Research Content

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Ultrasonic haptics is a technology that uses high-intensity ultrasonic focusing to generate tactile feedback, which is characterized by non-contact and high resolution. The realization method is to transmit a signal through a sensor array with a frequency of 40kHz. By adjusting the emission time difference of each sensor, the focus is formed in the air, and the user can feel the tactile sensation at the focus through the modulation of the signal.

The traditional sensor array used for tactile sensing is too large to be integrated into general commercial products. Therefore, our laboratory is committed to designing and manufacturing piezoelectric micro ultrasonic sensors (PMUT) that can generate high-intensity ultrasonic waves, in order to greatly reduce the size. The size of the ultrasonic tactile device allows it to be widely used in touch panels or display interfaces.

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    Miniature piezoelectric ultrasonic sensor (PMUT) is a new type of sensor in micro electromechanical system. Different from the traditional bulk piezoelectric sensor, PMUT uses a piezoelectric film to couple to a vibrating structure. When an electrical signal is applied, the element will start to vibrate and then emit ultrasonic waves. If ultrasonic waves are applied, the element It will be converted into a telephony signal. In the element structure, the response frequency of the sensor is determined by the thickness of the structure layer rather than the thickness of the piezoelectric material itself, which brings greater design flexibility. Although the current output power of PMUT is still less than that of traditional piezoelectric sensors, it has the advantages of greater flexibility in structural design, good impedance matching in water and low input voltage, so it is very likely to become a new generation of ultrasound in the future Sensor element.

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    Photoacoustic image (PAI) is a non-invasive imaging method that has been widely used in biomedical imaging. Its principle is to use a laser light source to excite tissues to generate ultrasound. As shown in Figure 1, first, pulsed laser light is used to irradiate the imaging area, a part of the light is absorbed by the tissue and converted into heat energy, which produces elastic expansion and emits broadband (MHz grade) ultrasonic waves. Then, through the self-developed transparent The flexible ultrasonic receiver converts the sound wave signal into a voltage, and then reconstructs the collected signal with a program to convert it into an image. Figure 2 shows the model to be scanned. The reconstructed image of the ultrasonic wave received by the receiver after signal processing is shown in Figure 3. It can be clearly seen that the image and the scanned model are consistent with the imaging at various angles.

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    The photoacoustic imaging system is a deep imaging system with the advantages of high-resolution real-time imaging. At present, more and more biomedical researches use photoacoustic imaging as a method of observing experimental results. Although photoacoustic imaging has been widely used in various biological experiments conducted in laboratories, there is still a long way to go before it is applied to consumer electronic products such as smart watches or mobile phones. Among them, the most difficult problem to be overcome is The need for high-resolution pulsed lasers and light-speed scanning mechanisms, so this research will explore how to use deep learning methods to reduce the demand for pulsed laser sources.

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Using the ultrasonic array temperature measurement method, dozens of ultrasonic transmission paths are generated in the target area (Figure 1), and based on the measured sound velocity of each path and its relationship with the temperature of the medium, appropriate reconstruction algorithms are developed Draw out the gas temperature at each point on the two-dimensional plane (Figure 2).

        According to the research results, it is found that the algorithm using the hexagonal grid can track the hot spot distribution most accurately (Figure 3), and meanwhile, the average temperature error on all sound velocity paths is less than 1%, and the hot spot movement relative to the area diameter of 3% is sensed. (Figure 4).

本研究係利用12顆超音波傳感器排成一個環形陣列，並搭配自行設計之發射/接收電路，以單顆傳感器作為發射端，其他傳感器作為接收端的方式，進行12次的量測實驗(圖一)，經資料處理後，可以得到共66組的聲波傳播速度，再透過本實驗室提出之二維超音波溫度分佈重建演算法，達到以超音波量測平面場氣溫的目標(圖二) 。整體系統架構如圖三所示，目前研究進展到「接收訊號優化」的部分。

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Ultrasonic waves are mechanical waves transmitted by a medium, and their attenuation speed in the water is very low. Therefore, they have the advantages of being able to pass through suspended particles and have minimal impact on the culture in the breeding field, and the imaging mechanism of ultrasonic waves is hardly affected. The influence of light, water color, and turbidity has great potential for development in the field of smart aquaculture.

This research develops a white shrimp ultrasonic image recognition system, which mainly uses the Verasonics system (Figure 1) to capture ultrasonic images (Figure 2), and first inputs the images into a Convolutional Neural Network (CNN) , Capture the image features, and then input the neural network model for training, the trained model (Figure 3) will be able to classify according to the image.

