Table 1.
Surface electromyography measurement duration breakdown. Measurements will be recorded in the left tongue and right tongue.
Fig 1.
Tongue HDSEMG data processing pipeline.
Tongue HDSEMG recordings from three patient tasks will be decomposed via DWT, and time-frequency features will be selected using linear discriminant analysis. Voluntary contraction tasks will be decomposed into motor unit spike train estimates using MUEdit, and a CNN will be trained on the resulting MU estimates. A final multitask neural network will make a final CN XII neuropathy prediction from all the data. Abbreviations: HDSEMG, High-density surface electromyography; MU, Motor unit; CNN, Convolutional neural network; WL, Waveform length; ZC, Zero crossings; SSC, Sign slope changes; RMS, Root-mean-square amplitude; MAV, Mean absolute value; IAV, Instantaneous absolute value; AMB, Amplitude-modulated bandwidth; FMB, Frequency-modulated bandwidth; SMPSD, Spectral moment of power spectral density; MFD, Mean first derivative of instantaneous frequency; MIF, mean instantaneous frequency; CN XII, Cranial nerve XII.