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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 Rep. 2016;5:66-71doi: 10.1016/j.ebcr.2016.03.005.
Van de Vel, A., Milosevic, M., Bonroy, B., Cuppens, K., Lagae, L., Vanrumste, B., Van Huffel, S., & Ceulemans, B. (2016). Long-term accelerometry-triggered video monitoring and detection of tonic-clonic and clonic seizures in a home environment: Pilot study. Epilepsy & behavior case reports, 566-71. https://doi.org/10.1016/j.ebcr.2016.03.005
Van de Vel, Anouk, et al. "Long-term accelerometry-triggered video monitoring and detection of tonic-clonic and clonic seizures in a home environment: Pilot study." Epilepsy & behavior case reports vol. 5 (2016): 66-71. doi: https://doi.org/10.1016/j.ebcr.2016.03.005
Van de Vel A, Milosevic M, Bonroy B, Cuppens K, Lagae L, Vanrumste B, Van Huffel S, Ceulemans B. Long-term accelerometry-triggered video monitoring and detection of tonic-clonic and clonic seizures in a home environment: Pilot study. Epilepsy Behav Case Rep. 2016 Apr 06;5:66-71. doi: 10.1016/j.ebcr.2016.03.005. eCollection 2016. PMID: 27144123; PMCID: PMC4840430.
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Epilepsy Behav Case Rep. 2016 Apr 06;5:66-71. doi: 10.1016/j.ebcr.2016.03.005. eCollection 2016.

Long-term accelerometry-triggered video monitoring and detection of tonic-clonic and clonic seizures in a home environment: Pilot study.

Epilepsy & behavior case reports

Anouk Van de Vel, Milica Milosevic, Bert Bonroy, Kris Cuppens, Lieven Lagae, Bart Vanrumste, Sabine Van Huffel, Berten Ceulemans

Affiliations

  1. Department of Neurology-Paediatric Neurology, University Hospital, University of Antwerpen, Wilrijkstraat 10, 1650 Edegem, Belgium.
  2. Department of Electrical Engineering (ESAT), STADIUS, KU Leuven, Kasteelpark Arenberg 10, Box 2446, 3001 Heverlee, Belgium; iMinds IT Department, KU Leuven, Kasteelpark Arenberg 10, Box 2446, 3001 Heverlee, Belgium.
  3. MOBILAB, Thomas More Kempen, Kleinhoefstraat 4, 2440 Geel, Belgium.
  4. Rehabilitation Center for Children and Youth Pulderbos, Reebergenlaan 4, 2242, Pulderbos, Belgium; Department of Child Neurology, University Hospital, KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
  5. Department of Electrical Engineering (ESAT), STADIUS, KU Leuven, Kasteelpark Arenberg 10, Box 2446, 3001 Heverlee, Belgium; iMinds IT Department, KU Leuven, Kasteelpark Arenberg 10, Box 2446, 3001 Heverlee, Belgium; Department of Electrical Engineering (ESAT), Advanced Integrated Sensing (AdvISe), KU Leuven, Kleinhoefstraat 4, 2440 Geel, Belgium.
  6. Department of Neurology-Paediatric Neurology, University Hospital, University of Antwerpen, Wilrijkstraat 10, 1650 Edegem, Belgium; Rehabilitation Center for Children and Youth Pulderbos, Reebergenlaan 4, 2242, Pulderbos, Belgium.

PMID: 27144123 PMCID: PMC4840430 DOI: 10.1016/j.ebcr.2016.03.005

Abstract

PURPOSE: The aim of our study was to test the efficacy of the VARIA system (video, accelerometry, and radar-induced activity recording) and validation of accelerometry-based detection algorithms for nocturnal tonic-clonic and clonic seizures developed by our team.

METHODS: We present the results of two patients with tonic-clonic and clonic seizures, measured for about one month in a home environment with four wireless accelerometers (ACM) attached to wrists and ankles. The algorithms were developed using wired ACM data synchronized with the gold standard video-/electroencephalography (EEG) and then run offline on the wireless ACM signals. Detection of seizures was compared with semicontinuous monitoring by professional caregivers (keeping an eye on multiple patients).

RESULTS: The best result for the two patients was obtained with the semipatient-specific algorithm which was developed using all patients with tonic-clonic and clonic seizures in our database with wired ACM. It gave a mean sensitivity of 66.87% and false detection rate of 1.16 per night. This included 13 extra seizures detected (31%) compared with professional caregivers' observations.

CONCLUSION: While the algorithms were previously validated in a controlled video/EEG monitoring unit with wired sensors, we now show the first results of long-term, wireless testing in a home environment.

Keywords: Data storage; Epilepsy; Nonpatient-specific algorithm; Patient-specific algorithm; Semipatient-specific algorithm; Visual verification

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