Posts Tagged seizure detection

[WEB SITE] New epilepsy warning device could save thousands of lives — ScienceDaily

Nightwatch bracelet on the arm of a young epilepsy patient.
Credit: LivAssured

A new high-tech bracelet, developed by scientists from the Netherlands detects 85 percent of all severe night-time epilepsy seizures. That is a much better score than any other technology currently available. The researchers involved think that this bracelet, called Nightwatch, can reduce the worldwide number of unexpected night-time fatalities in epilepsy patients. They published the results of a prospective trial in the scientific journal Neurology.

SUDEP, sudden unexpected death in epilepsy, is a major cause of mortality in epilepsy patients. People with an intellectual disability and severe therapy resistant epilepsy, may even have a 20% lifetime risk of dying from epilepsy. Although there are several techniques for monitoring patients at night, many attacks are still being missed.

Consortium researchers have therefore developed a bracelet that recognizes two essential characteristics of severe attacks: an abnormally fast heartbeat, and rhythmic jolting movements. In such cases, the bracelet will send a wireless alert to carers or nurses.

The research team prospectively tested the bracelet, known as Nightwatch, in 28 intellectually handicapped epilepsy patients over an average of 65 nights per patient. The bracelet was restricted to sounding an alarm in the event of a severe seizure. The patients were also filmed to check if there were any false alarms or attacks that the Nightwatch might have missed. This comparison shows that the bracelet detected 85 percent of all serious attacks and 96% of the most severe ones (tonic-clonic seizures), which is a particularly high score.

For the sake of comparison, the current detection standard, a bed sensor that reacts to vibrations due to rhythmic jerks, was tested at the same time. This signalled only 21% of serious attacks. On average, the bed sensor therefore remained unduly silent once every 4 nights per patient. The Nightwatch, on the other hand, only missed a serious attack per patient once every 25 nights on average. Furthermore, the patients did not experience much discomfort from the bracelet and the care staff were also positive about the use of the bracelet.

These results show that the bracelet works well, says neurologist and research leader Prof. Dr. Johan Arends. The Nightwatch can now be widely used among adults, both in institutions and at home. Arends expects that this may reduce the number of cases of SUDEP by two-thirds, although this also depends on how quickly and adequately care providers or informal carers respond to the alerts. If applied globally, it can save thousands of lives.

Watch the video here: https://youtu.be/0G_BQK4LK88

Story Source:

Materials provided by Eindhoven University of TechnologyNote: Content may be edited for style and length.


Journal Reference:

  1. Johan Arends, Roland D. Thijs, Thea Gutter, Constantin Ungureanu, Pierre Cluitmans, Johannes Van Dijk, Judith van Andel, Francis Tan, Al de Weerd, Ben Vledder, Wytske Hofstra, Richard Lazeron, Ghislaine van Thiel, Kit C.B. Roes, Frans Leijten. Multimodal nocturnal seizure detection in a residential care settingNeurology, 2018; 10.1212/WNL.0000000000006545 DOI: 10.1212/WNL.0000000000006545

via New epilepsy warning device could save thousands of lives — ScienceDaily

, , , , , ,

Leave a comment

[WEB SITE] Electronic device implanted in the brain could stop seizures – University of Cambridge

Green arrow points to the implant in the hippocampus of a mouse brain
Credit: Christopher Proctor

Researchers have successfully demonstrated how an electronic device implanted directly into the brain can detect, stop and even prevent epileptic seizures.

These thin, organic films do minimal damage in the brain, and their electrical properties are well-suited for these types of applications.

George Malliaras

The researchers, from the University of Cambridge, the École Nationale Supérieure des Mines and INSERM in France, implanted the device into the brains of mice, and when the first signals of a seizure were detected, delivered a native brain chemical which stopped the seizure from progressing. The results, reported in the journal Science Advances, could also be applied to other conditions including brain tumours and Parkinson’s disease.

The work represents another advance in the development of soft, flexible electronics that interface well with human tissue. “These thin, organic films do minimal damage in the brain, and their electrical properties are well-suited for these types of applications,” said Professor George Malliaras, the Prince Philip Professor of Technology in Cambridge’s Department of Engineering, who led the research.

While there are many different types of seizures, in most patients with epilepsy, neurons in the brain start firing and signal to neighbouring neurons to fire as well, in a snowball effect that can affect consciousness or motor control. Epilepsy is most commonly treated with anti-epileptic drugs, but these drugs often have serious side effects and they do not prevent seizures in three out of 10 patients.

In the current work, the researchers used a neurotransmitter which acts as the ‘brake’ at the source of the seizure, essentially signalling to the neurons to stop firing and end the seizure. The drug is delivered to the affected region of the brain by a neural probe incorporating a tiny ion pump and electrodes to monitor neural activity.

When the neural signal of a seizure is detected by the electrodes, the ion pump is activated, creating an electric field that moves the drug across an ion exchange membrane and out of the device, a process known as electrophoresis. The amount of drug can be controlled by tuning the strength of the electric field.

“In addition to being able to control exactly when and how much drug is delivered, what is special about this approach is that the drugs come out of the device without any solvent,” said lead author Dr Christopher Proctor, a postdoctoral researcher in the Department of Engineering. “This prevents damage to the surrounding tissue and allows the drugs to interact with the cells immediately outside the device.”

The researchers found that seizures could be prevented with relatively small doses of drug representing less than 1% of the total amount of drug loaded into the device. This means the device should be able to operate for extended periods without needing to be refilled. They also found evidence that the delivered drug, which was in fact a neurotransmitter that is native to the body, was taken up by natural processes in the brain within minutes which, the researchers say, should help reduce side effects from the treatment.

