Spike detection using a multiresolution entropy based method
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Sajjad Farashi
Abstract
Correct interpretation of neural mechanisms depends on the accurate detection of neuronal activities, which become visible as spikes in the electrical activity of neurons. In the present work, a novel entropy based method is proposed for spike detection which employs the fact that transient spike events change the entropy level of the neural time series. In this regard, the time-dependent entropy method can be used for detecting spike times, where the entropy of a selected segment of a neural time series, using a sliding window approach, is calculated and the time of the events are highlighted by sharp peaks in the output of the time-dependent entropy method. It is shown that the length of the sliding window determines the resolution of the time series in entropy space, therefore, the calculation is performed with a different window length for obtaining a multiresolution transform. The final decision threshold for detecting spike events is applied to the point-wise product of the time dependent entropy calculations with different resolutions. The proposed detection method has been assessed using several simulated and real neural data sets. The results show that the proposed method detects spikes in their exact times while compared with other traditional methods, relatively lower false alarm rate is obtained.
Author Statement
Research funding: Authors state no funding involved.
Conflict of interest: Authors state no conflict of interest.
Informed consent: Informed consent is not applicable.
Ethical approval: The conducted research is not related to either human or animals use.
References
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©2018 Walter de Gruyter GmbH, Berlin/Boston
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- In-service characterization of a polymer wick-based quasi-dry electrode for rapid pasteless electroencephalography
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Articles in the same Issue
- Frontmatter
- Research articles
- A new in vitro spine test rig to track multiple vertebral motions under physiological conditions
- In-service characterization of a polymer wick-based quasi-dry electrode for rapid pasteless electroencephalography
- Spike detection using a multiresolution entropy based method
- Obstacles in using a computer screen for steady-state visually evoked potential stimulation
- Classification of pulmonary pathology from breath sounds using the wavelet packet transform and an extreme learning machine
- Filtering of ECG signals distorted by magnetic field gradients during MRI using non-linear filters and higher-order statistics
- Failure analysis of eleven Gates Glidden drills that fractured intraorally during post space preparation. A retrieval analysis study
- Assessing multiple muscle activation during squat movements with different loading conditions – an EMG study
- In-vivo monitoring of infection via implantable microsensors: a pilot study
- Analysis of structural brain MRI and multi-parameter classification for Alzheimer’s disease
- False spectra formation in the differential two-channel scheme of the laser Doppler flowmeter
- A priori knowledge integration for the detection of cerebral aneurysm
- Is the location of the signal intensity weighted centroid a reliable measurement of fluid displacement within the disc?
- Image-based 3D surface approximation of the bladder using structure-from-motion for enhanced cystoscopy based on phantom data
- Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization
- Quantifying the dynamics of electroencephalographic (EEG) signals to distinguish alcoholic and non-alcoholic subjects using an MSE based K-d tree algorithm
- A hybrid active force control of a lower limb exoskeleton for gait rehabilitation
- Short communication
- Can somatosensory electrical stimulation relieve spasticity in post-stroke patients? A TMS pilot study
