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. 2022 Jul 20;12(7):541.
doi: 10.3390/bios12070541.

Millimeter Wave-Based Non-Destructive Biosensor System for Live Fish Monitoring

Affiliations

Millimeter Wave-Based Non-Destructive Biosensor System for Live Fish Monitoring

Meng Wang et al. Biosensors (Basel). .

Abstract

Waterless transportation for live grouper is a novel mode of transport that not only saves money, but also lowers wastewater pollution. Technical obstacles remain, however, in achieving intelligent monitoring and a greater survival rate. During live grouper waterless transportation, the stress response is a key indicator that affects the survival life-span of the grouper. Studies based on breathing rate analysis have demonstrated that among many stress response parameters, breathing rate is the most direct parameter to reflect the intensity. Conventional measurement methods, which set up sensors on the gills of groupers, interfere with the normal breathing of living aquatic products and are complex in system design. We designed a new breathing monitoring system based on a completely non-destructive approach. The system allows the real-time monitoring of living aquatic products' breathing rate by simply placing the millimeter wave radar on the inner wall of the incubator and facing the gills. The system we developed can detect more parameters in the future, and can replace the existing system to simplify the study of stress responses.

Keywords: breathing rate; grouper; millimeter wave radar; non-destructive; waterless transportation.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The whole procedure of the waterless transportation for live grouper.
Figure 2
Figure 2
Schematic diagram of NDBRMS with the sensor fixed to the inner wall of the incubator and the radar antenna facing the gills.
Figure 3
Figure 3
Prototype of the AWR1642 BOOST. (a) front view; (b) back view.
Figure 4
Figure 4
Data processing scheme. The sensor uses a frequency set to capture 20 times per second and is processed to determine the final breathing rate.
Figure 5
Figure 5
Comparison of the effects of manual observation and the NDBRMS system for measuring breathing rate.
Figure 6
Figure 6
Breathing signal filtering and PI in preliminary experiments. (a) Breathing signal phase waveform at 4 °C; (b) Breathing signal spectrum at 4 °C; (c) Breathing signal phase waveform at 7 °C; (d) Breathing signal spectrum at 7 °C; (e) Breathing signal phase waveform at 10 °C; (f) Breathing signal spectrum at 10 °C; (g) Breathing signal phase waveform at 12 °C; (h) Breathing signal spectrum at 12 °C. The blue solid line represents the filtered, the black dashed line represents the measured original and the red stars represent the local maximum used to calculate the respiration rate.
Figure 7
Figure 7
(a) Two-hour ‘normal’ breathing rate change curve; (b) Breathing signal phase waveform and its spectrum at 10 min; (c) Breathing signal phase waveform and its spectrum at 120 min; (d) Breathing signal phase waveform and its spectrum at 40 min; (e) Breathing signal phase waveform and its spectrum at 70 min.

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