本文選題：跌倒檢測 + MEMS慣性傳感器��； 參考：《南昌航空大學(xué)》2017年碩士論文

【摘要】：針對我國老齡化社會未富先老的特點,作為社會重要構(gòu)成人群老年人的健康也將對國家產(chǎn)生巨大影響,而跌倒會嚴重威脅老年人的身體健康。老年人一旦發(fā)生跌倒,將直接危害到生命安全以及加重家庭和社會的負擔(dān)。因此,研究開發(fā)人體跌倒預(yù)警及其防護設(shè)備對于減少由跌倒帶來的損害具有重要意義。系統(tǒng)采用STM32F405RG為主控芯片,MPU9150九軸傳感器為MEMS慣性傳感器,SIM900A作為GSM/GPRS通訊模塊,UM220作為GPS/BD定位模塊,通過這幾個模塊的組合構(gòu)成了一個跌倒檢測下位機節(jié)點。我們通過MEMS慣性傳感器來采集人體運動數(shù)據(jù),結(jié)合由多次人體跌倒實驗得出的跌倒時加速度、姿態(tài)角等特征,經(jīng)過充分分析比對后得出合理的姿態(tài)角和合加速度的閾值。從而系統(tǒng)能夠在跌倒發(fā)生后人體著地前發(fā)出跌倒預(yù)警,MCU把GPS模塊采集到的跌倒時的地理位置信息提取后加入到短信格式中,在跌倒時通過GSM/GPRS模塊發(fā)送出去,告知其監(jiān)護人已經(jīng)檢測到跌倒的發(fā)生。此外,在PC端還有能夠?qū)ο挛粰C傳感器傳來的運動數(shù)據(jù)進行顯示、分析、處理的上位機人體慣性數(shù)據(jù)采集監(jiān)測系統(tǒng),該監(jiān)測系統(tǒng)能夠?qū)崟r顯示9軸數(shù)據(jù)的波形曲線,同時具有運動數(shù)據(jù)的存儲和回放功能。在完成了跌倒檢測節(jié)點的設(shè)計后,把節(jié)點接上控制舵機部分驅(qū)動一個髖關(guān)節(jié)安全氣囊,組成跌到檢測及其防護系統(tǒng)。當(dāng)系統(tǒng)的跌倒檢測算法檢測到跌倒即將發(fā)生時,MCU給舵機發(fā)送信號驅(qū)動舵機上的刺針刺破氣瓶,使得系在人體腰間的氣囊快速充氣,在人體著地時保護人體髖關(guān)節(jié),減少跌倒時地面對人體的沖擊。跌倒檢測裝置的核心在于摔倒的檢測算法,摔倒檢測算法是需要以大量跌倒實驗為基礎(chǔ),通過人體慣性傳感器采集跌倒實驗中的跌倒數(shù)據(jù)特征,再對加速度計、陀螺儀原始數(shù)據(jù)進行原始數(shù)據(jù)處理,然后使用數(shù)字濾波融合算法來舉行人體姿態(tài)解算。最后,將姿態(tài)解算得出的人體合加速度、姿態(tài)角數(shù)據(jù)與分析得出跌倒的合加速度、姿態(tài)角的閾值進行對比,從而實現(xiàn)跌倒行為的檢測。我們把系統(tǒng)佩戴在腰部進行模擬摔倒實驗,在摔倒過程中系統(tǒng)正常工作,摔倒檢測的準(zhǔn)確度達到98%以上,并且氣囊能夠在跌倒前充分打開,在跌倒時能夠保護人體。
[Abstract]:In view of the characteristics of aging society in our country, as an important social group, the health of the elderly will also have a great impact on the country, and falling down will seriously threaten the health of the elderly. Once the elderly fall down, it will directly endanger the safety of life and increase the burden on families and society. Therefore, the research and development of human fall warning and its protective equipment is of great significance to reduce the damage caused by fall. The system uses STM32F405RG as main control chip MPU9150 nine-axis sensor as MEMS inertial sensor and SIM900A as GSM/GPRS communication module and UM220 as GPS/BD positioning module. Through the combination of these modules, a fall detection node is constructed. The MEMS inertial sensor is used to collect human motion data. Combining with the characteristics of fall acceleration and attitude angle obtained from multiple human fall experiments, a reasonable threshold of attitude angle and acceleration is obtained after full analysis and comparison. Therefore, the system can send out the fall warning system before the human body lands on the ground after the fall, and add the geographic position information of the fall collected by the GPS module to the short message format, and send it out through the GSM/GPRS module when the fall occurs. Inform his guardian that a fall has been detected. In addition, there is an upper computer inertial data acquisition and monitoring system on PC, which can display, analyze and process the motion data from the sensor of the lower computer. The monitoring system can display the waveform curve of 9-axis data in real time. At the same time, it has the function of storage and playback of moving data. After the design of the tumble detection node is completed, the joint is connected to the control steering gear to drive a hip joint airbag to form a detection and protection system. When the fall detection algorithm of the system detects that the fall is about to happen, MCU sends a signal to the steering gear to drive the needle on the steering gear to puncture the cylinder, so that the air bag tied to the waist of the human body is inflated quickly, and the human hip joint is protected when the human body lands on the ground. Reduce the impact of a fall on the human body. The core of the fall detection device is the fall detection algorithm. The fall detection algorithm needs to be based on a large number of fall experiments, through the human body inertial sensor to collect the fall data characteristics in the fall experiment, and then to the accelerometer, The original data of gyroscope are processed and the human pose is solved by digital filtering fusion algorithm. Finally, the human body acceleration and attitude angle data obtained by attitude solution are compared with the fall acceleration and attitude angle threshold, so as to realize the fall behavior detection. We wear the system in the waist to simulate the fall experiment, the system works normally during the fall, the accuracy of the fall detection is over 98%, and the air bag can be fully opened before the fall, and can protect the human body during the fall.
【學(xué)位授予單位】：南昌航空大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R318.6;TP212

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