Ambient noise reduction in cerebral near infrared spectroscopy based on frequency division multiplexing

Shahbaz Askari; Zoya Bastany; Roberto Pagano; Guy A. Dumont

doi:10.1117/12.2545214

21 February 2020 Ambient noise reduction in cerebral near infrared spectroscopy based on frequency division multiplexing

Shahbaz Askari, Zoya Bastany, Roberto Pagano, Guy A. Dumont

Author Affiliations +

Proceedings Volume 11237, Biophotonics in Exercise Science, Sports Medicine, Health Monitoring Technologies, and Wearables; 1123703 (2020) https://doi.org/10.1117/12.2545214
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Near-Infrared Spectroscopy (NIRS) is a non-invasive technique, extensively used to monitor the hemodynamic variations in cerebral neuronal tissues. For cerebral NIRS, the back-scattering probe is more prevailing, in which an incident beam is diffused, and only a slight fraction of the source optical energy reaches the light detectors. Multiplexing in the time domain is the conventional method used to distinguish the optical density of each NIR source at the receiver site. Even though time-multiplexing is straightforward and convenient, the ambient light can significantly contaminate the NIR beams during the sampling-path from the source to the detector. In this work, we present a novel method based on frequency division multiplexing (FDM) to overcome the interference of ambient light even without an external optical filter. The method proposes to modulate the NIR source intensities by using specific carrier frequencies distinct from the dominant frequency components of ambient light intensity. By modulating the intensity of each NIR source, and applying them at their specific frequency channels, the receiver is capable of distinguishing the received optical signals based on their frequency channel. Because the frequency channels are adjusted at distinct dominant frequency components of the ambient intensity, the latter ambient noise can be filtered out instantly. The method has been implemented by using electronic circuit design and evaluated both by numerical simulation and experimental measurements. The signal to noise ratio (SNR) has been improved at least by 45dB.

Conference Presentation

Citation Download Citation

Shahbaz Askari, Zoya Bastany, Roberto Pagano, and Guy A. Dumont "Ambient noise reduction in cerebral near infrared spectroscopy based on frequency division multiplexing", Proc. SPIE 11237, Biophotonics in Exercise Science, Sports Medicine, Health Monitoring Technologies, and Wearables, 1123703 (21 February 2020); https://doi.org/10.1117/12.2545214

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