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. 2018 Mar 25;18(4):973.
doi: 10.3390/s18040973.

A Portable Wireless Communication Platform Based on a Multi-Material Fiber Sensor for Real-Time Breath Detection

Mourad Roudjane  1 , Simon Bellemare-Rousseau  2 , Mazen Khalil  3   4 , Stepan Gorgutsa  5 , Amine Miled  6 , Younes Messaddeq  7
Affiliations

A Portable Wireless Communication Platform Based on a Multi-Material Fiber Sensor for Real-Time Breath Detection

Mourad Roudjane et al. Sensors (Basel). .

Abstract

In this paper, we present a new mobile wireless communication platform for real-time monitoring of an individual's breathing rate. The platform takes the form of a wearable stretching T-shirt featuring a sensor and a detection base station. The sensor is formed by a spiral-shaped antenna made from a multi-material fiber connected to a compact transmitter. Based on the resonance frequency of the antenna at approximately 2.4 GHz, the breathing sensor relies on its Bluetooth transmitter. The contactless and non-invasive sensor is designed without compromising the user's comfort. The sensing mechanism of the system is based on the detection of the signal amplitude transmitted wirelessly by the sensor, which is found to be sensitive to strain. We demonstrate the capability of the platform to detect the breathing rates of four male volunteers who are not in movement. The breathing pattern is obtained through the received signal strength indicator (RSSI) which is filtered and analyzed with home-made algorithms in the portable system. Numerical simulations of human breath are performed to support the experimental detection, and both results are in a good agreement. Slow, fast, regular, irregular, and shallow breathing types are successfully recorded within a frequency interval of 0.16-1.2 Hz, leading to a breathing rate varying from 10 to 72 breaths per minute.

Keywords: human breath monitoring; multi-material fibers; smart textile; wearable system.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Schematic representation of the working principle: (a) Breathing sensor is placed on the chest of the simulated human body (SHB); (b) the sensor is stitched onto the elastic textile and it follows the movements of the chest wall, inducing a deformation of the spiral fiber antenna shape; (c) the sensor is strained by the chest movements, so the transmitted signal changes during breath; (d) the signal is detected wirelessly by a base station.
Figure 2
Figure 2
Prototype of the breath sensor made from a polyimide-coated hollow-core silica fiber antenna connected to a Bluetooth transmitter and integrated into a stretchable T-shirt.
Figure 3
Figure 3
(a) Measured (red) and simulated (black) return loss (S11) for the spiral antenna. (b) Three-dimensional (3D) plot of the spiral antenna’s gain in the x, y, and z directions obtained using ANSYS software.
Figure 4
Figure 4
Schematic representation of the induced deformations applied to the spiral fiber antenna: (a) stretching, (b) compressing, (c) bending, and (d) folding. Simulations were performed using ANSYS.
Figure 5
Figure 5
Resonant frequency shift of the spiral fiber antenna in free space as a function of the induced stretching (a), compressing (b), bending (c), and folding (d) deformations.
Figure 6
Figure 6
Resonant frequency shift of the textile-integrated spiral fiber antenna as a function of the induced stretch on the SHB and in free space.
Figure 7
Figure 7
Experimental layout: volunteer wearing the smart textile and standing up in front of the base station.
Figure 8
Figure 8
(a) Breathing signal from received signal strength indicator (RSSI) measurements (blue) and the filtered signal using a Butterworth filter (red). (b) Simulated RSSI calculated for the SHB during the breath.
Figure 9
Figure 9
Output of fast Fourier transform for breath measurements.
Figure 10
Figure 10
Breathing signal patterns obtained from the RSSI measurements (blue) and the corresponding filtered signals (red) for slow (a), shallow (b), irregular (c), fast (d) and a combination of no and deep long breathing (e).
Figure 11
Figure 11
Output of Fourier transform for slow (a), shallow (b), irregular (c) and fast breathing (d).
See this image and copyright information in PMC

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