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[TNSRE 2021] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"
A survey and paper list of current Diffusion Model for Time Series and SpatioTemporal Data with awesome resources (paper, application, review, survey, etc.).
可以在README此页中搜索自己想找的代码资源
BNO055 library to use with STM32 HAL
Library for the Bosch BNO055 Sensor based on and used with the STM32-HAL.
CBLSNet: A concise feature context fusion network for sleep staging
The supplementary material for the paper: Automatic sleep-stage classification of heart rate and actigraphy data using deep and transfer learning approaches
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
墨墨背单词,每日分享链接访问脚本,提高单词上限。
DIY Watch based on ESP32-S3 and Amoled screen
DATA'20 - PPGraw is an analytical tool for the quality review of raw photoplethysmography (PPG) signals, based on 7 multi-varied decision metrics. It has been applied in the review of 10 publicly available photoplethysmography datasets.
Classify sleep from heart rate and acceleration via Apple Watch
Code for the paper published in Deep Generative Models for Health Workshop at the Neurips 2023.
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College London respectively
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG
Official PyTorch implementation of TSDiff models presented in the NeurIPS 2023 paper "Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting"
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