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TF-C Pretrain EMG

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posted on 2022-05-31, 03:01 authored by Xiang ZhangXiang Zhang, Ziyuan ZhaoZiyuan Zhao, Theodoros Tsiligkaridis, Marinka Zitnik

- Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency

- Paper link: 

- Github repo: https://github.com/mims-harvard/TFC-pretraining

- Project website: 


Electromyograms (EMG) measures muscle responses as electrical activity to neural stimulation, and they can be use to diagnose certain muscular dystrophies and neuropathies. EMG consists of single-channel EMG recording from the tibialis anterior muscle of three volunteers that are healthy, suffering from neuropathy, and suffering from myopathy, respectively. The recordings are sampled with the frequency of 4K Hz. Each patient, i.e., their disorder, is a separate classification category. Then the recordings are split into time series samples using a fixed-length window of 1,500 observations.

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