Although early results are promising, the potential treatment would not be available for humans for several years. The researchers next plan to study the longer-term effects of the device in mice.

Malliaras is establishing a new facility at Cambridge which will be able to prototype these specialised devices, which could be used for a range of conditions. Although the device was tested in an animal model of epilepsy, the same technology could potentially be used for other neurological conditions, including the treatment of brain tumours and Parkinson’s disease.

The research was funded by the European Union.

Reference: 
Christopher M. Proctor et al. ‘Electrophoretic drug delivery for seizure control.’ Science Advances (2018). DOI: 10.1126/sciadv.aau1291

 


Researcher profile: Dr Christopher Proctor

Dr Christopher Proctor is one of the first nine recipients of the Borysiewicz Biomedical Sciences Fellowship programme.

My research sets out to develop medical devices to treat and diagnose various health problems that have been difficult to address with conventional approaches such as epilepsy, Parkinson’s disease and brain tumours. As an engineer with expertise in electronics and materials, I work closely with biologists and clinicians in all stages of device development from early stage designing to late-stage testing.

The most exciting day I’ve had in research so far was when a concept that I took from a drawing on paper to a real device that I could hold in my hand, prevented a seizure for the third time. I say the third time because I am forever a sceptic, so I was hesitant to believe our initial results until we repeated it a couple times. Having seen that it was a repeatable result was very exciting because that is when you know you may really be on to something special.

I hope my research will ultimately lead to a better quality of life for people with health problems. I believe we are only scraping the surface of what is possible when we pair electronic devices with biology. It is difficult to project where early-stage research will go, but I suspect the way we address some of the most difficult to treat diseases may be radically different in the coming decades.

Cambridge is a great place to research and develop medical devices because this type of work is truly a team effort that requires expertise in everything from engineering to chemistry to medicine up to government regulations, finance and marketing. There is an ecosystem in and around the University of Cambridge that can bring all these experts together and that is exactly what is needed to take an early stage technology all the way to the patients that we are trying to help.

 

via Electronic device implanted in the brain could stop seizures | University of Cambridge

, , , , ,

Leave a comment

[WEB SITE] What Modern Day Challenges Affect Epilepsy Treatment?

epilepsy

Researchers recently published an article in The Lancet Neurology discussing the difficulties facing seizure detection in patients with epilepsy.

Epilepsy is a neurological disorder that is characterised by short repetitive epileptic seizures.  These seizures can be harmful to the individual depending on the circumstances in which they occur, such as a seizure while driving. This disorder is set apart from other neurological disorders since there is a broad range of different physiological changes that can cause it, leading to a large variation in symptoms and making it difficult to treat. While 70% of sufferers can be treated with pharmacological agents, 30% have no reliable anti-epileptic drugs that are effective for their particular type of epilepsy.

In a recent study, Christian Elger and Christian Hoppe determined that a key challenge facing patients is that over 50% of patients under-report the number of seizures they experience, which has a serious impact on how well doctors are able to determine what treatments are most suitable for them. This also calls into question many of the previously published research on epilepsy treatments. They recently published this report in The Lancet Neurology.

Why are Epileptic Seizures Difficult to Detect?

In this personal view, the writers determined that the cause of under-reporting is primarily due to patients, or their caregivers, being unable to identify when seizures are occurring. Seizures can impair consciousness, may occur at night, or the physical symptoms may be so subtle that they are not easily noticed unless professionally trained to do so.

Technologies for Epilepsy DetectionThe gold standard for epilepsy detection is video-electroencephalography (VEEG), where patients have their brain activity monitored for epilepsy-specific activity and trained technicians can test for impairments to consciousness, cognition, language, and memory. Video footage from the VEEG can also be viewed at a later time to spot slight body movements indicative of a seizure. The limitation of this method is that it requires a hospital visit, increasing associated costs, and is only suitable for identifying how frequent a person has a seizure over a given time, it does not address the issue of a person (or their caregiver) being aware they are having a seizure in real time.

Automated System Required

It is clear that the future of seizure detection requires an automated system,  preferably one that patients can wear over the long-term and that will notify them or a nearby center when a seizure occurs. The main barriers to this technology is that a number of the current ambulatory systems for monitoring brain activity can be limited in monitoring time (72 hours) or require labor-intensive analysis of data, although as algorithms for analyzing brain activity improve this limitation will also decrease.

An analysis of movement via home-based video systems, or of various physical data outputs (i.e. accelerometry, magnetometry, gyroscopy, or pressure data) derived from worn sensors have some promise but so far the results have not been consistent.

Surface Electromyography

It appears that one of the most promising methods, which is also viewed favorably by patients, is surface electromyography (SEMG). This method involves self-adhesive sensors that are attached to muscles in areas of the body affected by seizures. Furthermore, multi-modal approaches that combine SEMG, EEG, and electrocardiography have a detection rate over 85% for the majority of seizure types.

Improved Seizure Detection Necessary

It is clear that improved seizure detection is necessary for ensuring that doctors provide the most appropriate treatment to individual patients, as well as ensuring that patients are protected from life-threatening seizures. Improving wearable, ambulatory technologies and advancements in algorithms for the analysis of seizure data will help provide comprehensive support to both physicians and to the patients that they monitor.

