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                                   The Post-Surgery Mobility Tracker is a digital health tool designed to monitor and support patients' recovery following surgical procedures. By leveraging wearable technology and mobile app integration, the tracker collects real-time data on key mobility indicators such as step count, range of motion, and activity levels. This data enables healthcare providers to assess patient progress remotely, identify early signs of complications, and tailor rehabilitation plans accordingly. The system empowers patients with visual feedback on their recovery milestones, promoting adherence to post-operative protocols and improving overall outcomes. The tracker aims to enhance continuity of care, reduce hospital readmissions, and facilitate a smoother, data-driven recovery process.

                                 This project implements a basic night vision and normal vision switching system using an Arduino Nano, an LDR (Light Dependent Resistor), a relay module, and a lens. The system automatically detects ambient light levels through the LDR sensor; when low light or darkness is detected, the Arduino activates the relay to switch to night vision mode by enabling an infrared (IR) or low-light lens. In normal lighting conditions, the system defaults to standard vision. This setup demonstrates an automated vision control mechanism suitable for surveillance or smart camera systems, enabling seamless transition between day and night modes based on environmental lighting.

                       The BREATH Health Monitor System is a compact, real-time respiratory monitoring solution developed using the ESP32 microcontroller. Designed for continuous and remote health tracking, this system utilizes integrated sensors to measure vital respiratory parameters such as breathing rate, temperature, and oxygen levels. The ESP32’s built-in Wi-Fi and Bluetooth capabilities enable seamless data transmission to cloud platforms or mobile applications for remote access and analysis. With a focus on low power consumption, portability, and cost-effectiveness, the BREATH system is ideal for personal health monitoring, telemedicine, and early detection of respiratory conditions, providing users and healthcare providers with timely and actionable insights.

    We developed this project to study the practical application value of abdominal ultrasonography in the diagnosis and treatment of acute abdomen in children. This study uses the method of collecting actual clinical cases and scientific analysis to estimate the clinical diagnostic value of high-frequency ultrasound and low-frequency ultrasound. The sensitivity, specificity, positive predictive value, and negative predictive value in the diagnosis of mesenteric. The sensitivity, accuracy, and false negatives of high-frequency ultrasound in the diagnosis of acute appendicitis were significantly higher than those of low-frequency ultrasound. Our project shows that ultrasound has high accuracy, sensitivity, and specificity in the diagnosis of acute appendicitis. Low-frequency ultrasound can show the whole picture of the disease and the situation in the abdominal cavity, which can better guide the clinical treatment. Color Doppler hemodynamics is a useful supplement to two-dimens...

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