Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues
暂无分享,去创建一个
Fatimah Ibrahim | Mas S. Mohktar | Mohammad Ashfak Habib | Shahrul Bahyah Kamaruzzaman | Kheng Seang Lim | Tan Maw Pin | M. S. Mohktar | K. Lim | F. Ibrahim | S. Kamaruzzaman | T. Pin
[1] T. Tamura,et al. A preliminary study to demonstrate the use of an air bag device to prevent fall-related injuries , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[2] Yagiz Onat Yazir,et al. Tradeoffs in cross platform solutions for mobile assistive technology , 2013, 2013 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM).
[3] Jong Hyuk Park,et al. An Environmental-Adaptive Fall Detection System on Mobile Device , 2011, Journal of Medical Systems.
[4] Sheikh Iqbal Ahamed,et al. iPrevention: towards a novel real-time smartphone-based fall prevention system , 2013, SAC '13.
[5] Dong Xuan,et al. Mobile phone-based pervasive fall detection , 2010, Personal and Ubiquitous Computing.
[6] Lale Akarun,et al. A Smartphone Based Fall Detector with Online Location Support , 2010 .
[7] Yingli Tian,et al. Privacy Preserving Automatic Fall Detection for Elderly Using RGBD Cameras , 2012, ICCHP.
[8] Jeffrey M. Hausdorff,et al. Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls , 2012, PloS one.
[9] Ali-young Jeon,et al. Emergency Detection System Using PDA Based on Self-Response Algorithm , 2007, 2007 International Conference on Convergence Information Technology (ICCIT 2007).
[10] Tong Zhang,et al. Fall Detection by Embedding an Accelerometer in Cellphone and Using KFD Algorithm , 2006 .
[11] Yibin Hou,et al. Triaxial accelerometer-based real time fall event detection , 2012, International Conference on Information Society (i-Society 2012).
[12] Hanseok Ko,et al. Acoustic and visual signal based context awareness system for mobile application , 2011, IEEE Transactions on Consumer Electronics.
[13] Shuai Tao,et al. Privacy-Preserved Behavior Analysis and Fall Detection by an Infrared Ceiling Sensor Network , 2012, Sensors.
[14] Juan Manuel Moreno,et al. FATE: One step towards an automatic aging people fall detection service , 2013, Proceedings of the 20th International Conference Mixed Design of Integrated Circuits and Systems - MIXDES 2013.
[15] M. Kaenampornpan,et al. Fall detection prototype for Thai elderly in mobile computing era , 2011, The 8th Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI) Association of Thailand - Conference 2011.
[16] Ying-Wen Bai,et al. Recognition of direction of fall by smartphone , 2013, 2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE).
[17] Felix Büsching,et al. DroidCluster: Towards Smartphone Cluster Computing -- The Streets are Paved with Potential Computer Clusters , 2012, 2012 32nd International Conference on Distributed Computing Systems Workshops.
[18] Shuwan Xue,et al. Portable Preimpact Fall Detector With Inertial Sensors , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[19] Younghoon Kim,et al. A Simple Falling Recognition Scheme for a Human Body by Using Mobile Devices , 2013 .
[20] Yasuhisa Hirata,et al. Analysis of the slip-related falls and fall prevention with an intelligent shoe system , 2010, 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.
[21] Xia Wang,et al. Fall Detection on Mobile Phones Using Features from a Five-Phase Model , 2012, 2012 9th International Conference on Ubiquitous Intelligence and Computing and 9th International Conference on Autonomic and Trusted Computing.
[22] Frank Sposaro,et al. iFall: An android application for fall monitoring and response , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[23] A McIntosh,et al. The design of a practical and reliable fall detector for community and institutional telecare , 2000, Journal of telemedicine and telecare.
[24] Ruzena Bajcsy,et al. USING SMART SENSORS AND A CAMERA PHONE TO DETECT AND VERIFY THE FALL OF ELDERLY PERSONS , 2005 .
[25] Ye Li,et al. Physical Activity Recognition Utilizing the Built-In Kinematic Sensors of a Smartphone , 2013, Int. J. Distributed Sens. Networks.
