University of Twente Student Theses
Vital Signs Monitoring Using a 26 GHz OFDM Multibeam Testbed
Sellés Valls, Miquel (2022) Vital Signs Monitoring Using a 26 GHz OFDM Multibeam Testbed.
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| Abstract: | This paper presents a novel pipeline for vital sign monitoring using a 26 GHz OFDM multi-beam testbed. In the context of Joint Communication and Sensing (JCAS), the advanced communication capability at millimeter-wave bands is comparable to the radio resource of radars and hence is able to sense the surrounding environment while communicating. The proposed processing pipeline leverages 20 MHz and 16 spatially orthogonal beams with 7 ◦ Half Power Beam Width (HPBW) to estimate vital sign activity in single and multi-person static scenarios directly from raw Channel State Information (CSI) samples. The proposed pipeline employing phase time-frequency calibration methods and Discrete Wavelet Transform (DWT) to improve the performance of conventional Fast Fourier Transform (FFT) based methods in single person scenario is described in detail. A frequency-domain comparison between single and multi-person scenarios is also studied and a k−means clustering algorithm introduced to extract breath and heartbeat frequency rates from static persons. According to experimental results, individual transmit (Tx) and receive (Rx) pair links can achieve below 2 bpm error in static single-person monostatic configuration when compared directly to the ground-truth, for both breath and heartbeat activity using the proposed DWT method for a human seating in front and up to 2 m from the Tx/Rx. In static multi-person configuration, individual Tx and Rx pair links achieve less than 2 bpm estimation error in a JCAS scenario employing the proposed joint FFT and k-means method, when two humans are seating at distances below 4 m from the Rx. The presented research work is a promising first step in vital signs monitoring using an active mmWave multibeam communication system, which is promising for practical JCAS applications. |
| Item Type: | Essay (Master) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Programme: | Electrical Engineering MSc (60353) |
| Link to this item: | https://purl.utwente.nl/essays/93688 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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