[1] 蔡伦, 林岑, 周鼒, 等. 老年人跌倒的公共卫生研究进展 [J].中国老年学杂志, 2018, 38(9): 222-225. CAI Lun, LIN Cen, ZHOU Zi, et al. Advances in public health research on falls of the elderly[J]. Chinese Journal of Gerontology, 2018, 38(9): 222-225.

[2] 吕汶聪, 张志静 . 老年人跌倒现状及护理对策 [J].现代医学与健康研究电子杂志, 2018: 119-119. LV Wencong, ZHANG Zhijing. The current situation of elderly fall and nursing countermeasures[J]. Modern Medicine and Health Research E-Magazine, 2018: 119-119.

[3] 吴志强, 曹蕾, 王凯, 等. 基于智能手机的人体跌倒检测系统设计 [J].计算机工程与设计, 2014, 35(4): 1465-1470. WU Zhiqiang, CAO Lei, WANG Kai, et al. Design of human body fall detection system based on smart phone[J]. Computer engineering and design, 2014, 35(4): 1465-1470.

[4] 左常玲. 基于视频的自动摔倒检测研究与实现 [D].合肥: 安徽大学 , 2012. ZUO Changling. Research and implementation of video-based automatic fall detection[D]. Hefei: Anhui University, 2012.

[5] 王刚. 基于多传感器的可穿戴跌倒检测系统的设计与实现 [D].北京: 北京工业大学, 2015. WANG Gang. Design and implementation of wearable fall detection system based on multi-sensor[D]. Beijing: Beijing University of Technology, 2015.

[6] 李仲华, 臧春华 , 杨刚. 基于噪声嵌入的跌倒检测系统的设计 [J]. 微机处理, 2017(2): 74-76. LI Zhonghua, ZANG Chunhua, YANG Gang. Design of fall detection system based on noise embedding[J]. Microcomputer Processing, 2017(2): 74-76.

[7] Mashiyama S, Hong J, Ohtsuki T. A fall detection system using low resolution infrared array sensor[C]// International Symposium on Personal, Indoor and Mobile Radio Communications. IEEE, 2014: 2109-2113.

[8] 杨任兵, 程文播, 钱庆, 等. 红外图像中基于多特征提取的跌倒检测算法研究[J].红外技术 , 2017, 39(12): 1131-1138. YANG Renbing, CHENG Wenbo, QIAN Qing, et al. Research on fall detection algorithm based on multi-feature extraction in infrared image[J]. Infrared technology, 2017, 39(12): 1131-1138.

[9] LIU Chienliang, LEE Chiahoang, LIN Pingmin. A fall detection system using k-nearest neighbor classifier[J]. Expert System with Applications, 2010(37): 7174-7181.

[10] 张舒雅, 吴科艳, 黄炎子, 等. 基于 SVM_KNN的老人跌倒检测算法 [J].计算机与现代化 , 2017(12):5 3-59. ZHANG Shuya, WU Keyan, HUANG Yanzi, et al.Old man fall detection algorithm based on SVM_KNN[J]. Computer and Modernization, 2017(12): 53-59.

[11] 陈玮, 周晴, 曹桂涛 . 基于 SVM和阈值分析法的摔倒检测系统[J]. 计算机应用于软件, 2017(7): 182-187. CHEN Wei, ZHOU Qing, CAO Guitao. Fall detection system based on SVM and threshold analysis method[J]. Computer application software, 2017(7): 182-187.

[12] Nadi M, Elbendary N, Hassanien A E, et al. Falling Detection System Based on Machine Learning[C]//International Conference on Advanced Information Technology & Sensor Application. IEEE, 2016: 71-75.

[13] Adhikari K, Bouchachia H, Nait-Charif H. Activity recognition for indoor fall detection using convolutional neural network[C]//2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA). IEEE, 2017: 81-84.

[14] FENG P, YU M, Naqvi S M, et al. Deep learning for posture analysis in fall detection[C]//2014 International Conference on Digital Signal Processing (DSP). IEEE, 2014: 12-17.

[15] Vidigal M, Lima M, Neto A D A. Elder Falls Detection Based on Artificial Neural Networks[C]//Fourteenth Mexican International Conference on Artificial Intelligence. IEEE Computer Society, 2015: 226-230.

[16] Kerdegari H, Mokaram S, Samsudin K, et al. A Pervasive Neural Network Based Fall Detection System on Smart Phone[J]. Journal of Ambient Intelligence and Smart Environments, 2015, 7(2): 221-230.

[17] Linhong Wang. Human infrared signal recognition using single PIR detector[C]//2011 4th International Congress on Image and Signal Processing, 2011: 2664-2668.

[18] 李洪奇, 杨中国, 朱丽萍, 等. 基于数据集特征的 KNN最优 K值预测方法[J].计算机应用与软件 , 2013, 33(6): 54-58. LI Hongqi, YANG Zhongguo, ZHU Liping, et al. KNN optimal K-value prediction method based on data set features[J]. Computer Applications and Software, 2013, 33(6): 54-58.