A Wearable System with Embedded Conductive Textiles and an IMU for Unobtrusive Cardio-Respiratory Monitoring

Abstract

The continuous and simultaneous monitoring of physiological parameters represents a key aspect in clinical environments, remote monitoring and occupational settings. In this regard, respiratory rate (RR) and heart rate (HR) are correlated with several physiological and pathological conditions of the patients/workers, and with environmental stressors. In this work, we present and validate a wearable device for the continuous monitoring of such parameters. The proposed system embeds four conductive sensors located on the user's chest which allow retrieving the breathing activity through their deformation induced during cyclic expansion and contraction of the rib cage. For monitoring HR we used an embedded IMU located on the left side of the chest wall. We compared the proposed device in terms of estimating HR and RR against a reference system in three scenarios: sitting, standing and supine. The proposed system reliably estimated both RR and HR, showing low error averaged along subjects in all scenarios. This is the first study focused on the feasibility assessment of a wearable system based on a multi-sensor configuration (i.e., conductive sensors and IMU) for RR and HR monitoring. The promising results encourage the application of this approach in clinical and occupational settings.

Keywords: IMU; cardio-respiratory monitoring; heart rate; respiratory rate; smart textile; wearable device; wearable system.

Figure 1

Schematic representations of the proposed wearable system and the reference system, and their positioning on the rib cage.

Figure 2

A schematic representation of the experimental protocol performed. The top trend represents the respiratory trial performed in the 3 tested scenarios shown in the lower part.

Figure 3

A schematic representation of the breathing act period $\Delta T_{rr}\left[n\right]$. The blue line represents $r_{WS}\left(t\right)$, and the red circles represent the identified respiratory peaks.

Figure 4

nPSD of $r_{ref}$ (left) and $r_{WS}$ (right) a representative subjects in each scenario.

Figure 5

$r_{ref}$ (left) and $r_{WS}$ (right) plotted over time for all scenarios using a representative subject. Peaks selected using the method presented in Section 5 were superimposed on the signals (red circles).

Figure 6

Plot related to Bland-Altman analysis for each scenario. Each plot contains all breath-by-breath RR values estimated for each subject. $\Delta f_{RR}=f_{ref}^{RR}\left[n\right]-f_{WS}^{RR}\left[n\right]$, and $f_{mean}^{RR}=\frac{f_{ref}^{RR}\left[n\right]+f_{WS}^{RR}\left[n\right]}{2}$, for n-th breath estimated.

Figure 7

PSD of $h_{ref}$ (left) and $h_{g_x}$ (right) for a representative subject and all scenarios.