 หัวเรื่อง:ไม่มีชื่อไทย (ชื่ออังกฤษ : A Wireless Smart Shoe for Gait Analysis Using Heuristic Algorithms with Automated Thresholding) ผู้เขียน: Nantawat Pinkam, Itthisek Nilkhamhang สื่อสิ่งพิมพ์:pdf AbstractThis paper proposes a novel decision system for segregation of five normal gait phases (stance, heel-off, swing 1, swing 2 and heel-strike) by using a real-time wireless smart shoe. The classification method employed four force sensitive resistors to measure the force underneath a foot, together with an inertial measurement unit that is attached at the back of the shoe to determine the magnitude of acceleration and the inclination angle of the foot with respect to the ground. Data acquisition was through the XBee wireless network protocol to allow serial processing by a computer. The state transition theorem and threshold-based classification were used to distinguish the gait phases according to received data, where the thresholds were optimized by heuristic algorithms, such as the genetic algorithm and particle swarm optimization. Ground truthing was determined by marker-tracking using image processing. Video recording with real-time data and embedded interfacing was used to verify the output of the proposed state transition algorithm under indoor testing on a stationary treadmill. Experimentation and verification were conducted on a subject with a normal gait cycle. The smart shoe was able to ascertain the gait phase with 96.07% accuracy after optimized threshold values had been determined. |
หัวเรื่อง:ไม่มีชื่อไทย (ชื่ออังกฤษ : Development of Robotic Platform for Swarm Robots in Fire Detection Application) ผู้เขียน:Sarun Chattunyakit, Toshiaki Kondo, Itthisek Nilkhamhang สื่อสิ่งพิมพ์:pdf AbstractIn recent years, a team of simple robots, so-called swarm robots, can perform the same level of difficult tasks as a more complicated robot. Due to their abilities, they can be applied to many situations. Fire detection is one application that can be combined with swarm intelligence to increase efficiency and effectiveness. This paper presents a new swarm robotic platform for a fire detection task called FiFiBot that has been developed for low cost and high performance. The average cost per FiFiBot is USD 140. Compared with conventional designs, they are better in terms of computational speed, cost and the number of included sensors. Moreover, two FiFiBots were programmed to perform a leader-follower routine with fire detection, and were successfully tested. Hence, FiFiBots are feasible robotic platforms to be used for research and educational purposes for swarm systems. |