A robot-assisted tracheal intubation system based on a soft actuator?

PURPOSE: Tracheal intubation is the gold standard of airway protection and constitutes a pivotal life-saving technique frequently employed in emergency medical interventions. Hence, in this paper, a system is designed to execute tracheal intubation tasks automatically, offering a safer and more efficient solution, thereby alleviating the burden on physicians. METHODS: The system comprises a tracheal tube with a bendable front end, a drive system, and a tip endoscope. The soft actuator provides two degrees of freedom for precise orientation. It is fabricated with varying-hardness silicone and reinforced with fibers and spiral steel wire for flexibility and safety. The hydraulic actuation system and tube feeding mechanism enable controlled bending and delivery. Object detection of key anatomical features guides the robotic arm and soft actuator. The control strategy involves visual servo control for coordinated robotic arm and soft actuator movements, ensuring accurate and safe tracheal intubation. RESULTS: The kinematics of the soft actuator were established using a constant curvature model, allowing simulation of its workspace. Through experiments, the actuator is capable of 90° bending as well as 20° deflection on the left and right sides. The maximum insertion force of the tube is 2 N. Autonomous tracheal intubation experiments on a training manikin were successful in all 10 trials, with an average insertion time of 45.6 s. CONCLUSION: Experimental validation on the manikin demonstrated that the robot tracheal intubation system based on a soft actuator was able to perform safe, stable, and automated tracheal intubation. In summary, this paper proposed a safe and automated robot-assisted tracheal intubation system based on a soft actuator, showing considerable potential for clinical applications.

A stiffness-tunable soft actuator inspired by helix for medical applications.

PURPOSE: This paper introduces the stiffness-tunable soft actuator (STSA), a novel device that combines a silicone body with a thermoplastic resin structure (TPRS). The STSA's design allows for the variable stiffness of soft robots, significantly increasing their potential for use in medical scenarios such as minimally invasive surgeries (MIS). By adjusting the stiffness of the STSA, it is possible to enhance the robot's dexterity and adaptability, making it a promising tool for performing complex tasks in narrow and delicate spaces. METHODS: The stiffness of the STSA can be modulated by altering the temperature of the TPRS, which has been inspired by the helix and is integrated into the soft actuator to achieve a broad range of stiffness modulation while maintaining flexibility. The STSA has been designed with both diagnostic and therapeutic functions in mind, with the hollow area of the TPRS serving as an instrument channel for delivering surgical instruments. Additionally, the STSA features three uniformly arranged pipelines for actuation by air or tendon, and can be expanded with more functional chambers for endoscopy, illumination, water injection, and other purposes. RESULTS: Experimental results show that the STSA can achieve a maximum 30-fold stiffness tuning, providing a significant improvement in load capacity and stability when compared to pure soft actuators (PSAs). Of particular importance, the STSA is capable of achieving stiffness modulation below 45 °C, thereby ensuring a safe entry into the human body and creating an environment conducive to the normal operation of surgical instruments such as endoscope. CONCLUSION: The experimental findings indicate that the soft actuator with TPRS can achieve a broad range of stiffness modulation while retaining flexibility. Moreover, the STSA can be designed to have a diameter of 8-10 mm, which satisfies the diameter requirements of a bronchoscope. Furthermore, the STSA has the potential to be utilized for clamping and ablation in a laparoscopic scenario, thereby demonstrating its potential for clinical use. Overall, these results suggest that the STSA has significant promise for use in medical applications, particularly in the context of minimally invasive surgeries.

Omnidirectional 3D autostereoscopic aerial display with continuous parallax.

We present anl omnidirectional 3D autostereoscopic aerial display with continuous parallax. Integral photography (IP) combined with polyhedron-shaped aerial imaging plates (AIPs) is utilized to achieve an extended view angle of 3D aerial images. With optical theoretical analysis and an aerial in situ rotation design, a 3D aerial display with an enlarged viewing angle is realized. In particular, the proposed 3D aerial display can realize any assigned angle within 360 deg. We also optimize the aerial display with artifact image removal and floating image brightness analysis. Experiments are performed to prove the 3D aerial display with full-motion parallax, continuous viewpoints, and multiplayer interaction. The proposed system is an attractive prospect of non-contact interaction and multi-person collaboration.

