發(fā)布時間：2018-06-14 14:30

  本文選題：跌倒檢測 + 慣性傳感��； 參考：《電子科技大學》2017年碩士論文

【摘要】：人口老齡化是一個世界性的問題。根據(jù)世界衛(wèi)生組織的定義和我國第六次全國人口普查數(shù)據(jù),我國已經步入老齡化社會。在日常生活中,老年人極易出現(xiàn)跌倒等意外情況。據(jù)央視報道,在中國每年約有4000萬65歲以上的老人意外跌倒。當老人跌倒時,若未得到及時救助,會造成不可挽回的后果,因此跌倒檢測技術有很強的實際應用價值。本文的具體工作內容為:1)開展關于慣性傳感節(jié)點佩戴位置對于數(shù)據(jù)影響的實驗,選定腰部作為佩戴位置。將真實場景下跌倒樣本與實驗采集獲得的跌倒樣本進行對比,分析了二者的特點。對系統(tǒng)進行需求分析并確定設計目標,提出系統(tǒng)的技術方案。2)采集跌倒和日常行為活動的慣性數(shù)據(jù)樣本,構建算法設計所需的數(shù)據(jù)集。對所獲得的原始數(shù)據(jù)集進行預處理;使用Relief算法進行特征選擇,選取了分類器設計所需的特征集合;兼顧系統(tǒng)開發(fā),對比算法特異度和敏感度,選擇決策樹作為分類模型。3)實現(xiàn)包含云端服務器、安卓應用和慣性傳感節(jié)點的跌倒檢測系統(tǒng)。當檢測到跌倒時,慣性傳感節(jié)點向智能手機發(fā)送檢測結果,由手機進行定位并向云端服務器發(fā)送求助信息,而云端服務器則通知社區(qū)或醫(yī)院的監(jiān)護人員對跌倒者進行救助。4)對整個系統(tǒng)的功能進行驗證,驗證結果表明系統(tǒng)功能均正確實現(xiàn)。對系統(tǒng)跌倒檢測算法的敏感度和特異度進行測試,測試實驗結果表明該跌倒檢測算法敏感度為95.56%、特異度為98.00%,說明系統(tǒng)能夠較為準確地檢測跌倒且誤報較少。本文通過分析跌倒檢測的國內外研究現(xiàn)狀,對比不同跌倒檢測技術,選擇基于慣性傳感信號的檢測技術進行方案設計,結合現(xiàn)在成熟的云端服務器技術和安卓智能手機,實現(xiàn)了一套基于慣性傳感的跌倒檢測系統(tǒng)。系統(tǒng)功能完善,具有較強的實用價值。
[Abstract]:The aging of the population is a worldwide problem. According to the definition of the WHO and the data of the sixth national population census, China has entered an aging society. In daily life, the elderly are extremely prone to fall and other accidents. According to CCTV, it is reported that some people over 40 million and 65 years of age in China fall unexpectedly every year. When people fall, it will cause irreparable consequences if they are not saved in time. Therefore, the fall detection technology has a strong practical application value. The specific contents of this paper are as follows: 1) to carry out the experiment on the influence of the position of the inertial sensor node on the data, select the waist as the position to wear. The characteristics of the two fall samples are analyzed, and the characteristics of the two are analyzed. The system needs analysis and the design target is determined. The system's technical scheme is proposed to collect the inertial data samples from the fall and daily activities, and the data set required for the algorithm design is constructed. The original data set is preprocessed by the Relief calculation. The feature selection is carried out by the method, and the feature set required by the classifier is selected. The system is developed, the specificity and sensitivity of the algorithm are compared, and the decision tree is selected as the classification model.3) to implement the fall detection system containing cloud server, Android application and inertial sensor nodes. When the fall is detected, the inertial sensor node sends to the smart phone. Send the detection results, locate the mobile phone and send the help information to the cloud server, and the cloud server notifies the community or hospital guardians to help the fall person to help.4) to verify the function of the whole system. The results show that the system functions are realized correctly. The sensitivity and specificity of the system fall detection algorithm are advanced. The test results show that the sensitivity of the fall detection algorithm is 95.56% and the specificity is 98%. It shows that the system can detect the fall and less misinformation more accurately. In this paper, the status of the fall detection at home and abroad is analyzed, and the detection technology based on the inertial sensing signal is selected to choose the detection technology based on the inertial sensing signal. Design, combined with the mature cloud server technology and Android smart phone, a set of fall detection system based on inertial sensing is realized. The system has perfect function and has strong practical value.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP274;TP212.9

【參考文獻】

相關期刊論文 前10條

1 姜琛凱;;新常態(tài)下智慧養(yǎng)老生態(tài)鏈的構建——基于供需視角的分析框架及路徑選擇[J];山東財經大學學報;2016年06期

2 蒙彩英;;PDCA模式及平衡姿勢認知訓練在預防腦卒中患者跌倒中的應用[J];護理實踐與研究;2016年21期

3 孫朋;夏飛;張浩;彭道剛;馬茜;羅志疆;;改進混合高斯模型在人體跌倒檢測中的應用[J];計算機工程與應用;2017年20期

4 馬英楠;靳宗振;高星;張哲;趙珍儀;張文佳;;北京市社區(qū)老年人跌倒居家環(huán)境危險因素調研分析[J];城市住宅;2016年01期

5 趙正平;;典型MEMS和可穿戴傳感技術的新發(fā)展[J];微納電子技術;2015年01期

6 王之瓊;曲璐渲;隋雨彤;鮑楠;康雁;;基于極限學習機的跌倒檢測分類識別研究[J];中國生物醫(yī)學工程學報;2014年04期

7 李慧奇;梁丁;寧運琨;張靜;趙國如;;一種防跌倒預警系統(tǒng)的研究與實現(xiàn)[J];集成技術;2014年01期

8 ;老年人跌倒干預技術指南[J];中國實用鄉(xiāng)村醫(yī)生雜志;2012年08期

9 陳勇華;;微機電系統(tǒng)的研究與展望[J];電子機械工程;2011年03期

10 霍宏偉;張宏科;;基于室內無線傳感器網絡射頻信號的老年人跌倒檢測研究[J];電子學報;2011年01期

相關碩士學位論文 前3條

1 唐薇;基于單節(jié)點慣性傳感器的人體行為監(jiān)測[D];電子科技大學;2016年

2 程e，

本文編號：2017709