Written by Michael Healy, BSc, MSc

Reference: Elger C.E., Hoppe C. Diagnostic challenges in epilepsy: seizure under-reporting and seizure detection. Lancet Neurol 2018; 17: 279–88.

via What Modern Day Challenges Affect Epilepsy Treatment? – Medical News Bulletin | Health News and Medical Research

, , , , , , ,

Leave a comment

[Abstract+References] Diagnostic challenges in epilepsy: seizure under-reporting and seizure detection

Summary

Epileptic seizures vary greatly in clinical phenomenology and can markedly affect the patient’s quality of life. As therapeutic interventions focus on reduction or elimination of seizures, the accurate documentation of seizure occurrence is essential. However, patient self-evaluation compared with objective evaluation by video-electroencephalography (EEG) monitoring or long-term ambulatory EEG revealed that patients document fewer than 50% of their seizures, on average, and that documentation accuracy varies significantly over time. For good clinical practice in epilepsy, novel and feasible seizure detection techniques for ambulatory long-term use are needed. Generalised tonic-clonic seizures can already be detected reliably by methods that rely on motion recording (eg, surface electromyography). However, the automatic detection of other seizure types, such as complex partial seizures, will require multimodal approaches that combine the measurement of ictal autonomic alterations (eg, heart rate) and of characteristic movement patterns (eg, accelerometry). Innovative and feasible tools for automatic seizure detection are likely to advance both monitoring of the outcome of a treatment in a patient and clinical research in epilepsy.