[26] Pat Langley,et al. Estimating Continuous Distributions in Bayesian Classifiers , 1995, UAI.
[27] Binod Vaidya,et al. SensorFall - An Accelerometer Based Mobile Application , 2009, 2009 2nd International Conference on Computer Science and its Applications.
[28] Begoña García Zapirain,et al. Mobile communication for intellectually challenged people: a proposed set of requirements for interface design on touch screen devices , 2012, Communications in Mobile Computing.
[29] C. Todd,et al. World Health Organisation Global Report on Falls Prevention in Older Age , 2007 .
[30] M. Tinetti,et al. Risk factors for falls among elderly persons living in the community. , 1988, The New England journal of medicine.
[31] Young-Koo Lee,et al. Comprehensive Context Recognizer Based on Multimodal Sensors in a Smartphone , 2012, Sensors.
[32] Hamit Erdem,et al. A multi-channel remote controller for home and office appliances , 2009, IEEE Transactions on Consumer Electronics.
[33] B. Hjorth. EEG analysis based on time domain properties. , 1970, Electroencephalography and clinical neurophysiology.
[34] Cem Ersoy,et al. A Review and Taxonomy of Activity Recognition on Mobile Phones , 2013 .
[35] Juan-Luis Gorricho,et al. Surveillance with Alert Management System Using Conventional Cell Phones , 2010, 2010 Fifth International Multi-conference on Computing in the Global Information Technology.
[36] G. Miller,et al. Science Perspectives on Psychological the Smartphone Psychology Manifesto on Behalf Of: Association for Psychological Science the Smartphone Psychology Manifesto Previous Research Using Mobile Electronic Devices What Smartphones Can Do Now and Will Be Able to Do in the near Future , 2022 .
[37] Hartmut König,et al. Location-independent fall detection with smartphone , 2013, PETRA '13.
[38] Andrew Boehner. A Smartphone Application for a Portable Fall Detection System , 2013 .
[39] Raymond Y. W. Lee,et al. Detection of falls using accelerometers and mobile phone technology. , 2011, Age and ageing.
[40] E. Thammasat,et al. A simply fall-detection algorithm using accelerometers on a smartphone , 2012, The 5th 2012 Biomedical Engineering International Conference.
[41] A. K. Singh,et al. Using Android platform to detect free fall , 2013, 2013 International Conference on Information Systems and Computer Networks.
[42] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[43] Davide Carneiro,et al. A multi-modal approach for activity classification and fall detection , 2014, Int. J. Syst. Sci..
[44] S. Cerutti,et al. Falls event detection using triaxial accelerometry and barometric pressure measurement , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[45] Deborah Estrin,et al. Diversity in smartphone usage , 2010, MobiSys '10.
[46] P. Laippala,et al. Falls and lying helpless in the elderly. , 1992, Zeitschrift fur Gerontologie.
[47] Mihail Popescu,et al. Acoustic fall detection using a circular microphone array , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[48] Maria Virvou,et al. Intelligent Mobile Multimedia Application for the Support of the Elderly , 2012, 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.
[49] Raveendra Hegde,et al. Technical Advances in Fall Detection System – A Review , 2013 .
[50] R. K. Megalingam,et al. HOPE: An electronic gadget for home-bound patients and elders , 2012, 2012 Annual IEEE India Conference (INDICON).
[51] M. Kangas,et al. Determination of simple thresholds for accelerometry-based parameters for fall detection , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[52] J.R. Casar,et al. Context-aware services for ambient assisted living: A case-study , 2008, 2008 First International Symposium on Applied Sciences on Biomedical and Communication Technologies.
[53] Dong Xuan,et al. PerFallD: A pervasive fall detection system using mobile phones , 2010, 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).
[54] Sheikh Iqbal Ahamed,et al. smartPrediction: a real-time smartphone-based fall risk prediction and prevention system , 2013, RACS.
[55] Wan-Young Chung,et al. Visual Sensor Based Abnormal Event Detection with Moving Shadow Removal in Home Healthcare Applications , 2012, Sensors.
