Abstract:The creation of unique control methods for a hand prosthesis is still a problem that has to be addressed. The best choice of a human-machine interface (HMI) that should be used to enable natural control is still a challenge. Surface electromyography (sEMG), the most popular option, has a variety of difficult-to-fix issues (electrode displacement, sweat, fatigue). The ultrasound imaging-based methodology offers a means of recognising complex muscle activity and configuration with a greater SNR and less hardware requirements as compared to sEMG. In this study, a prototype system for high frame rate ultrasound imaging for prosthetic arm control is proposed. Using the proposed framework, a virtual robotic hand simulation is developed that can mimick a human hand as illustrated in the link. The proposed classification model simulating four hand gestures has a classification accuracy of more than 90%.
Abstract:Gas leakage is a critical problem in the industrial sector, residential structures, and gas-powered vehicles; installing gas leakage detection systems is one of the preventative strategies for reducing hazards caused by gas leakage. Conventional gas sensors, such as electrochemical, infrared point, and MOS sensors, have traditionally been used to detect leaks. The challenge with these sensors is their versatility in settings involving many gases, as well as their exorbitant cost and scalability. As a result, several gas detection approaches were explored. Our approach utilizes 40 KHz ultrasound signal for gas detection. Here, the reflected signal has been analyzed to detect gas leaks and identify gas in real-time, providing a quick, reliable solution for gas leak detection in industrial environments. The electronics and sensors used are both low-cost and easily scalable. The system incorporates commonly accessible materials and off-the-shelf components, making it suitable for use in a variety of contexts. They are also more effective at detecting numerous gas leaks and has a longer lifetime. Butane was used to test our system. The breaches were identified in 0.01 seconds after permitting gas to flow from a broken pipe, whereas identifying the gas took 0.8 seconds