Non-Contact Heartbeat Detection by Heartbeat Signal Reconstruction Based on Spectrogram Analysis With Convolutional LSTM
Heartbeat detection is one of key techniques to monitor our health condition in daily life, and demands for this technique have increased year and year. Thanks to the non-contact and non-invasive features, various Doppler sensor-based detection methods have been investigated so far. However, the hea...
Main Authors: | Kohei Yamamoto, Tomoaki Ohtsuki |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9129737/ |
Similar Items
-
Spectrogram-Based Non-Contact RRI Estimation by Accurate Peak Detection Algorithm
by: Kohei Yamamoto, et al.
Published: (2018-01-01) -
ECG Signal Reconstruction via Doppler Sensor by Hybrid Deep Learning Model With CNN and LSTM
by: Kohei Yamamoto, et al.
Published: (2020-01-01) -
Interpretability Analysis of Heartbeat Classification Based on Heartbeat Activity’s Global Sequence Features and BiLSTM-Attention Neural Network
by: Runchuan Li, et al.
Published: (2019-01-01) -
Doppler Sensor-Based Blink Duration Estimation by Analysis of Eyelids Closing and Opening Behavior on Spectrogram
by: Kohei Yamamoto, et al.
Published: (2019-01-01) -
ECG Heartbeat Classification Using Convolutional Neural Networks
by: Xuexiang Xu, et al.
Published: (2020-01-01)