Heart rate variability estimation with joint accelerometer and gyroscope sensing
: Olli Lahdenoja, Tero Hurnanen, Mojtaba Jafari Tadi, Mikko Pänkäälä, Tero Koivisto
: Alan Murray
: Computers in Cardiology (CinC)
: 2016
: Computing in Cardiology
: Computing in Cardiology Conference (CinC), 2016
: 43
: 717
: 720
: 4
: 978-1-5090-0896-4
: 978-1-5090-0895-7
: 2325-887X
DOI: https://doi.org/10.22489/CinC.2016.209-166
: http://ieeexplore.ieee.org/document/7868843/
: https://research.utu.fi/converis/portal/detail/Publication/17391066
This paper describes a method for estimation of heart rate (HR) and heart rate variability (HRV) with accelerometers and gyroscopes. We denote this joint seismocardiography (SCG) and gyrocardiography (GCG) approach as SCG/GCG. In principle, SCG which is a well known method measures the linear mechanical movements of the heart and GCG is a new technique which measures angular motion due to the chest micro-vibrations caused by myocardial rotation. As electrocardiography (ECG), they can also be performed in non-invasive manner using a device in contact to subjects skin, for example. Our method extracts HRV parameters based on single-axis and multi-axes autocorrelation analysis (1-AC and 6-AC) of all simultaneously captured SCG/GCG axes. The results of each axes are combined to maintain reliable HR- and HRV. We validate our results with a comparison study between simultaneous ECG and SCG/GCG recordings using a study group of 29 healthy male volunteers. The study provides a promising approach for HRV estimation with modern wearable devices.