In this paper, we propose a low-complexity LSTM-only neural network for HR estimation from a single PPG channel during intense physical activity.
In this paper, we propose a low-complexity LSTM-only neural network for HR estimation from a single PPG channel during intense physical activity. This work ...
Nov 4, 2021 · In this paper, we propose a low-complexity LSTM-only neural network for HR estimation from a single PPG channel during intense physical activity ...
Clinical relevance- This work aims to improve the quality of HR inference from PPG signals using neural network, enabling continuous vital signal monitoring ...
This work explored the trade-off between model complexity and accuracy by exploring different model dataflows, number of layers, and number of training ...
Clinical relevance- This work aims to improve the quality of HR inference from PPG signals using neural network, enabling continuous vital signal monitoring ...
LSTM-only Model for Low-complexity HR Estimation from Wrist PPG. Conference ... Research on heart rate (HR) estimation using wrist-worn photoplethysmography (PPG) ...
Oct 17, 2019 · In this paper, we propose a binarized neural network framework, b-CorNET, to efficiently estimate HR from single-channel wrist PPG signals ...
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Feb 13, 2023 · In this paper, we proposed an end-to-end BVP signal quality evaluation method based on a long short-term memory network (LSTM-SQA).
A novel deep learning framework (CorNET) to efficiently estimate heart rate (HR) information and perform biometric identification (BId) using only a wrist-worn ...