Article
Feasibility of Heart Rate and Respiratory Rate
Estimation by Inertial Sensors Embedded in a Virtual
Reality Headset
Claudia Floris
1
, Sarah Solbiati
1
, Federica Landreani
1
, Gianfranco Damato
2
, Bruno Lenzi
2
,
Valentino Megale
2
and Enrico Gianluca Caiani
1,3,
*
1
Electronics, Information and Bioengineering Dpt., Politecnico di Milano, 20133 Milano, Italy;
claudia.floris@polimi.it (C.F.); sarah.solbiati@polimi.it (S.S.); federica.landreani@polimi.it (F.L.)
2
Softcare Studios Srls, 00137 Rome, Italy; g.damato@softcarestudios.com (G.D.);
b.lenzi@softcarestudios.com (B.L.); v.megale@softcarestudios.com (V.M.)
3
Consiglio Nazionale delle Ricerche, Istituto di Elettronica e di Ingegneria dell’Informazione e delle
Telecomunicazioni, 20133 Milano, Italy
* Correspondence: enrico.caiani@polimi.it
Received: 5 November 2020; Accepted: 12 December 2020; Published: 14 December 2020
Abstract:
Virtual reality (VR) headsets, with embedded micro-electromechanical systems, have the
potential to assess the mechanical heart’s functionality and respiratory activity in a non-intrusive way
and without additional sensors by utilizing the ballistocardiographic principle. To test the feasibility
of this approach for opportunistic physiological monitoring, thirty healthy volunteers were studied at
rest in different body postures (sitting (SIT), standing (STAND) and supine (SUP)) while accelerometric
and gyroscope data were recorded for 30 s using a VR headset (Oculus Go, Oculus, Microsoft, USA)
simultaneously with a 1-lead electrocardiogram (ECG) signal for mean heart rate (HR) estimation.
In addition, longer VR acquisitions (50 s) were performed under controlled breathing in the
same three postures to estimate the respiratory rate (RESP). Three frequency-based methods
were evaluated to extract from the power spectral density the corresponding frequency. By the
obtained results, the gyroscope outperformed the accelerometer in terms of accuracy with the gold
standard. As regards HR estimation, the best results were obtained in SIT, with R
s
2
(95% confidence
interval) = 0.91 (0.81
−
0.96) and bias (95% Limits of Agreement)
−
1.6 (5.4) bpm, followed by STAND,
with R
s
2
= 0.81 (0.64
−
0.91) and
−
1.7 (11.6) bpm, and SUP, with R
s
2
= 0.44 (0.15
−
0.68) and 0.2 (19.4)
bpm. For RESP rate estimation, SUP showed the best feasibility (98%) to obtain a reliable value from
each gyroscope axis, leading to the identification of the transversal direction as the one containing
the largest breathing information. These results provided evidence of the feasibility of the proposed
approach with a degree of performance and feasibility dependent on the posture of the subject,
under the conditions of keeping the head still, setting the grounds for future studies in real-world
applications of HR and RESP rate measurement through VR headsets.
Keywords:
heart rate; respiratory rate; virtual reality headsets; gyroscope; accelerometer;
ballistocardiography
1. Introduction
Virtual reality (VR) and augmented reality headsets represent state-of-the-art technologically
advanced systems able to simulate real-word interactive experience through a combination of
technologies [
1
]. In particular, in the last 25 years, VR technologies have been expanded to cover a
vast range of applications [
2
] with a widespread use also in the healthcare sector [
3
], ranging from
physical rehabilitation [
4
] to psychiatric treatment for anxiety disorders (such as specific phobias and
Sensors 2020, 20, 7168; doi:10.3390/s20247168 www.mdpi.com/journal/sensors