References

  1. Fisher, RS, van Emde Boas, W, Blume, W et al. Epileptic seizures and epilepsy: definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE).Epilepsia200546470–472
  2. Beghi, E. Addressing the burden of epilepsy: many unmet needs. Pharmacol Res201610779–84
  3. Schmidt, D and Schachter, SC. Drug treatment of epilepsy in adults. BMJ2014348g254
  4. Fisher, RS, Blum, DE, DiVentura, B et al. Seizure diaries for clinical research and practice: limitations and future prospects. Epilepsy Behav201224304–310
  5. Blum, DE, Eskola, J, Bortz, JJ, and Fisher, RS. Patient awareness of seizures. Neurology199647260–264
  6. Inoue, Y and Mihara, T. Awareness and responsiveness during partial seizures. Epilepsia1998397–10
  7. Nijsen, TM, Arends, JB, Griep, PA, and Cluitmans, PJ. The potential value of three-dimensional accelerometry for detection of motor seizures in severe epilepsy. Epilepsy Behav2005774–84
  8. Kerling, F, Mueller, S, Pauli, E, and Stefan, H. When do patients forget their seizures? An electroclinical study. Epilepsy Behav20069281–285
  9. Hoppe, C, Poepel, A, and Elger, C. Epilepsy: accuracy of patient seizure counts. Arch Neurol2007;641595–1599
  10. Poochikian-Sarkissian, S, Tai, P, del Campo, M et al. Patient awareness of seizures as documented in the epilepsy monitoring unit. Can J Neurosci Nurs20093122–23
  11. DuBois, JM, Boylan, LS, Shiyko, M, Barr, WB, and Devinsky, O. Seizure prediction and recall.Epilepsy Behav201018106–109
  12. Tatum, WO 4th, Winters, L, Gieron, M et al. Outpatient seizure identification: results of 502 patients using computer-assisted ambulatory EEG. J Clin Neurophysiol20011814–19
  13. Fattouch, J, Di Bonaventura, C, Lapenta, L et al. Epilepsy, unawareness of seizures and driving license: the potential role of 24-hour ambulatory EEG in defining seizure freedom. Epilepsy Behav20122532–35
  14. Cook, MJ, O’Brien, TJ, Berkovic, SF et al. Prediction of seizure likelihood with a long-term, implanted seizure advisory system in patients with drug-resistant epilepsy: a first-in-man study.Lancet Neurol201312563–571
  15. Van de Vel, A, Milosevic, M, Bonroy, B et al. Long-term accelerometry-triggered video monitoring and detection of tonic-clonic and clonic seizures in a home environment: pilot study. Epilepsy Behav Case Rep2016566–71
  16. Browne, TR, Dreifuss, FE, Penry, JK, Porter, RJ, and White, BG. Clinical and EEG estimates of absence seizure frequency. Arch Neurol198340469–472
  17. Akman, CI, Montenegro, MA, Jacob, S, Eck, K, Chiriboga, C, and Gilliam, F. Seizure frequency in children with epilepsy: factors influencing accuracy and parental awareness. Seizure200918524–529
  18. Glauser, TA, Cnaan, A, Shinnar, S et al. Ethosuximide, valproic acid, and lamotrigine in childhood absence epilepsy. N Engl J Med2010362790–799
  19. Munos, B, Baker, PC, Bot, BM et al. Mobile health: the power of wearables, sensors, and apps to transform clinical trials. Ann N Y Acad Sci201613753–18
  20. Hamandi, K, Beniczky, S, Diehl, B et al. Current practice and recommendations in UK epilepsy monitoring units. Report of a national survey and workshop. Seizure20175092–98
  21. Beniczky, S, Neufeld, M, Diehl, B et al. Testing patients during seizures: a European consensus procedure developed by a joint taskforce of the ILAE—Commission on European Affairs and the European Epilepsy Monitoring Unit Association. Epilepsia2016571363–1368
  22. Osorio, I and Manly, BF. Probability of detection of clinical seizures using heart rate changes.Seizure201530120–123
  23. Ulate-Campos, A, Coughlin, F, Gaínza-Lein, M, Fernández, IS, Pearl, PL, and Loddenkemper, T.Automated seizure detection systems and their effectiveness for each type of seizure. Seizure2016;4088–101
  24. Elger, CE and Mormann, F. Seizure prediction and documentation—two important problems.Lancet Neurol201312531–532
  25. Dalrymple, J and Appleby, J. Cross sectional study of reporting of epileptic seizures to general practitioners. BMJ200032094–97
  26. Del Brutto, OH and Mera, RM. The importance of people compliance (social desirability bias) in the assessment of epilepsy prevalence in rural areas of developing countries. Results of the Atahualpa Project. Epilepsia201657e221–e224
  27. Blachut, B, Hoppe, C, Surges, R, Stahl, J, Elger, CE, and Helmstaedter, C. Counting seizures: the primary outcome measure in epileptology from the patients’ perspective. Seizure20152997–103
  28. Blachut, B, Hoppe, C, Surges, R, Elger, C, and Helmstaedter, C. Subjective seizure counts by epilepsy clinical drug trial participants are not reliable. Epilepsy Behav201767122–127
  29. Detyniecki, K and Blumenfeld, H. Consciousness of seizures and consciousness during seizures: are they related?. Epilepsy Behav2014306–9
  30. Rheims, S and Ryvlin, P. Patients’ safety in the epilepsy monitoring unit: time for revising practices. Curr Opin Neurol201427213–218
  31. Hoppe, C, Feldmann, M, Blachut, B, Surges, R, Elger, CE, and Helmstaedter, C. Novel techniques for automated seizure registration: patients’ wants and needs. Epilepsy Behav2015521–7
  32. Patel, AD, Moss, R, Rust, SW et al. Patient-centered design criteria for wearable seizure detection devices. Epilepsy Behav201664116–121
  33. Tovar Quiroga, DF, Britton, JW, and Wirrell, EC. Patient and caregiver view on seizure detection devices: a survey study. Seizure201641179–181
  34. Van de Vel, A, Smets, K, Wouters, K, and Ceulemans, B. Automated non-EEG based seizure detection: do users have a say?. Epilepsy Behav201662121–128
  35. van Andel, J, Leijten, F, van Delden, H, and van Thiel, G. What makes a good home-based nocturnal seizure detector? A value sensitive design. PLoS One201510e0121446
  36. Schulze-Bonhage, A, Sales, F, Wagner, K et al. Views of patients with epilepsy on seizure prediction devices. Epilepsy Behav201018388–396
  37. Bialer, M, Johannessen, SI, Levy, RH et al. Seizure detection and neuromodulation: a summary of data presented at the XIII conference on new antiepileptic drug and devices (EILAT XIII). Epilepsy Res201713027–36
