epilepsy in adults. Lancet. 2019;393:689-701. doi: 10.1016/S0140-6736(18)32596-0.

Ryvlin P, Nashef L, Lhatoo SD, Bateman LM, Bird J, Bleasel A et al. Incidence and mechanisms of cardiorespiratory arrests in epilepsy monitoring units (MORTEMUS): a retrospective study. Lancet Neurol. 2013;12:966-77. doi: 10.1016/S1474-4422(13)70214-X.

Van Westrhenen A, de Lange WF, Hagebeuk EE, Lazeron RH, Thijs RD, Kars MC. Parental experiences and perspectives on the value of seizure detection while caring for a child with epilepsy: A qualitative study. Epilepsy Behav. 2021;124:108323. doi: 10.1016/j.yebeh.2021.108323.

Li W, Wang G, Lei X, Sheng D, Yu T, Wang G. Seizure detection based on wearable devices: A review of device, mechanism, and algorithm. Acta Neurol Scand. 2022;146:723-31. doi: 10.1111/ane.13716.

Rugg-Gunn F. The role of devices in managing risk. Epilepsy Behav. 2020;103:106456. doi: 10.1016/j.yebeh.2019.106456.

Sivathamboo S, Nhu D, Piccenna L, Yang A, Antonic-Baker A, Vishwanath S, et al. Preferences and User Experiences of Wearable Devices in Epilepsy: A Systematic Review and Mixed-Methods Synthesis. Neurology. 2022;99:e1380-92. doi: 10.1212/WNL.0000000000200794.

Patel UK, Anwar A, Saleem S, Malik P, Rasul B, Patel K, et al. Artificial intelligence as an emerging technology in the current care of neurological disorders. J Neurol. 2021;268:1623-42. doi: 10.1007/s00415-019-09518-3.

Bruno E, Simblett S, Lang A, Biondi A, Odoi C, Schulze-Bonhage A, et al. Wearable technology in epilepsy: The views of patients, caregivers, and healthcare professionals. Epilepsy Behav. 2018;85:141-9. doi: 10.1016/j.yebeh.2018.05.044.

Beniczky S, Wiebe S, Jeppesen J, Tatum WO, Brazdil M, Wang Y, et al. Automated seizure detection using wearable devices: A clinical practice guideline of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology. Epilepsia. 2021;62:632-46. doi: 10.1111/epi.16818.

van Westrhenen A, Wijnen BFM, Thijs RD. Parental preferences for seizure detection devices: A discrete choice experiment. Epilepsia. 2022;63:1152-63. doi: 10.1111/epi.17202.

Schulze-Bonhage A, Sales F, Wagner K, Teotonio R, Carius A, Schelle A, Ihle M. Views of patients with epilepsy on seizure prediction devices. Epilepsy Behav. 2010;18:388-96. doi: 10.1016/j.yebeh.2010.05.008.

Regalia G, Onorati F, Lai M, Caborni C, Picard RW. Multimodal wrist-worn devices for seizure detection and advancing research: Focus on the Empatica wristbands. Epilepsy Res. 2019;153:79-82. doi: 10.1016/j.eplepsyres.2019.02.007.

Weisdorf S, Gangstad SW, Duun-Henriksen J, Mosholt KSS, Kjær TW. High similarity between EEG from subcutaneous and proximate scalp electrodes in patients with temporal lobe epilepsy. J Neurophysiol. 2018;120:1451-60. doi: 10.1152/jn.00320.2018.

You S, Hwan Cho B, Shon YM, Seo DW, Kim IY. Semisupervised automatic seizure detection using personalized anomaly detecting variational autoencoder with behind-the-ear EEG. Comput Methods Programs Biomed. 2022;213:106542. doi: 10.1016/j.cmpb.2021.106542.

Leutmezer F, Schernthaner C, Lurger S, Pötzelberger K, Baumgartner C. Electrocardiographic changes at the onset of epileptic seizures. Epilepsia. 2003;44:348-54. doi: 10.1046/j.1528-1157.2003.34702.x.

Ong JS, Wong SN, Arulsamy A, Watterson JL, Shaikh MF. Medical Technology: A Systematic Review on Medical Devices Utilized for Epilepsy Prediction and Management. Curr Neuropharmacol. 2022;20:950-64. doi: 10.2174/1570159X19666211108153001.

Poh MZ, Loddenkemper T, Swenson NC, Goyal S, Madsen JR, Picard RW. Continuous monitoring of electrodermal activity during epileptic seizures using a wearable sensor. Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:4415-8. doi: 10.1109/IEMBS.2010.5625988.

