Detection and classification of neuromuscular late wave activity for the assessment of neuromuscular function

A method for detecting and classifying neuromuscular late wave activity so as to assess neuromuscular function in a patient, the method comprising:

• electrically stimulating a nerve;
• measuring the electrical responses of the muscle innervated by the stimulated nerve, and recording the responses as an ensemble of traces;
• identifying, using a computer, time segments in an ensemble of traces, wherein identifying time segments in an ensemble of traces comprises calculating a differential feature component and a mean feature component at every time point along the ensemble of traces and comparing the differential feature component and the mean feature component against thresholds so as to identify time segments in the ensemble of traces;
• classifying, using the computer, the time segments in the ensemble of traces as quiet, A-wave, Repeater wave and/or F-wave segments;
• determining, using the computer, F-wave latency by (i) identifying any masking of an F-wave by an A-wave segment, (ii) where masking occurs, using the differential feature component to differentiate the A-wave from the F-wave and (iii) establishing the F-wave latency from the point at which only the A-wave is present;
• and
• using the F-wave latency to assess neuromuscular function in the patient.

A method for detecting and classifying neuromuscular late wave activity so as to assess neuromuscular function in a patient, the method comprising:

• electrically stimulating a nerve;
• measuring the electrical responses of the muscle innervated by the stimulated nerve, and recording the responses as an ensemble of traces;
• determining, using a computer, a differential feature component and a mean feature component at every time point across an ensemble of traces;
• comparing, using the computer, the differential feature component and the mean feature component against thresholds so as to identify time segments in the ensemble of traces;
• classifying, using the computer, the identified time segments in the ensemble of traces as quiet, A-wave, Repeater wave and/or F-wave segments;
• determining, using the computer, F-wave latency by using the start of the F-wave segment to identify the onset of the F-wave;
• and
• using the F-wave latency to assess neuromuscular function in the patient.