Real-Time HR Estimation from wrist PPG using Binary LSTMs

Leandro Giacomini Rocha, Nick Van Helleputte, Muqing Liu, Dwaipayan Biswas, Bram Ernst Verhoef, Sergio Bampi, Chris H. Kim, Chris Van Hoof, Mario Konijnenburg, Marian Verhelst

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Wrist-worn photoplethysmography (PPG) sensors present a popular alternative to electrocardiogram recording for heart rate (HR) estimation. However, their accuracy is limited by motion artifacts inherent in ambulatory settings. In this paper, we propose a binarized neural network framework, b-CorNET, to efficiently estimate HR from single-channel wrist PPG signals during intense physical activity. The model comprises two binary convolution neural network layers followed by two binary long short-Term memory (b-LSTM) layers and a dense layer working on quantized PPG data. The proposed framework achieves an MAE of 3.75±3.05 bpm when evaluated on 12 IEEE SPC subjects. Furthermore, a novel, low-complexity architecture for the b-LSTM layers is proposed and efficiently mapped on a Xilinx Virtex5 FPGA, enabling HR computation.

Original languageEnglish (US)
Title of host publicationBioCAS 2019 - Biomedical Circuits and Systems Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509006175
DOIs
StatePublished - Oct 2019
Event2019 IEEE Biomedical Circuits and Systems Conference, BioCAS 2019 - Nara, Japan
Duration: Oct 17 2019Oct 19 2019

Publication series

NameBioCAS 2019 - Biomedical Circuits and Systems Conference, Proceedings

Conference

Conference2019 IEEE Biomedical Circuits and Systems Conference, BioCAS 2019
CountryJapan
CityNara
Period10/17/1910/19/19

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Keywords

  • Binary LSTM
  • CNN
  • FPGA
  • PPG

Cite this

Rocha, L. G., Helleputte, N. V., Liu, M., Biswas, D., Verhoef, B. E., Bampi, S., Kim, C. H., Van Hoof, C., Konijnenburg, M., & Verhelst, M. (2019). Real-Time HR Estimation from wrist PPG using Binary LSTMs. In BioCAS 2019 - Biomedical Circuits and Systems Conference, Proceedings [8918726] (BioCAS 2019 - Biomedical Circuits and Systems Conference, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIOCAS.2019.8918726