  38. Van de Vel, A, Cuppens, K, Bonroy, B et al. Non-EEG seizure detection systems and potential SUDEP prevention: state of the art: review and update. Seizure201641141–153
  39. van Andel, J, Thijs, RD, de Weerd, A, Arends, J, and Leijten, F. Non-EEG based ambulatory seizure detection designed for home use: what is available and how will it influence epilepsy care?. Epilepsy Behav20165782–89
  40. Jory, C, Shankar, R, Coker, D, McLean, B, Hanna, J, and Newman, C. Safe and sound? A systematic literature review of seizure detection methods for personal use. Seizure2016364–15
  41. Askamp, J and van Putten, MJ. Mobile EEG in epilepsy. Int J Psychophysiol20149130–35
  42. Mihajlovic, V, Grundlehner, B, Vullers, R, and Penders, J. Wearable, wireless EEG solutions in daily life applications: what are we missing?. IEEE J Biomed Health Inform2015196–21
  43. Grant, AC, Abdel-Baki, SG, Omurtag, A et al. Diagnostic accuracy of microEEG: a miniature, wireless EEG device. Epilepsy Behav20143481–85
  44. Debener, S, Emkes, R, De Vos, M, and Bleichner, M. Unobtrusive ambulatory EEG using a smartphone and flexible printed electrodes around the ear. Sci Rep2015516743
  45. Baldassano, SN, Brinkmann, BH, Ung, H et al. Crowdsourcing seizure detection: algorithm development and validation on human implanted device recordings. Brain20171401680–1691
  46. Mathieson, SR, Stevenson, NJ, Low, E et al. Validation of an automated seizure detection algorithm for term neonates. Clin Neurophysiol2016127156–168
  47. Hopfengärtner, R, Kasper, BS, Graf, W et al. Automatic seizure detection in long-term scalp EEG using an adaptive thresholding technique: a validation study for clinical routine. Clin Neurophysiol20141251346–1352
  48. Hartmann, MM, Schindler, K, Gebbink, TA, Gritsch, G, and Kluge, T. PureEEG: automatic EEG artifact removal for epilepsy monitoring. Neurophysiol Clin201444479–490
  49. Sierra-Marcos, A, Scheuer, ML, and Rossetti, AO. Seizure detection with automated EEG analysis: a validation study focusing on periodic patterns. Clin Neurophysiol2015126456–462
  50. Touloumes, G, Morse, E, Chen, WC et al. Human bedside evaluation versus automatic responsiveness testing in epilepsy (ARTiE). Epilepsia201657e28–e32
  51. Fürbass, F, Ossenblok, P, Hartmann, M et al. Prospective multi-center study of an automatic online seizure detection system for epilepsy monitoring units. Clin Neurophysiol20151261124–1131
  52. Geller, EB, Skarpaas, TL, Gross, RE et al. Brain-responsive neurostimulation in patients with medically intractable mesial temporal lobe epilepsy. Epilepsia201758994–1004
  53. Jobst, BC, Kapur, R, Barkley, GL et al. Brain-responsive neurostimulation in patients with medically intractable seizures arising from eloquent and other neocortical areas. Epilepsia2017581005–1014
  54. Dericioglu, N, Yetim, E, Bas, DF et al. Non-expert use of quantitative EEG displays for seizure identification in the adult neuro-intensive care unit. Epilepsy Res201510948–56
  55. Rakshasbhuvankar, A, Paul, S, Nagarajan, L, Ghosh, S, and Rao, S. Amplitude-integrated EEG for detection of neonatal seizures: a systematic review. Seizure20153390–98
  56. Temko, A, Marnane, W, Boylan, G, and Lightbody, G. Clinical implementation of a neonatal seizure detection algorithm. Decis Support Syst20157086–96
  57. Tewolde, S, Oommen, K, Lie, DY, Zhang, Y, and Chyu, MC. Epileptic seizure detection and prediction based on continuous cerebral blood flow monitoring—a review. J Health Eng20156159–178
  58. Jeppesen, J, Beniczky, S, Johansen, P, Sidenius, P, and Fuglsang-Frederiksen, A. Exploring the capability of wireless near infrared spectroscopy as a portable seizure detection device for epilepsy patients. Seizure20152643–48
  59. Kandler, R, Ponnusamy, A, and Wragg, C. Video ambulatory EEG: a good alternative to inpatient video telemetry?. Seizure20174766–70
  60. Pediaditis, M, Tsiknakis, M, and Leitgeb, N. Vision-based motion detection, analysis and recognition of epileptic seizures—a systematic review. Comput Methods Programs Biomed20121081133–1148
  61. Noda, K. Google Home: smart speaker as environmental control unit. Disabil Rehabil Assist Technol2017; : 1–2
  62. Beniczky, S, Polster, T, Kjaer, TW, and Hjalgrim, H. Detection of generalized tonic-clonic seizures by a wireless wrist accelerometer: a prospective, multicenter study. Epilepsia201354e58–e61
  63. Velez, M, Fisher, RS, Bartlett, V, and Le, S. Tracking generalized tonic-clonic seizures with a wrist accelerometer linked to an online database. Seizure20163913–18
  64. Cuppens, K, Karsmakers, P, Van de Vel, A et al. Accelerometry-based home monitoring for detection of nocturnal hypermotor seizures based on novelty detection. IEEE J Biomed Health Inform2014181026–1033
  65. Patterson, AL, Mudigoudar, B, Fulton, S et al. SmartWatch by SmartMonitor: assessment of seizure detection efficacy for various seizure types in children, a large prospective single-center study. Pediatr Neurol201553309–311
  66. Fulton, S, Poppel, KV, McGregor, A, Ellis, M, Patters, A, and Wheless, J. Prospective study of 2 bed alarms for detection of nocturnal seizures. J Child Neurol2013281430–1433
  67. Narechania, AP, Garić, II, Sen-Gupta, I, Macken, MP, Gerard, EE, and Schuele, SU. Assessment of a quasi-piezoelectric mattress monitor as a detection system for generalized convulsions. Epilepsy Behav201328172–176
  68. Beniczky, S, Conradsen, I, Moldovan, M et al. Quantitative analysis of surface electromyography during epileptic and nonepileptic convulsive seizures. Epilepsia2014551128–1134
  69. Halford, JJ, Sperling, MR, Nair, DR et al. Detection of generalized tonic-clonic seizures using surface electromyographic monitoring. Epilepsia2017581861–1869
  70. Beniczky, S, Conradsen, I, Pressler, R, and Wolf, P. Quantitative analysis of surface electromyography: biomarkers for convulsive seizures. Clin Neurophysiol20161272900–2907
