Detects abnormal events in brain wave data (namely, interictal spikes in EEG data) using a linelength transform algorithm.
Transforms data into linelength then detects events (spikes) surpassing the designated percentile threshold. Note that this function assumes any detections in any channel occurring simultaneously are involved in the same spike event. Based on Estellar et al 2001, DOI 10.1109/IEMBS.2001.1020545 INPUTS d: vector or matrix of ICEEG data and sfx: sampling frequency llw: linelength window (in seconds) over which to calculate transform prc: percentile to use as a threshold for detections badch: logical index of bad channels (1=bad, 0=ok) OUTPUTS ets: matrix of events (rows) and their on/off times (2 columns) in samples ech: logical index of which channels are involved in each detection, thus having the same number of rows (spikes) as ets
Example: [ets,ech]=LLspikedetector(d,512,.04,99.99)
jon.kleen@ucsf.edu 2016-2021