[56] Gary M. Weiss,et al. Applications of mobile activity recognition , 2012, UbiComp.
[57] Keith Hill,et al. Design-related bias in hospital fall risk screening tool predictive accuracy evaluations: systematic review and meta-analysis. , 2007, The journals of gerontology. Series A, Biological sciences and medical sciences.
[58] Joaquim Gabriel,et al. Active assistance for senior healthcare: A wearable system for fall detection , 2013, 2013 8th Iberian Conference on Information Systems and Technologies (CISTI).
[59] Matthias Gietzelt,et al. Fall detection on the road , 2013, 2013 IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013).
[60] A. Oguz KANSIZ,et al. Selection of Time-Domain Features for Fall Detection Based on Supervised Learning , .
[61] Gueesang Lee,et al. Fall Detection Based on Movement and Smart Phone Technology , 2012, 2012 IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future.
[62] Amy Loutfi,et al. Evaluation of the android-based fall detection system with physiological data monitoring , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[63] Joel J. P. C. Rodrigues,et al. Towards an autonomous fall detection and alerting system on a mobile and pervasive environment , 2011, Telecommunication Systems.
[64] Siv Sadigh,et al. Falls and Fall-Related Injuries Among the Elderly: A Survey of Residential-Care Facilities in a Swedish Municipality , 2004, Journal of Community Health.
[65] Dimitrios Makris,et al. Fall detection system using Kinect’s infrared sensor , 2014, Journal of Real-Time Image Processing.
[66] S. Brownsell,et al. Do community alarm users want telecare? , 2000, Journal of telemedicine and telecare.
[67] Ying-Wen Bai,et al. Design and implementation of a fall monitor system by using a 3-axis accelerometer in a smart phone , 2012, 2012 IEEE 16th International Symposium on Consumer Electronics.
[68] Martin J.-D. Otis,et al. Toward an augmented shoe for preventing falls related to physical conditions of the soil , 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
[69] A. Bourke,et al. Fall detection - Principles and Methods , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[70] Alberto Maria Segre,et al. Programs for Machine Learning , 1994 .
[71] Bingchuan Yuan. Non-intrusive Movement Detection in CARA Pervasive Healthcare Application , 2011 .
[72] Oh-young Kwon,et al. Design of U-Health System with the Use of Smart Phone and Sensor Network , 2010, 2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications.
[73] Jeffrey M. Hausdorff,et al. Comparison of acceleration signals of simulated and real-world backward falls. , 2011, Medical engineering & physics.
[74] Stefan Madansingh,et al. Smartphone based fall detection system , 2015, 2015 15th International Conference on Control, Automation and Systems (ICCAS).
[75] Philip Heng Wai Leong,et al. Development of a Human Airbag System for Fall Protection Using MEMS Motion Sensing Technology , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[76] Konrad Paul Kording,et al. Fall Classification by Machine Learning Using Mobile Phones , 2012, PloS one.
[77] Kazuhiro Kosuge,et al. Motion control of intelligent passive-type Walker for fall-prevention function based on estimation of user state , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..
[79] Arthur D. Fisk,et al. Designing for Older Adults: Principles and Creative Human Factors Approaches , 2004 .
[80] Jer-Vui Lee,et al. Smart Elderly Home Monitoring System with an Android Phone , 2013 .
[81] J. Painter,et al. Living Alone and Fall Risk Factors in Community-Dwelling Middle Age and Older Adults , 2009, Journal of community health.
[82] Ye Li,et al. Falling-Incident Detection and Alarm by Smartphone with Multimedia Messaging Service (MMS) , 2012 .
[83] Yujiu Yang,et al. E-FallD: A fall detection system using android-based smartphone , 2012, 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery.
[84] Alessio Vecchio,et al. A smartphone-based fall detection system , 2012, Pervasive Mob. Comput..
[85] John G. Cleary,et al. K*: An Instance-based Learner Using and Entropic Distance Measure , 1995, ICML.
[86] Shih-Hau Fang,et al. Developing a mobile phone-based fall detection system on Android platform , 2012, 2012 Computing, Communications and Applications Conference.
