A flexible ultrasonic array transducer able to be attached to the body has the potential to achieve long-term continuous unconstrained ultrasound (US) imaging. However, the quality of reconstructed US images is affected by the accuracy of the estimated array shape because the array shape is primitive for time-delay calculation in delay-and-sum beamforming. In this study, we propose an algorithm for estimating the array shape only from the backscattered US signal without using any external device. The proposed algorithm is based on the assumption that beam-summed images reconstructed using an array shape estimated at higher accuracy would have smaller entropy. The array shape is estimated by searching for the shape with minimal entropy, which was used as the index of the beam-summed image quality. Simulation experiments and phantom experiments were used to evaluate the proposed algorithm. In the simulation experiments, three different array shapes with 2.0 MHz, 20 elements, and 0.8 mm pitch transducers were estimated. In the phantom experiments, the array shapes of commercially available linear, convex, and concave transducers were estimated. The results showed that the proposed algorithm can estimate the correct array shape with an average element position error of less than one-eighth of the wavelength of the transmitted signals. These results indicate that the proposed algorithm can achieve sufficiently accurate shape estimation and has the potential to enable clear US imaging with flexible array transducers.

Conventionally, ultrasound (US) diagnosis is performed using hand-held rigid probes. Such devices are difficult to be used for long-term monitoring because they need to be continuously pressed against the body to remove the air between the probe and body. Flexible probes, which can deform and effectively adhere to the body, are a promising technology for long-term monitoring applications. However, owing to the flexible element array geometry, the reconstructed image becomes blurred and distorted. In this study, we propose a flexible probe U.S. imaging method based on element array geometry estimation from radio frequency (RF) data using a deep neural network (DNN). The input and output of the DNN are the RF data and parameters that determine the element array geometry, respectively. The DNN was first trained from scratch with simulation data and then fine-tuned with in vivo data. The DNN performance was evaluated according to the element position mean absolute error (MAE) and the reconstructed image quality. The reconstructed image quality was evaluated with peak-signal-to-noise ratio (PSNR) and mean structural similarity (MSSIM). In the test conducted with simulation data, the average element position MAE was 0.86 mm, and the average reconstructed image PSNR and MSSIM were 20.6 and 0.791, respectively. In the test conducted with in vivo data, the average element position MAE was 1.11 mm, and the average reconstructed image PSNR and MSSIM were 19.4 and 0.798, respectively. The average estimation time was 0.045 s. These results demonstrate the feasibility of the proposed method for long-term real-time monitoring using flexible probes.

Daily monitoring of internal tissues with shape-conformable and breathable ultrasound (US) imaging probes is promising for early detection of diseases. In recent years, textile substrates are widely used for wearable devices since they satisfy both conformability and breathability. However, it is not currently possible to use textile substrates for US probes due to the reflection or attenuation of US waves at the air gaps in the textiles. In this paper, we fabricated a shape-conformable and breathable US imaging probe by sandwiching the US elements between two woven polyester textiles on which copper electrodes were formed through electroless plating. The air gaps between the fibers at the electrode parts were filled with copper, allowing for high penetration of US waves. On the other hand, the non-electrode parts retain air gaps, leading to high breathability. The fabricated textile-based probe showed low flexural rigidity (0.066 × 10⁻⁴ N m² m⁻¹) and high air permeability (11.7 cm³ cm⁻² s⁻¹). Human neck imaging demonstrated the ability of the probe to monitor the pulsation of the common carotid artery and change in the internal jugular vein diameter, which led to the early detection of health issues such as arteriosclerosis and dehydration, and the capability of stable 24-hour monitoring.

Wearable ultrasound probes that enable non-invasive, continuous monitoring of internal body tissues have attracted increasing attention. Among various approaches, fabric-based probes are particularly promising due to their inherent flexibility, durability, and potential for seamless integration into garments. However, implementing high-density ultrasound arrays on fabric remains technically challenging, primarily due to the difficulty in forming reduced-pitch electrical wiring, which degrades imaging quality. In this study, we propose a novel fabrication approach using xurography, a wiring formation technique, to create tightly pitched electrical wiring on fabric. Furthermore, choosing glass fabric as the substrate—owing to its high mechanical and thermal resilience—enhanced the durability of the wiring; the fabricated wiring maintained stable resistance over 1,000 bending cycles. Using this method, we developed a 16-element flexible ultrasound probe with a 600 μm element pitch on a glass fabric. In imaging experiments with tissue-mimicking phantoms, the probe clearly visualized string targets and simulated blood vessels. The signal-to-noise ration of string targets improved by up to 6.3 dB, and the contrast-to-noise ratio for the vessel improved by 5.3 dB compared to previous design. These results demonstrate that the proposed approach overcomes the limitations of previous fabric-based probes and has potential for wearable healthcare applications.

Skin-attachable ultrasound probes face challenges in imaging the intended cross-section due to the difficulty in precisely adjusting the position and angle of attachment. While matrix element arrays are capable of imaging any cross-section within a three-dimensional field of view, their implementation presents a challenge due to the significant number of required ultrasound elements. We propose a method for optimizing the coordinates and shapes of elements based on the focusing quality onto the imaging points under the positional and angular errors in the element array. A 128-element array was optimized through the proposed method and its imaging performance was evaluated with simulated phantoms. The optimized array demonstrated the ability to clearly visualize the simulated wires, cysts, and blood vessels even with the positional error of 3 mm and the angular error of 20°. These results indicate the feasibility of developing a skin-attachable ultrasound probe that can be easily used in daily life without requiring precise positional and angular accuracy.