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Heart Beat Detection and Pulse Demodulation from Emfit Mattress Sensor

Jose Maria Perez-Macias, Mirja Tenhunen, Alpo Värri, Sari-Leena Himanen, and Jari Viik

Published in Computing in Cardiology (CinC), vol. 498, pp. 1–4, 2022. DOI: 10.22489/CinC.2022.285

Ballistocardiography BCG Heart Pulse Demodulation from Emfit Mattress Sensor

Overview

Developing reliable methods to detect heartbeats using non-invasive EMFiT mattress sensors.

Background

Conventional heart monitoring can be intrusive, motivating alternative solutions embedded in everyday sleeping environments, mostly for screening purposes of heart disease, and sleep measurement (sleep architecture, quality, and stress / recovery analysis). Conventional BCG is studied in time. Although there are methods to detect heartbeats, also other domains, the method developed produced a PPG-like signal that is independent on the position of the patient.

Aim

To accurately identify heartbeats from mattress sensor signals, ensuring comfort and minimal disruption. Explore alternative methods and exploit information in the spectral domain.

Methods

Applying spectral analysis and NMF-based source separation (non-negative tensor factorization of the amplitude spectrogram) techniques to isolate and demodulate heart pulse signals.

Results

Preliminary tests show promising accuracy in heartbeat detection, independent of patient position or movement.

📄 Download Open-Access Preprint (PDF)

Cite This Research

CinC Citation: J. M. Perez-Macias, M. Tenhunen, A. Värri, S.-L. Himanen, and J. Viik, "Heart pulse demodulation from Emfit mattress sensor using spectral and source separation techniques," in Computing in Cardiology (CinC), vol. 498, pp. 1–4, 2022, doi: 10.22489/CinC.2022.285. 

@inproceedings{perezmacias2022heart,
  author    = {Perez-Macias, Jose Maria and Tenhunen, Mirja and V{\"a}rri, Alpo and Himanen, Sari-Leena and Viik, Jari},
  title     = {Heart pulse demodulation from Emfit mattress sensor using spectral and source separation techniques},
  booktitle = {2022 Computing in Cardiology (CinC)},
  volume    = {498},
  pages     = {1--4},
  year      = {2022},
  doi       = {10.22489/CinC.2022.285}
}