[87] Sergios Theodoridis,et al. Introduction to Pattern Recognition: A Matlab Approach , 2010 .
[88] Shuangquan Wang,et al. FallAlarm: Smart Phone Based Fall Detecting and Positioning System , 2012, ANT/MobiWIS.
[89] Deokjai Choi,et al. Semi-supervised fall detection algorithm using fall indicators in smartphone , 2012, ICUIMC '12.
[90] Toshiyo Tamura,et al. A Wearable Airbag to Prevent Fall Injuries , 2009, IEEE Transactions on Information Technology in Biomedicine.
[91] Andrew Charlesworth. The ascent of smartphone , 2009 .
[92] Bernd Schulze,et al. Concept and Design of a Video Monitoring System for Activity Recognition and Fall Detection , 2009, ICOST.
[93] Inmaculada Plaza,et al. Challenges, issues and trends in fall detection systems , 2013, Biomedical engineering online.
[94] Kazuhiro Kosuge,et al. Fall prevention control of passive intelligent walker based on human model , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[95] Ye Li,et al. Fall detection by built-in tri-accelerometer of smartphone , 2012, Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics.
[96] Yiqiang Chen,et al. Fall Detecting and Alarming Based on Mobile Phone , 2010, 2010 7th International Conference on Ubiquitous Intelligence & Computing and 7th International Conference on Autonomic & Trusted Computing.
[97] Jian Huang,et al. A novel fall prevention scheme for intelligent cane robot by using a motor driven universal joint , 2011, 2011 International Symposium on Micro-NanoMechatronics and Human Science.
[98] Axel Steinhage,et al. Monitoring Movement Behavior by Means of a Large Area Proximity Sensor Array in the Floor , 2008, BMI.
[99] C. Becker,et al. Smartphone-based solutions for fall detection and prevention: the FARSEEING approach , 2012, Zeitschrift für Gerontologie und Geriatrie.
[100] Lei Wang,et al. Exploration and Implementation of a Pre-Impact Fall Recognition Method Based on an Inertial Body Sensor Network , 2012, Sensors.
[101] Shang-Lin Hsieh,et al. A Finite State Machine-Based Fall Detection Mechanism on Smartphones , 2012, 2012 9th International Conference on Ubiquitous Intelligence and Computing and 9th International Conference on Autonomic and Trusted Computing.
[102] Norbert Noury,et al. A feasibility study of using a smartphone to monitor mobility in elderly , 2012, 2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom).
[103] Lorenzo Chiari,et al. Smartphone-based applications for investigating falls and mobility , 2011, 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops.
[104] Majid Sarrafzadeh,et al. A Remote Patient Monitoring System for Congestive Heart Failure , 2011, Journal of Medical Systems.
[105] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[106] Yun Li,et al. A Microphone Array System for Automatic Fall Detection , 2012, IEEE Transactions on Biomedical Engineering.
[107] Jian Huang,et al. Real-time fall and overturn prevention control for human-cane robotic system , 2013, IEEE ISR 2013.
[108] Jesús Fontecha,et al. Elderly frailty detection by using accelerometer-enabled smartphones and clinical information records , 2012, Personal and Ubiquitous Computing.
[109] Wen-Chang Cheng,et al. Fall Detection with the Support Vector Machine during Scripted and Continuous Unscripted Activities , 2012, Sensors.
[110] H. S. Wolff,et al. iRun: Horizontal and Vertical Shape of a Region-Based Graph Compression , 2022, Sensors.
[111] Inmaculada Plaza,et al. Guidelines to Design Smartphone Applications for People with Intellectual Disability: A Practical Experience , 2013, ISAmI.
[112] Jean Meunier,et al. Robust Video Surveillance for Fall Detection Based on Human Shape Deformation , 2011, IEEE Transactions on Circuits and Systems for Video Technology.
[113] Nancy Fell,et al. Telemedicine assessment of fall risk using wireless sensors , 2013, 2013 IEEE International Conference on Sensing, Communications and Networking (SECON).
[114] Peter P. K. Chiu,et al. Health Guard system with emergency call based on smartphone , 2011 .