Real-Time Embedded Identification System for Knee Joint Rehabilitating Movements

• Main Authors: Sheng-Yuan Huang, 黃聖芫
• Other Authors: 練光祐
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/u9qtec

碩士 === 國立臺北科技大學 === 電機工程系研究所 === 102 === Becoming more and more popular in recent years, the study of gesture and posture recognition has provoked suggestions of numerous algorithms in many researches and references, striving for more accurate hand gesture and body posture recognition. The mathematical models built by most algorithms are too complex with amount of calculation too large to be successfully operated by lightweight embedded systems. The Longest Common Subsequence (LCS) is employed in this study as the core algorithm for the recognition of posture movements and the design is realized using an embedded system built with ATmega2560 microcontroller. This way, portability and abilities to instantly and accurately recognize user posture and movements are achieved. Currently, it is part of the standard treatment procedure to use hinged knee braces in a long-term rehabilitation process. Here, a single inertial sensor is taken and attached on a hinged knee brace then signal processing through moving average and data normalization methods are used for real-time recognition and more accurate results of physical therapy (PT) movements. For recognizing a wide range of movements, this study took a step further and attached two separate inertial sensors on the upper and lower parts of the knee brace to increase the details of acquired data. The two sets of sensor data are taken and paired up to identify a wider variety of PT movements. As the experiment results cited the 7 most common knee joint PT movements and presented the data from several different users, it is observed that identification accuracy reach over 90%. This is a sound prove that this PT aid can be widely applied to the rehabilitation of post cruciate ligament surgeries.