Design and Implementation of a FPGA-Based Airborne Ultrasound Sensing and Radiation Phased Array Device

The ultrasonic phased array system, known for its ability to transmit and receive ultrasound, has been widely utilized in medical ultrasonic imaging. Recently, several novel air-based applications have emerged, such as object levitation, directional acoustics, and tactile feedback, expanding the potential for next-generation human-machine interfaces. Ultrasonic phased arrays not only provide sensory stimuli like vision and hearing but also deliver tactile sensations to users. By integrating the capability to receive ultrasound reflections, the system enables functionalities like gesture recognition and posture verification. Despite these advancements, a key challenge remains: can ultrasonic phased arrays offer sufficient range and acoustic radiation force to support these new applications? Additionally, traditional air-based ultrasonic phased arrays are typically limited to transmission and lack the ability to receive echo signals. To overcome these limitations, we propose a new ultrasonic phased array system designed for rapid scaling and implementation in existing applications. Our system incorporates the ability to receive ultrasound echoes, a feature absent in conventional designs. This new capability, coupled with the future integration of deep learning algorithms, holds great promise for enhancing features like gesture recognition. Moreover, the system operates at higher voltages to increase acoustic radiation pressure and includes a faster communication interface to minimize control delays. This improved bandwidth for receiving signals makes it a superior platform for advancing ultrasonic phased array research.

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Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1109/uffc-js60046.2024.10793807
Citations
3
Primary Topic
Engineering Applied Research
Type
article
Field-Weighted Citation Impact
0.78
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article

Design and Implementation of a FPGA-Based Airborne Ultrasound Sensing and Radiation Phased Array Device

Hao‐Li Liu, Guowei Hong, C. T. Li, Mei Yang
3 citations
Engineering Applied Research
0.78
article

Design and Implementation of a FPGA-Based Airborne Ultrasound Sensing and Radiation Phased Array Device

Hao‐Li Liu, Guowei Hong, C. T. Li, Mei Yang
article en
3 citations

Abstract

The ultrasonic phased array system, known for its ability to transmit and receive ultrasound, has been widely utilized in medical ultrasonic imaging. Recently, several novel air-based applications have emerged, such as object levitation, directional acoustics, and tactile feedback, expanding the potential for next-generation human-machine interfaces. Ultrasonic phased arrays not only provide sensory stimuli like vision and hearing but also deliver tactile sensations to users. By integrating the capability to receive ultrasound reflections, the system enables functionalities like gesture recognition and posture verification. Despite these advancements, a key challenge remains: can ultrasonic phased arrays offer sufficient range and acoustic radiation force to support these new applications? Additionally, traditional air-based ultrasonic phased arrays are typically limited to transmission and lack the ability to receive echo signals. To overcome these limitations, we propose a new ultrasonic phased array system designed for rapid scaling and implementation in existing applications. Our system incorporates the ability to receive ultrasound echoes, a feature absent in conventional designs. This new capability, coupled with the future integration of deep learning algorithms, holds great promise for enhancing features like gesture recognition. Moreover, the system operates at higher voltages to increase acoustic radiation pressure and includes a faster communication interface to minimize control delays. This improved bandwidth for receiving signals makes it a superior platform for advancing ultrasonic phased array research.

National Taiwan University (TW)
Affordable and clean energy
Openalex Percentile: Top 29%
Engineering Applied Research
0.78
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