Casanovas Ortega M, Bruno E, Richardson MP. Electrodermal activity response during seizures: A systematic review and meta-analysis. Epilepsy Behav. 2022;134:108864. doi: 10.1016/j.yebeh.2022.108864.

Van de Vel A, Cuppens K, Bonroy B, Milosevic M, Jansen K, Van Huffel S, et al. Non-EEG seizure detection systems and potential SUDEP prevention: State of the art: Review and update. Seizure. 2016;41:141-53. doi: 10.1016/j.seizure.2016.07.012.

Zhao X, Lhatoo SD. Seizure detection: do current devices work? And when can they be useful? Curr Neurol Neurosci Rep. 2018;18:40. doi: 10.1007/s11910-018-0849-z.

J Jeppesen J, Beniczky S, Johansen P, Sidenius P, Fuglsang-Frederiksen A. Exploring the capability of wireless near infrared spectroscopy as a portable seizure detection device for epilepsy patients. Seizure. 2015;26:43-8. doi: 10.1016/j.seizure.2015.01.015. Erratum in: Seizure. 2015;29:174

Rodriguez-Villegas E, Chen G, Radcliffe J, Duncan J. A pilot study of a wearable apnoea detection device. BMJ Open. 2014;4:e005299. doi: 10.1136/bmjopen-2014-005299.

Lockman J, Fisher RS, Olson DM. Detection of seizure-like movements using a wrist accelerometer. Epilepsy Behav. 2011;20:638-41. doi: 10.1016/j.yebeh.2011.01.019.

Beniczky S, Conradsen I, Henning O, Fabricius M, Wolf P. Automated real-time detection of tonic-clonic seizures using a wearable EMG device. Neurology. 2018;90:e428-34. doi: 10.1212/WNL.0000000000004893.

Kjaer TW, Sorensen HB, Groenborg S, Pedersen CR, DuunHenriksen J. Detection of Paroxysms in Long-Term, Single-Channel EEG-Monitoring of Patients with Typical Absence Seizures. IEEE J Transl Eng Health Med. 2017;5:2000108. doi: 10.1109/JTEHM.2017.2649491.

Swinnen L, Chatzichristos C, Jansen K, Lagae L, Depondt C, Seynaeve L, et al. Accurate detection of typical absence seizures in adults and children using a two-channel electroencephalographic wearable behind the ears. Epilepsia. 2021;62:2741-52. doi: 10.1111/epi.17061.

Nasseri M, Nurse E, Glasstetter M, Böttcher S, Gregg NM, Laks Nandakumar A, et al. Signal quality and patient experience with wearable devices for epilepsy management. Epilepsia. 2020 Nov;61 Suppl 1:S25-S35. doi: 10.1111/epi.16527.

Brinkmann BH, Karoly PJ, Nurse ES, Dumanis SB, Nasseri M, Viana PF, et al. Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic. Front Neurol. 2021;12:690404. doi: 10.3389/fneur.2021.690404.

Beniczky S, Polster T, Kjaer TW, Hjalgrim H. Detection of generalized tonic-clonic seizures by a wireless wrist accelerometer: a prospective, multicenter study. Epilepsia. 2013;54:e58-61. doi: 10.1111/epi.12120.

Meritam P, Ryvlin P, Beniczky S. User-based evaluation of applicability and usability of a wearable accelerometer device for detecting bilateral tonic-clonic seizures: A field study. Epilepsia. 2018;59 Suppl 1:48-52. doi: 10.1111/epi.14051.

Halford JJ, Sperling MR, Nair DR, Dlugos DJ, Tatum WO, Harvey J, et al. Detection of generalized tonic-clonic seizures using surface electromyographic monitoring. Epilepsia. 2017;58:1861-9. doi: 10.1111/epi.13897.

Jeppesen J, Fuglsang-Frederiksen A, Johansen P, Christensen J, Wüstenhagen S, Tankisi H, Qerama E, Beniczky S. Seizure detection using heart rate variability: A prospective validation study. Epilepsia. 2020;61 Suppl 1:S41-S46. doi: 10.1111/epi.16511.

Jeppesen J, Beniczky S, Fuglsang Frederiksen A, Sidenius P, Johansen P. Modified automatic R-peak detection algorithm for patients with epilepsy using a portable electrocardiogram recorder. Annu Int Conf IEEE Eng Med Biol Soc. 2017;2017:4082-5. doi: 10.1109/EMBC.2017.8037753.

van Andel J, Thijs RD, de Weerd A, Arends J, Leijten F. Non-EEG based ambulatory seizure detection designed for home use: What is available and how will it influence epilepsy care? Epilepsy Behav. 2016;57:82-9. doi: 10.1016/j.yebeh.2016.01.003.

