DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG - aascode/deepsleepnet
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG - GitHub - genaris/deepsleepnet: DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
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. [paper][github]
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG - GitHub - zhangfeng026/deepsleepnet: DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG - deepsleepnet/deepsleep/trainer.py at master · akaraspt/deepsleepnet
本篇论文贴心地给出了实现代码:https://github.com/akaraspt/deepsleepnet 早期的睡眠评分阶段,主要依赖于专家制定的评分规则(评分规则主要有: AASM 和 R&K),然后对照 PSG 的记录结果来进行睡眠分阶。这个过程往往是冗长乏味的,十分耗时的。而 DeepSleepNet 模型是基于原始单通道 EEG 的自动睡眠阶段评分模型,完全...
# # https://github.com/fchollet/keras/blob/master/keras/preprocessing/image.py # # TODO # pass # channel shift def channel_shift(x, intensity, is_random=False, channel_index=2): """Shift the channels of an image, randomly or non-randomly, see `numpy.rollaxis <https://docs....
1. Setup an eAE cluster (follows the instruction in this [link](https://github.com/aoehmichen/eae-docker)) 2. Setup a MongoDB 3. Change location of MongoDB in `deepsleep/trainer.py` 4. Modify `submit_eAE.py` 5. Run `python submit_eAE.py` ## Citation ## If you find this useful...
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG - GitHub - ddl0/deepsleepnet: DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
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. [paper][github]