Intelligent optical diagnosis and treatment system for automated image-guided laser ablation of tumors.

PURPOSE: For tumor resections near critical structures, accurate identification of tumor boundaries and maximum removal are the keys to improve surgical outcome and patient survival rate, especially in neurosurgery. In this paper, we propose an intelligent optical diagnosis and treatment system for tumor removal, with automated lesion localization and laser ablation. METHODS: The proposed system contains a laser ablation module, an optical coherence tomography (OCT) unit, and a robotic arm along with a stereo camera. The robotic arm can move the OCT sample arm and the laser ablation front-end to the suspected lesion area. The corresponding diagnosis and treatment procedures include computer-aided lesion segmentation using OCT, automated ablation planning, and laser control. The ablation process is controlled by a deflectable mirror, and a non-common-path ablation planning algorithm based on the transformation from lesion positions to mirror deflection angles is presented. RESULTS: Phantom and animal experiments are carried out for system verification. The robot could reach the planned position with high precision, which is approximately 1.16 mm. Tissue classification with OCT images achieves 91.7% accuracy. The error of OCT-guided automated laser ablation is approximately 0.74 mm. Experiments on mouse brain tumors show that the proposed system is capable of clearing lesions efficiently and precisely. We also conducted an ex vivo porcine brain experiment to verify the whole process of the system. CONCLUSION: An intelligent optical diagnosis and treatment system is proposed for tumor removal. Experimental results show that the proposed system and method are promising for precise and intelligent theranostics. Compared to conventional cancer diagnosis and treatment, the proposed system allows for automated operations monitored in real-time, with higher precision and efficiency.

Real-Time Underwater Image Recognition with FPGA Embedded System for Convolutional Neural Network.

The underwater environment is still unknown for humans, so the high definition camera is an important tool for data acquisition at short distances underwater. Due to insufficient power, the image data collected by underwater submersible devices cannot be analyzed in real time. Based on the characteristics of Field-Programmable Gate Array (FPGA), low power consumption, strong computing capability, and high flexibility, we design an embedded FPGA image recognition system on Convolutional Neural Network (CNN). By using two technologies of FPGA, parallelism and pipeline, the parallelization of multi-depth convolution operations is realized. In the experimental phase, we collect and segment the images from underwater video recorded by the submersible. Next, we join the tags with the images to build the training set. The test results show that the proposed FPGA system achieves the same accuracy as the workstation, and we get a frame rate at 25 FPS with the resolution of 1920 × 1080. This meets our needs for underwater identification tasks.

A Machine Learning Approach to Argo Data Analysis in a Thermocline.

With the rapid development of sensor networks, big marine data arises. To efficiently use these data to predict thermoclines, we propose a machine learning approach. We firstly focus on analyzing how temperature, salinity, and geographic location features affect the formation of thermocline. Then, an improved model based on entropy value method for the thermocline selection is demonstrated. The experiments adopt BOA Argo data sets and the experimental results show that our novel model can predict thermoclines and related data effectively.

Genetic analysis of Chinese families reveals a novel truncation allele of the retinitis pigmentosa GTPase regulator gene.

AIM: To make comprehensive molecular diagnosis for retinitis pigmentosa (RP) patients in a consanguineous Han Chinese family using next generation sequencing based Capture-NGS screen technology. METHODS: A five-generation Han Chinese family diagnosed as non-syndromic X-linked recessive RP (XLRP) was recruited, including four affected males, four obligate female carriers and eleven unaffected family members. Capture-NGS was performed using a custom designed capture panel covers 163 known retinal disease genes including 47 RP genes, followed by the validation of detected mutation using Sanger sequencing in all recruited family members. RESULTS: Capture-NGS in one affected 47-year-old male reveals a novel mutation, c.2417_2418insG:p.E806fs, in exon ORF15 of RP GTPase regulator (RPGR) gene results in a frameshift change that results in a premature stop codon and a truncated protein product. The mutation was further validated in three of four affected males and two of four female carriers but not in the other unaffected family members. CONCLUSION: We have identified a novel mutation, c.2417_2418insG:p.E806fs, in a Han Chinese family with XLRP. Our findings expand the mutation spectrum of RPGR and the phenotypic spectrum of XLRP in Han Chinese families, and confirms Capture-NGS could be an effective and economic approach for the comprehensive molecular diagnosis of RP.