  71. Szabó, CÁ, Morgan, LC, Karkar, KM et al. Electromyography-based seizure detector: preliminary results comparing a generalized tonic-clonic seizure detection algorithm to video-EEG recordings.Epilepsia2015561432–1437
  72. Hagge, M, Nunnemann, S, Bauer, S et al. Biceps electromyography in dialeptic and automotor seizures with and without secondary generalization. Clin Neurophysiol20161271163–1169
  73. Osorio, I. Automated seizure detection using EKG. Int J Neural Syst2014241450001
  74. Osorio, I and Manly, BF. Is seizure detection based on EKG clinically relevant?. Clin Neurophysiol20141251946–1951
  75. Jeppesen, J, Fuglsang-Frederiksen, A, Brugada, R et al. Heart rate variability analysis indicates preictal parasympathetic overdrive preceding seizure-induced cardiac dysrhythmias leading to sudden unexpected death in a patient with epilepsy. Epilepsia201455e67–e71
  76. Jeppesen, J, Beniczky, S, Johansen, P, Sidenius, P, and Fuglsang-Frederiksen, A. Detection of epileptic seizures with a modified heart rate variability algorithm based on Lorenz plot. Seizure2015241–7
  77. Eggleston, KS, Olin, BD, and Fisher, RS. Ictal tachycardia: the head-heart connection. Seizure201423496–505
  78. Goldenholz, DM, Kuhn, A, Austermuehle, A et al. Long-term monitoring of cardiorespiratory patterns in drug-resistant epilepsy. Epilepsia20175877–84
  79. Poh, MZ, Loddenkemper, T, Reinsberger, C et al. Autonomic changes with seizures correlate with postictal EEG suppression. Neurology2012781868–1876
  80. Hampel, KG, Jahanbekam, A, Elger, CE, and Surges, R. Seizure-related modulation of systemic arterial blood pressure in focal epilepsy. Epilepsia2016571709–1718
  81. Reinsberger, C, Perez, DL, Murphy, MM, and Dworetzky, BA. Pre- and postictal, not ictal, heart rate distinguishes complex partial and psychogenic nonepileptic seizures. Epilepsy Behav20122368–70
  82. Opherk, C, Coromilas, J, and Hirsch, LJ. Heart rate and EKG changes in 102 seizures: analysis of influencing factors. Epilepsy Res200252117–127
  83. Stefanidou, M, Carlson, C, and Friedman, D. The relationship between seizure onset zone and ictal tachycardia: an intracranial EEG study. Clin Neurophysiol20151262255–2260
  84. Kolsal, E, Serdaroğlu, A, Cilsal, E et al. Can heart rate variability in children with epilepsy be used to predict seizures?. Seizure201423357–362
  85. Franco, AC, Noachtar, S, and Rémi, J. Ictal ipsilateral sweating in focal epilepsy. Seizure2017504–5
  86. Thomas, SS, Nathan, V, Zong, C, Soundarapandian, K, Shi, X, and Jafari, R. BioWatch: a noninvasive wrist-based blood pressure monitor that incorporates training techniques for posture and subject variability. IEEE J Biomed Health Inform2016201291–1300
  87. Poh, MZ, McDuff, DJ, and Picard, RW. Advancements in noncontact, multiparameter physiological measurements using a webcam. IEEE Trans Biomed Eng2011587–11
  88. Fisher, RS, Afra, P, Macken, M et al. Automatic vagus nerve stimulation triggered by ictal tachycardia: clinical outcomes and device performance—the U.S. E-37 trial. Neuromodulation2016;19188–195
  89. Nass, RD, Sassen, R, Elger, CE, and Surges, R. The role of postictal laboratory blood analyses in the diagnosis and prognosis of seizures. Seizure20174751–65
  90. Surges, R, Kretschmann, A, Abnaof, K et al. Changes in serum miRNAs following generalized convulsive seizures in human mesial temporal lobe epilepsy. Biochem Biophys Res Comm201648113–18
  91. Matz, O, Zdebik, C, Zechbauer, S et al. Lactate as a diagnostic marker in transient loss of consciousness. Seizure20164071–75
  92. Chatzikonstantinou, A, Ebert, AD, and Hennerici, MG. Temporal seizure focus and status epilepticus are associated with high-sensitive troponin I elevation after epileptic seizures. Epilepsy Res201511577–80
  93. Stöcklin, B, Fouzas, S, Schillinger, P et al. Copeptin as a serum biomarker of febrile seizures. PLoS One201510e0124663
  94. Tumani, H, Jobs, C, Brettschneider, J, Hoppner, AC, Kerling, F, and Fauser, S. Effect of epileptic seizures on the cerebrospinal fluid—a systematic retrospective analysis. Epilepsy Res201511423–31
  95. Fisher, RS, Bartfeld, E, and Cramer, JA. Use of an online epilepsy diary to characterize repetitive seizures. Epilepsy Behav20154766–71
  96. Wong, KF, Smith, AC, Pierce, ET et al. Statistical modeling of behavioral dynamics during propofol-induced loss of consciousness. J Neurosci Methods201422765–74
  97. Patel, AC, Thornton, RC, Mitchell, TN, and Michell, AW. Advances in EEG: home video telemetry, high frequency oscillations and electrical source imaging. J Neurol20162632139–2144
  98. Goodwin, E, Kandler, RH, and Alix, JJ. The value of home video with ambulatory EEG: a prospective service review. Seizure201423480–482
  99. Fürbass, F, Kampusch, S, Kaniusas, E et al. Automatic multimodal detection for long-term seizure documentation in epilepsy. Clin Neurophysiol20171281466–1472
  100. Conradsen, I, Beniczky, S, Wolf, P, Kjaer, TW, Sams, T, and Sorensen, HB. Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data. Comput Methods Programs Biomed201210797–110
  101. Cogan, D, Birjandtalab, J, Nourani, M, Harvey, J, and Nagaraddi, V. Multi-biosignal analysis for epileptic seizure monitoring. Int J Neural Syst2017271650031
  102. Larsen, SN, Conradsen, I, Beniczky, S, and Sorensen, HB. Detection of tonic epileptic seizures based on surface electromyography. Conf Proc IEEE Eng Med Biol Soc20142014942–945
  103. Van de Vel, A, Verhaert, K, and Ceulemans, B. Critical evaluation of four different seizure detection systems tested on one patient with focal and generalized tonic and clonic seizures.Epilepsy Behav20143791–94
  104. McLean, B, Shankar, R, Hanna, J, Jory, C, and Newman, C. Sudden unexpected death in epilepsy: measures to reduce risk. Pract Neurol20171713–20
  105. Picard, RW, Migliorini, M, Caborni, C et al. Wrist sensor reveals sympathetic hyperactivity and hypoventilation before probable SUDEP. Neurology201789633–635
  106. Jobst, BC and Cascino, GD. Resective epilepsy surgery for drug-resistant focal epilepsy: a review. JAMA2015313285–293