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    The purpose of this research is to control the frequency and intensity of ultrasonic waves to produce ultrasonic cavitation in the water, thereby inhibiting or promoting the growth of specific algae in the water. The realization method is to fix multiple piezoelectric slices around the algae test tube, and connect the piezoelectric slices to a portable ultrasonic algae growth control circuit made in the laboratory. This circuit can output a variety of control signals to the piezoelectric slices, causing them to vibrate and generate vibrations. Apply ultrasonic waves of different frequencies and intensities to the algae. According to the number of algae before and after the experiment, the effect of ultrasound on the growth of algae can be analyzed.

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      EIT electrical impedance imaging (Electrical Impedance Tomography, EIT) is a noninvasive (noninvasive) technique for reconstructing images of human internal tissues, which can display images of human internal tissues in real time. As shown in Figure 1, with the known injection current (I) and the preset impedance distribution (Ω), the voltage distribution (Φ) is obtained by solving the Forward Problem (α), and the voltage distribution (Φ) is compared with the voltage measured by the electrode (V After the comparison, the impedance distribution (ρ) is obtained by solving the Inverse Problem (b), and this process is repeated until the difference between the voltage distribution and the measured voltage is the smallest.

Through the combination of Matlab and Python, this laboratory integrates hardware and 2D and 3D image reconstruction algorithms and user interface (GUI) (Figures 2, 3, and 4) to realize the software architecture of the wearable EIT system, which will be used in the future. The aspect continues to extend.

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Ultrasonic imaging is often used as a means of observing animal muscles and internal organs in biomedical experiments. However, because the machine is not easy to move, it is often necessary to transport the experiment body to the machine room and anesthetize it. During the transportation and anesthesia process, the experiment body is often killed or injured. The goal of this research is to design a wireless backpack-type ultrasonic image capture device for small experimental animals.

In this experiment, the LabVIEW program is used to control the scanning mirror module and the pulse transmitter receiver, to perform pulse sound wave scanning and signal acquisition on the experimental body, reconstruct the ultrasonic image and send it back to the experimenter at regular intervals. This program can also adjust the sound wave signal gain To enhance or attenuate images of a specific depth.

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本研究使用Python開發一套系統，透過深度攝影機(Azure Kinect)與電腦，將系統架設於健身房，以此系統辨識人體骨架，將其骨架與時間之間的關係輸入到機器學習模型當中的來判斷學員每一次深蹲的好壞，並可以在系統上回放每一次的深蹲搭配模型預測的結果，讓學員透過影片了解其動作的哪裡需要改善，提供教練與學員更良好的教學環境。

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本研究專注於開發一個基於深度學習的系統，將目標追蹤技術(YOLOv4-tiny)和加速度計（Xsense.dots）結合起來，以實現游泳過程中的實時自動分段計時和顯示加速度信息。旨在提高游泳者的訓練效率，使教練和運動員能夠評估他們的表現並相應地調整他們的練習方法。

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    The purpose of this research is to control the frequency and intensity of ultrasonic waves to produce ultrasonic cavitation in the water, thereby inhibiting or promoting the growth of specific algae in the water. The realization method is to fix multiple piezoelectric slices around the algae test tube, and connect the piezoelectric slices to a portable ultrasonic algae growth control circuit made in the laboratory. This circuit can output a variety of control signals to the piezoelectric slices, causing them to vibrate and generate vibrations. Apply ultrasonic waves of different frequencies and intensities to the algae. According to the number of algae before and after the experiment, the effect of ultrasound on the growth of algae can be analyzed.

The transportation of objects or liquids without physical contact is an innovative technology required by a new generation of new intelligent machinery. In addition to reducing the pollution and loss caused by the physical contact between the carrier and the transported object, it can also be used today. Fine operations that are difficult to achieve with robotic arms. Among them, Acoustic Levitation is the least restricted non-contact transportation method.

The levitation device system of this study is shown in Figure 1. There is an array of acoustic wave sensors on the top and bottom, which are placed face to face to generate standing waves. The distance between the two must be a multiple of half the wavelength. If the size of the object is less than half the wavelength and the weight is less than the sound pressure. The sound radiation force, the object will be able to be stably suspended in the medium. Figure 2 is a photo of an actual suspended object, and Figure 3 is a two-dimensional sound pressure distribution diagram measured by a high-frequency sound pressure microphone.