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Sunlight background noise significantly hinders the operation of ghost imaging systems, posing a considerable challenge for target imaging under daytime sunlight conditions. This paper introduces a method to eliminate sunlight background noise using a Faraday anomalous dispersion optical filter (FADOF). A ghost imaging system based on FADOF is constructed, and experiments are conducted under strong background noise conditions. The system operates outdoors in direct sunlight, utilizing sunlight introduction system to introduce light into the detection path, directly reaching the detection end of the system. In this real sunlight noise condition, the ghost imaging system using FADOF filtering achieved nearly continuous and stable imaging throughout three summer days, contrasting with a system using a 10 nm filter that only functions properly after sunset. The research findings indicate that FADOF effectively enhances the ghost imaging system's resistance to background light noise, enabling continuous operation under conditions of strong background noise throughout the day. [ABSTRACT FROM AUTHOR]

In endoscopic surgery, the surgical navigation system needs to calculate the deformation of soft tissue by biomechanical model which requires elastic properties and boundary conditions. However, patient-specific elastic parameters and boundary conditions of soft tissue are hard to measure accurately from the preoperative images, especially the boundary conditions will change during the operation due to the ligament cutting. In addition, simple boundary conditions such as fixed constraints and free-force constraints are not physically adequate to simulate the elastic effect of ligaments attached to the liver. In this paper, we present a novel method to identify the Young's modulus and equivalent spring constraint boundary conditions of a locally observed soft tissue. Based on the spring constraint boundary condition, a two-step inverse algorithm is developed based on the finite element method (FEM) with integration of energy regularized Gauss-Newton (GN) method and l 1 -regularized method, which takes external forces and displacements of observable nodes as inputs. A series of numerical simulations and physical hydrogel phantom experiments were conducted. The results of simulation and physical experiments show that the Young's modulus and equivalent spring constraint boundary conditions identified by the proposed method agree well with their setup true values. [ABSTRACT FROM AUTHOR]

Scoliosis often occurs in adolescents and seriously affects physical development and health. Traditionally, medical imaging is the most common means of evaluating the corrective effect of bracing during treatment. However, the imaging approach falls short in providing real-time feedback, and the optimal corrective force remains unclear, potentially slowing the patient's recovery progress. To tackle these challenges, an all-in-one integrated array of pressure sensors and sEMG electrodes based on hierarchical MXene/chitosan/polydimethylsiloxane (PDMS)/polyurethane sponge and MXene/polyimide (PI) is developed. Benefiting from the microstructured electrodes and the modulus enhancement of PDMS, the sensor demonstrates a high sensitivity of 444.3 kPa -1 and a broad linear detection range (up to 81.6 kPa). With the help of electrostatic attraction of chitosan and interface locking of PDMS, the pressure sensor achieves remarkable stability of over 100 000 cycles. Simultaneously, the sEMG electrodes offer exceptional stretchability and flexibility, functioning effectively at 60% strain, which ensures precise signal capture for various human motions. After integrating the developed all-in-one arrays into a commercial scoliosis brace, the system can accurately categorize human motion and predict Cobb angles aided by deep learning. This study provides real-time insights into brace effectiveness and patient progress, offering new ideas for improving the efficiency of scoliosis treatment., (© 2024 Wiley‐VCH GmbH.)