via Diagnostic challenges in epilepsy: seizure under-reporting and seizure detection

, , ,

Leave a comment

[WEB SITE] A wearable using AI to identify severe seizures and warn caregivers gains FDA approval

Embrace by Empatica is a smart watch for epilepsy management to identify convulsive seizures and send alerts to caregivers.

Empatica, a Massachusetts Institute of Technology spinoff, received FDA clearance for a wristworn device that uses machine learning to alert people with epilepsy and their caregivers of a convulsive seizure and track their duration and frequency.

Epilepsy affects a least 2.2 million people, according to data from the Epilepsy Foundation.

Empatica’s Emrace device assesses multiple indicators of a seizure, including electrodermal activity, a signal associated with fight or flight response that’s used by stress researchers to quantify physiological changes related to sympathetic nervous system activity, the company statement noted.

In a clinical trial of the device, 135 patients across multiple sites resided at epilepsy monitoring units with continuous monitoring with video-EEG and simultaneously wore an Empatica device. Data collected over 272 days showed that the wearable’s algorithm detected 100 percent of the seizures, according to the company’s statement.

In addition to seizures, the device also tracks sleep and physical activity, according to the company’s website.

The company’s FDA clearance comes nearly one year since its device received regulatory approval in Europe.

Rosalind Picard, the Director of the Affective Computing Group at MIT Media Lab and Chief Scientist at Empatica said in a company statement that “it’s been very meaningful to see this technology move from the lab” into an easy-to-use sensor.

Other companies have developed seizure detection systems, particularly with the goal of sharing the collected data with clinicians so they have a better understanding of their patients’ health between appointments. SmartMonitor developed a smartwatch that detects “irregular shaking” akin to a convulsive seizure. Last month it rolled out a version of its technology in an app for the Apple smartwatch.

Two years ago THREAD Research developed a smartwatch application for tracking epileptic seizures for ResearchKit with Johns Hopkins University.

The holy grail for people who suffer from seizures would be a device that could warn them ahead of time so that people could avoid potentially putting themselves in harm’s way or take other appropriate action. That’s a longterm goal for Empatica.

Photo: Empatica

via A wearable using AI to identify severe seizures and warn caregivers gains FDA approval – MedCity News

, , ,

Leave a comment

[WEB SITE] Using Tech to Improve life with Epilepsy

Jennifer’s Story

Colleen’s life began with so much uncertainty; none of her doctors knew what to expect and what she would be capable of. As she’s gotten older, we’ve had to overcome many issues, including communication and safety. But this is where technology has begun to play a key role.

Having both epilepsy and cerebral palsy, I thought her crib would work for her for a while. It was lowered to as far as it would go, and I thought that it was enough to keep her safe. One day, much to my surprise, she managed to get out of her crib and crawl to the landing at the top of the stairway. Thank goodness for some left-out Easter decorations, or I don’t want to know what could have happened. I knew at that point, Colleen needed a better option. We worked with her service coordinator and I began to search online for solutions. A lot of options were large and clunky. Or, they left me wondering just how long they would work for. I found and petitioned for the Safety Sleeper, also known as Abrams Bed. It’s an enclosed bed designed for special needs and has been an absolute life-saver. Colleen loves it and I can sleep well at night knowing she can’t fall out or get into anything unsafe. What makes the Safety Sleeper better for our needs is that it is portable. It came with it’s own suitcase and is very easy to assemble. So, when we make our annual trip to Boston Children’s or want to go on vacation (this actually hasn’t quite happened yet!) it can be brought with us!

Colleen, spent 20 days in the NICU. There was a lot of uncertainty, questions that couldn’t be fully answered. But I believed when they thought she would eventually grow out of it. The medications changed, but her EEG’s stayed the same. Throughout, I still hoped that maybe one day when we went in for that EEG, we’d finally be told that there was an improvement. She had two seizures in the NICU, and one in 2013. But there was a dramatic increase in visible seizures in 2015 (I say visible because her EEG showed seizure activity, but we couldn’t tell she was having anything, other than maybe a slight pause or some blinking). This is when I discovered the very real and very scary SUDEP. None of her doctors ever told me about the risk. I was always scared about Colleen having a seizure at night, but with her increase, I became very scared of this possibility. I remembered having seen a GoFundMe campaign for the Embrace epilepsy monitoring watch.

What amazing technology! Something that could detect seizures and alert caregivers? I didn’t even know that was possible. But at that point in time, they weren’t ready. So I began to search for other options and found the SAMi camera. This gets mounted to a wall near their bed, and can detect seizure movements. This was the first step to being able to sleep better at night. I cannot say just how much better it makes you feel to know that your loved one, your child has a constant watch on them. Once the Embrace watch was released, Colleen received hers and we could not be happier. It has alerted up on a few occasions where we were able to get to Colleen and make sure she’s safe until the end of her seizure. This device is also invaluable.

Through all this, even with the close monitoring, you still want what is best for your child, no matter what. And as technology also advances, so does medical innovation. I clearly remember the words of Colleen’s neurologist. She has scar tissue on her right and left frontal lobe from her birth injury. “Once the neurons are damaged, they cannot regrow.” It was crushing, but I knew it was true. I just hoped that her brain, as little as she was, would be able to “remap” itself to avoid the damage. Still, instead of accepting that as it was, I researched “neuron regeneration” when we got home from the neurologist and found two research studies; one in the U.S and one in Europe. Maybe not now, but in the future, there could be hope!

But, what if there is hope today? As I was browsing Instagram one day, I found a post from one of the families I follow whose daughter also has cerebral palsy, and she talked about receiving stem cell therapy. I immediately began to research and even emailed the mother who had posted about the therapy. The doctor she brought her daughter to in California uses cord blood stem cells. Stem cells are thought to be able to travel to areas of the body where they are needed. They are able to bridge gaps and form new neurons.

