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Accelerometry-based home monitoring for detection of nocturnal hypermotor seizures based on novelty detection

Author
Organization
Abstract
Nocturnal home monitoring of epileptic children is often not feasible due to the cumbersome manner of seizure monitoring with the standard method of video/EEG-monitoring. We propose a method for hypermotor seizure detection based on accelerometers attached to the extremities. From the acceleration signals, multiple temporal, frequency, and wavelet-based features are extracted. After determining the features with the highest discriminative power, we classify movement events in epileptic and nonepileptic movements. This classification is only based on a non-parametric estimate of the probability density function of normal movements. Such approach allows us to build patient-specific models to classify movement data without the need for seizure data that are rarely available. If, in the test phase, the probability of a data point (event) is lower than a threshold, this event is considered to be an epileptic seizure; otherwise, it is considered as a normal nocturnal movement event. The mean performance over seven patients gives a sensitivity of 95.24% and a positive predictive value of 60.04%. However, there is a noticeable interpatient difference.
Keywords
Accelerometers, home monitoring, hypermotor seizures, novelty detection, AUTOMATED DETECTION, MYOCLONIC SEIZURES, MOVEMENTS, SENSOR

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Chicago
Cuppens, Kris, Peter Karsmakers, Anouk Van de Vel, Bert Bonroy, Milica Milosevic, Stijn Luca, Tom Croonenborghs, et al. 2014. “Accelerometry-based Home Monitoring for Detection of Nocturnal Hypermotor Seizures Based on Novelty Detection.” Ieee Journal of Biomedical and Health Informatics 18 (3): 1026–1033.
APA
Cuppens, K., Karsmakers, P., Van de Vel, A., Bonroy, B., Milosevic, M., Luca, S., Croonenborghs, T., et al. (2014). Accelerometry-based home monitoring for detection of nocturnal hypermotor seizures based on novelty detection. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 18(3), 1026–1033.
Vancouver
1.
Cuppens K, Karsmakers P, Van de Vel A, Bonroy B, Milosevic M, Luca S, et al. Accelerometry-based home monitoring for detection of nocturnal hypermotor seizures based on novelty detection. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS. 2014;18(3):1026–33.
MLA
Cuppens, Kris et al. “Accelerometry-based Home Monitoring for Detection of Nocturnal Hypermotor Seizures Based on Novelty Detection.” IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 18.3 (2014): 1026–1033. Print.
@article{8581151,
  abstract     = {Nocturnal home monitoring of epileptic children is often not feasible due to the cumbersome manner of seizure monitoring with the standard method of video/EEG-monitoring. We propose a method for hypermotor seizure detection based on accelerometers attached to the extremities. From the acceleration signals, multiple temporal, frequency, and wavelet-based features are extracted. After determining the features with the highest discriminative power, we classify movement events in epileptic and nonepileptic movements. This classification is only based on a non-parametric estimate of the probability density function of normal movements. Such approach allows us to build patient-specific models to classify movement data without the need for seizure data that are rarely available. If, in the test phase, the probability of a data point (event) is lower than a threshold, this event is considered to be an epileptic seizure; otherwise, it is considered as a normal nocturnal movement event. The mean performance over seven patients gives a sensitivity of 95.24\% and a positive predictive value of 60.04\%. However, there is a noticeable interpatient difference.},
  author       = {Cuppens, Kris and Karsmakers, Peter and Van de Vel, Anouk and Bonroy, Bert and Milosevic, Milica and Luca, Stijn and Croonenborghs, Tom and Ceulemans, Berten and Lagae, Lieven and Van Huffel, Sabine and Vanrumste, Bart},
  issn         = {2168-2194},
  journal      = {IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS},
  language     = {eng},
  number       = {3},
  pages        = {1026--1033},
  title        = {Accelerometry-based home monitoring for detection of nocturnal hypermotor seizures based on novelty detection},
  url          = {http://dx.doi.org/10.1109/jbhi.2013.2285015},
  volume       = {18},
  year         = {2014},
}

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