Narechania AP, Garic II, Sen-Gupta I, Macken MP, Gerard EE, Schuele SU. Assessment of a quasi-piezoelectric mattress monitor as a detection system for generalized convulsions. Epilepsy Behav. 2013;28:172-6. doi: 10.1016/j.yebeh.2013.04.017.

Arends J, Thijs RD, Gutter T, Ungureanu C, Cluitmans P, Van Dijk J, et al. Multimodal nocturnal seizure detection in a residential care setting: A long-term prospective trial. Neurology. 2018;91:e2010-9. doi: 10.1212/WNL.0000000000006545.

NightWatch. Seizure detection for nocturnal epilepsy. [accessed 2023 February 25, 2023]; Available from: https://nightwatchepilepsy.com/nightwatch/.

Sisterson ND, Wozny TA, Kokkinos V, Constantino A, Richardson RM. Closed-Loop Brain Stimulation for Drug-Resistant Epilepsy: Towards an Evidence-Based Approach to Personalized Medicine. Neurotherapeutics. 2019;16:119-27. doi: 10.1007/s13311-018-00682-4.

Sun FT, Morrell MJ. The RNS System: responsive cortical stimulation for the treatment of refractory partial epilepsy. Expert Rev Med Devices. 2014;11:563-72. doi: 10.1586/17434440.2014.947274.

Fisher RS, Afra P, Macken M, Minecan DN, Bagić A, Benbadis SR, et al. Automatic Vagus Nerve Stimulation Triggered by Ictal Tachycardia: Clinical Outcomes and Device Performance--The U.S. E-37 Trial. Neuromodulation. 2016;19:188-95. doi: 10.1111/ner.12376.

Salanova V, Sperling MR, Gross RE, Irwin CP, Vollhaber JA, Giftakis JE, et al. The SANTÉ study at 10 years of follow-up: Effectiveness, safety, and sudden unexpected death in epilepsy. Epilepsia. 2021;62:1306-17. doi: 10.1111/epi.16895.

Hesdorffer DC, Tomson T, Benn E, Sander JW, Nilsson L, Langan Y, et al. Combined analysis of risk factors for SUDEP. Epilepsia. 2011;52:1150-9. doi: 10.1111/j.1528-1167.2010.02952.x.

Ryvlin P, Rheims S, Hirsch LJ, Sokolov A, Jehi L. Neuromodulation in epilepsy: state-of-the-art approved therapies. Lancet Neurol. 2021;20:1038-47. doi: 10.1016/S1474-4422(21)00300-8.. Erratum in: Lancet Neurol. 2021;20:e7.

Simula S, Daoud M, Ruffini G, Biagi MC, Bénar CG, Benquet P, et al. Transcranial current stimulation in epilepsy: A systematic review of the fundamental and clinical aspects. Front Neurosci. 2022;16:909421. doi: 10.3389/fnins.2022.909421.

Lampros M, Vlachos N, Zigouris A, Voulgaris S, Alexiou GA. Transcutaneous Vagus Nerve Stimulation (t-VNS) and epilepsy: A systematic review of the literature. Seizure. 2021;91:40-8. doi: 10.1016/j.seizure.2021.05.017.

Elger CE, Hoppe C. Diagnostic challenges in epilepsy: seizure under-reporting and seizure detection. Lancet Neurol. 2018;17:279-88. doi: 10.1016/S1474-4422(18)30038-3.

Escoffery C, McGee R, Bidwell J, Sims C, Thropp EK, Frazier C, Mynatt ED. A review of mobile apps for epilepsy self-management. Epilepsy Behav. 2018;81:62-9. doi: 10.1016/j.yebeh.2017.12.010.

Alzamanan MZ, Lim KS, Akmar Ismail M, Abdul Ghani N. Self-Management Apps for People With Epilepsy: Systematic Analysis. JMIR Mhealth Uhealth. 2021;9:e22489. doi: 10.2196/22489.

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Published

2024-04-02

How to Cite

1.
Carrola Costa J, Dias L, Carvalho M. Medical Devices for the Management of Patients with Epilepsy. Sinapse [Internet]. 2024 Apr. 2 [cited 2024 May 18];24(1):23-32. Available from: https://sinapse.pt/index.php/journal/article/view/43

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Review Article