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Ultrasonography

Ultrasonography

Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called a...

Echo

Echo

The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case, then the...

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BioNet-A: Ultrasonic echo representation network for target discrimination using active SONAR.

Sangwook Park¹, Mounya Elhilali²

¹Department of Electronic and Semiconductor Engineering, Kangwon National University, Gangneung, Gangwon 25457, South Korea.

The Journal of the Acoustical Society of America

|July 1, 2026

Summary

A new biomimetic encoder, BioNet5-A, enhances ultrasonic echo perception by focusing on brief echo segments and multi-scale structures. It outperforms existing methods for object discrimination in biosonar applications.

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Area of Science:

Bioacoustics
Machine Learning
Sensory Neuroscience

Background:

Ultrasonic echoes are crucial for object perception but pose challenges for conventional spectrogram-based models due to their short duration and frequency structure.
Existing biomimetic systems often fail to optimally process these brief echoes or impose unsuitable frequency shift-invariance.

Purpose of the Study:

To introduce BioNet5-A, a novel biomimetic encoder specifically designed to optimize the processing of ultrasonic echoes.
To improve object discrimination and robustness in biosonar-inspired sensing applications.

Main Methods:

Developed BioNet5-A from an autoencoder pretrained on bat vocalizations.
Incorporated spectrotemporal attention, multi-sized convolution modules, and a symmetric encoder-decoder architecture.
Evaluated performance on a controlled ultrasonic dataset with varying objects and noise conditions.

Main Results:

BioNet5-A demonstrated superior performance compared to auditory spectrograms, cortical wavelets, and the conventional BioNet.
Achieved improved echo clustering, discrimination, and robustness against noise.
Generated compact and interpretable representations consistent with bat midbrain physiology.

Conclusions:

BioNet5-A represents a significant advancement in processing ultrasonic echoes for object perception.
The model offers a practical and effective front-end solution for biosonar-inspired sensing and other ultrasonic applications.