An apparatus for detecting seizures with motor manifestations, the apparatus comprising: one or more EMG electrodes capable of providing an EMG signal substantially representing seizure-related muscle activity; a processor (26; 30) configured to receive the EMG signal, process the EMG signal to determine whether a seizure may be occurring, and generate an alert if a seizure is determined to be occurring based on the EMG signal; said processor being configured to detect bursts of EMG signal data, assign certainty values to individual burst members among said detected bursts, and weight the number of said detected bursts as a function of the certainty value assigned to said individual burst members; wherein said certainty values are determined based on a comparison of said individual burst members to a reference burst in terms of one or more burst characteristics selected from the group of characteristics including burst signal-to-noise ratio, burst width and burst amplitude; said processor being further configured to periodically scan a buffer in computer memory and identify the presence of a plurality of bursts over a time window, and determine the periodicity of burst characteristics over said time window; and said processor further configured to combine said burst count contribution and said periodicity contribution using a supervisory algorithm to determine a seizure detection value based on the certainty value weighted number of detected bursts and the periodicity of the burst characteristics, and compare said seizure detection value to a threshold seizure detection value suitable to indicate if said seizure is occurring. one or more EMG electrodes capable of providing an EMG signal substantially representing seizure-related muscle activity; a processor (26; 30) configured to receive the EMG signal, process the EMG signal to determine whether a seizure may be occurring, and generate an alert if a seizure is determined to be occurring based on the EMG signal; said processor being configured to detect bursts of EMG signal data, assign certainty values to individual burst members among said detected bursts, and weight the number of said detected bursts as a function of the certainty value assigned to said individual burst members; wherein said certainty values are determined based on a comparison of said individual burst members to a reference burst in terms of one or more burst characteristics selected from the group of characteristics including burst signal-to-noise ratio, burst width and burst amplitude; said processor being further configured to periodically scan a buffer in computer memory and identify the presence of a plurality of bursts over a time window, and determine the periodicity of burst characteristics over said time window; and said processor further configured to combine said burst count contribution and said periodicity contribution using a supervisory algorithm to determine a seizure detection value based on the certainty value weighted number of detected bursts and the periodicity of the burst characteristics, and compare said seizure detection value to a threshold seizure detection value suitable to indicate if said seizure is occurring.