I was elated. We got in touch with the doctor and were able to raise enough money to take her. One of the things that struck me most about the doctor was when he was talking about stem cell therapy. He told me so many successes and stories of hope and miracles. The stem cells themselves are screened, as with the mom and baby, almost like if you were donating blood. They are 100% safe. I see the progress of the family on Instagram, and I had a co-worker come to me and tell me about their niece, who had had the therapy within a medical study.

The therapy session itself is very easy. We traveled from New York to California. Her appointment was at 9AM. Walking talking through everything with us, we gave Colleen a dose of her emergency med to help her relax. He also programed a Microcurrent machine, which was a surprise. When you get an EEG, electrodes are placed on your head, and they can essentially read the brain waves. Microcurrent is able to focus on those areas, almost as a way to direct the stem cells where to go. Colleen’s microcurrent program was directed to her right and left frontal lobe as well as her ears (she has bilateral hearing loss).

We are two months post-stem cells and so far, very happy with the results. Colleen is babbling a lot more. She’s making sounds that she never did prior. She’s experiencing far less stomach issues. She can incredibly close to needing a feeding tube as she was failure to thrive. After having to see her literally suffer for months and months, it’s amazing that she’s no longer uncomfortable and in pain. She’s more aware of her surroundings and has been more careful. She’s using her arms more and seems stronger. A week after stem cells, she went to see her neurologist. I was sad to find out there was really no change in her EEG, but that’s okay. When she’s gotten enough sleep, we’ve seen far less myoclonic jerks. After one treatment, I think it’s safe to say that this medical innovation is a life-changer and we plan on bringing Colleen back for additional treatment.

Epilepsy makes me feel out of control. In some sense, I have felt that no matter what we did, we just couldn’t help her in the way we would like. What has made me feel empowered is researching. The more knowledge I have, the more prepared I can be for the uncertainties. Technology has given me peace of mind, and I have no doubt that there are and can be better options in the future. Of course, as a mother, nothing would make me happier than for there to be a cure for epilepsy.

This is where, I believe, medical innovation will come into play. And based on what we’ve been able to do so far, I have faith.

If you would like any more information about stem cell therapy, or any of the other things I have talked about, please feel free to email me at jennylouns@email.com

via Using Tech to Improve life with Epilepsy – Alert News Today

, ,

Leave a comment

[WEB SITE] Wearable Seizure Detection Devices Promising – Medscape

PHILADELPHIA — Costly in-hospital video electroencephalography (EEG) monitoring for epilepsy may soon be replaced by wearable seizure detection devices — at least that seems to be where the technology is headed.

Some of the new devices, all relatively small and discreet and variously worn on the arm, scalp, and wrist, were highlighted here at the American Epilepsy Society (AES) 69th Annual Meeting.

One of these monitoring units detects generalized tonic-clonic (GTC) seizure activity. The Brain Sentinel GTC Seizure Detection and Warning System appears to have a very low false-positive rate, José Cavazos, MD, PhD, a board-certified epileptologist and cofounder of Brain Sentinel, the company behind the new device, reported.

The portable device, currently under US Food and Drug Administration regulatory review, provides real-time analysis of surface electromyography (sEMG) data to detect GTC seizures. It also has an alarm that alerts caregivers in the event of such a seizure.

The longitudinal clinical data that it captures should help guide treatment, Dr Cavazos said.

The system includes a discreet detection device, base station (laptop), and cellular wireless router. The detection device is attached to the biceps with an adhesive patch that has three pre-gelled sEMG electrodes.

“We have fine-tuned the algorithm to understand the recruiting properties of muscle cells in the biceps muscle,” Dr Cavazos told a press briefing. “This is a direct reflection of brain activity; meaning that if you stimulate the brain, muscles are going to contract.”

He added that collecting information from muscles, which are connected directed via neurons to the brain, may be less susceptible to artefacts than devices that collect biometric signals through other means.

A new study, funded by the company and presented here, compared the device to “gold standard” video EEG (vEEG) in patients at 11 epilepsy monitoring units across the United States. All parties were blinded to the seizure alert status of the device.

The analysis included 7326 hours of sEMG and vEEG data collected in 142 participants wearing the device. When the device was properly used, its sensitivity to identify GTC seizures was 100% compared with vEEG review. The false-negative rate was 0.48 per 8 hours.

“This device certainly can provide some peace of mind to some patients,” said Dr Cavazos.

Asked to comment on Dr Cavazos’s device, R. Edward Hogan, MD, professor and director, Adult Epilepsy Center, Washington University, St Louis, Missouri, thought it was promising in helping to track seizures, which can be useful in determining whether treatments are working.

Tracking seizures has traditionally been difficult, said Dr Hogan. “Overall, people remember only about half of their seizures,” he said. “So right off the bat, there’s a problem with people not remembering just by the nature of what happens to the brain during seizures.”

An effective seizure tracker can also improve safety. Because seizures can cause injuries — patients often fall and hurt themselves — a convenient device that alerts caregivers and others of a seizure “would be great,” said Dr Hogan.

He was encouraged by the low false-positive rate of this new device. “You don’t want a system that goes off all the time.”

The study authors, he said, “have looked at the pattern of how the muscle contraction changes,” and the false-positive rate they picked up with the device was “pretty good.”

Continue —> Wearable Seizure Detection Devices Promising

, ,

Leave a comment

%d bloggers like this: