本文選題：坐姿識(shí)別 + 卡爾曼濾波��； 參考：《哈爾濱理工大學(xué)》2017年碩士論文

【摘要】：坐姿是現(xiàn)代職業(yè)人群工作中最常見(jiàn)的姿勢(shì),在日常工作中保持健康坐姿對(duì)于老年人群預(yù)防疾病有著重要的意義。因此,正確的坐姿成為提高健康質(zhì)量的重要指標(biāo)。近年來(lái),隨著微機(jī)械電子系統(tǒng)技術(shù)的發(fā)展,特別是加速度和角速度傳感器的出現(xiàn),對(duì)坐姿檢測(cè)的研究起到很大的推進(jìn)作用。單一傳感器的姿態(tài)檢測(cè),容易因慣性器件的漂移和累計(jì)誤差,導(dǎo)致測(cè)量精度的下降。因此,通過(guò)多個(gè)傳感器進(jìn)行姿態(tài)檢測(cè),并借助數(shù)據(jù)融合算法提高姿態(tài)檢測(cè)精度成為目前研究的熱點(diǎn)。與基于計(jì)算機(jī)視覺(jué)技術(shù)的人體姿態(tài)識(shí)別方法相比,基于傳感器的人體姿態(tài)識(shí)別和監(jiān)測(cè)技術(shù)具有不泄露使用者的隱私、攜帶方便簡(jiǎn)潔、檢測(cè)準(zhǔn)確等諸多優(yōu)點(diǎn)。本文在國(guó)內(nèi)外研究發(fā)展的現(xiàn)狀的基礎(chǔ)上,進(jìn)一步加深對(duì)坐姿檢測(cè)的研究。在本文中利用MPU6050傳感器、單片機(jī)、選擇器和電源等硬件組成坐姿檢測(cè)系統(tǒng)。通過(guò)傳感器采集到的三軸加速度和三軸角速度數(shù)據(jù),將數(shù)據(jù)通過(guò)I2C總線協(xié)議傳到單片機(jī),單片機(jī)再將數(shù)據(jù)上傳到電腦中并儲(chǔ)存。通過(guò)MATLAB軟件先對(duì)采集到的原始數(shù)據(jù)進(jìn)行處理,處理的方法是利用卡爾曼濾波方法進(jìn)行濾波處理。再對(duì)處理后的數(shù)據(jù)利用四元數(shù)算法進(jìn)行角度合成,之后利用得到的數(shù)據(jù)對(duì)其進(jìn)行特征項(xiàng)的提取,利用SVM分類(lèi)器對(duì)處理過(guò)的數(shù)據(jù)進(jìn)行識(shí)別,最后達(dá)到對(duì)不同坐姿姿態(tài)的識(shí)別。本系統(tǒng)實(shí)驗(yàn)結(jié)果表明,本系統(tǒng)可以識(shí)別出不同身高不同體重的人的正坐、前傾、后傾、左傾、右傾以及左翹腿和右翹腿的坐姿姿態(tài),識(shí)別率可以達(dá)到90%以上。
[Abstract]:Sitting posture is the most common posture in the work of modern professional population. It is of great significance to keep a healthy sitting posture in daily work for the elderly to prevent diseases. Therefore, the correct sitting position is an important indicator to improve health quality. In recent years, with the development of MEMS technology, especially the emergence of acceleration and angular velocity sensors, the research of sitting posture detection plays a very important role. The attitude detection of a single sensor is easy to be caused by the drift and accumulative error of the inertial device, which leads to the decrease of the measurement accuracy. Therefore, attitude detection based on multiple sensors and data fusion algorithm to improve the accuracy of attitude detection has become a hot topic. Compared with the human body attitude recognition method based on computer vision technology, the sensor based human posture recognition and monitoring technology has many advantages, such as not revealing users' privacy, convenient and simple to carry, accurate detection and so on. Based on the current situation of domestic and international research, this paper further deepens the research of sitting posture detection. In this paper, the MPU6050 sensor, single-chip microcomputer, selector and power supply hardware composed of sitting position detection system. The data of three-axis acceleration and triaxial angular velocity collected by the sensor are transmitted to the single-chip computer through the I2C bus protocol, and the data are uploaded to the computer and stored by the single-chip microcomputer. The original data is processed by MATLAB software, and the Kalman filter is used to process the original data. Then the processed data are angled synthesized by quaternion algorithm, and then the feature items are extracted by the obtained data, and the processed data are identified by SVM classifier, and finally the attitude recognition of different sitting posture is achieved. The experimental results of the system show that the system can recognize the sitting posture of people with different height and weight, including the positive, forward, backward, left, right, left and right legs, and the recognition rate can reach more than 90%.
【學(xué)位授予單位】：哈爾濱理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP391.41;TP212

【參考文獻(xiàn)】

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本文編號(hào)：1842195