Practical fall detection based on IoT technologies: A survey

Abstract Fall is the second incident that leads to death over the world. Fall event happens to numerous groups of people consist of elderly, babies and also younger people. Admittedly, fall-related research must be considered as one of the most important aspects of a healthy lifestyle. For this reason, Internet of Things(IoT) is the emerging technology and a powerful candidate to develop fall diagnosis system. In this paper, we have discussed the three stages of fall as Prediction, Prevention, and Detection. We have illustrated Edge, Fog, and Cloud layers as IoT layers to develop a fall diagnosis system. At the end of the paper, we have considered the challenges of fall diagnosis systems and suggested future aspects.

[1]  Yasuhisa Hasegawa,et al.  Fall Detection and Prevention Control Using Walking-Aid Cane Robot , 2016, IEEE/ASME Transactions on Mechatronics.

[2]  Muhammad Bin Altaf,et al.  A high accuracy and low latency patient-specific wearable fall detection system , 2017, 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

[3]  Himanshu Thapliyal,et al.  IoT-Based Fall Detection for Smart Home Environments , 2016, 2016 IEEE International Symposium on Nanoelectronic and Information Systems (iNIS).

[4]  Nadia Magnenat-Thalmann,et al.  Fall Detection Based on Body Part Tracking Using a Depth Camera , 2015, IEEE Journal of Biomedical and Health Informatics.

[5]  Donald Y. C. Lie,et al.  An Efficient and Robust Fall Detection System Using Wireless Gait Analysis Sensor with Artificial Neural Network (ANN) and Support Vector Machine (SVM) Algorithms , 2014 .

[6]  Miguel A. Labrador,et al.  A Survey on Human Activity Recognition using Wearable Sensors , 2013, IEEE Communications Surveys & Tutorials.

[7]  Sam Kwong,et al.  Hilbert-Huang Transform for Analysis of Heart Rate Variability in Cardiac Health , 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[8]  I. K. E. Purnama,et al.  A wearable device for fall detection elderly people using tri dimensional accelerometer , 2016, 2016 International Seminar on Intelligent Technology and Its Applications (ISITIA).

[9]  Panayiotis Tsanakas,et al.  Fall Detection Using Commodity Smart Watch and Smart Phone , 2014, AIAI.

[10]  Giancarlo Fortino,et al.  Cloud-based Activity-aaService cyber-physical framework for human activity monitoring in mobility , 2017, Future Gener. Comput. Syst..

[11]  Kai-Chun Liu,et al.  A machine learning approach to fall detection algorithm using wearable sensor , 2016, 2016 International Conference on Advanced Materials for Science and Engineering (ICAMSE).

[12]  Eryk Dutkiewicz,et al.  Superior Path Planning Mechanism for Mobile Beacon-Assisted Localization in Wireless Sensor Networks , 2014, IEEE Sensors Journal.

[13]  Mohamed S. Shehata,et al.  Structural Health Monitoring Using Wireless Sensor Networks: A Comprehensive Survey , 2017, IEEE Communications Surveys & Tutorials.

[14]  Senem Velipasalar,et al.  A Survey on Activity Detection and Classification Using Wearable Sensors , 2017, IEEE Sensors Journal.

[15]  Alessio Vecchio,et al.  A smartphone-based fall detection system , 2012, Pervasive Mob. Comput..

[16]  Kumbesan Sandrasegaran,et al.  Transmission Power Adjustment Scheme for Mobile Beacon-Assisted Sensor Localization , 2019, IEEE Transactions on Industrial Informatics.

[17]  Gerhard Tröster,et al.  Eye Movement Analysis for Activity Recognition Using Electrooculography , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Bruno M. C. Silva,et al.  An IoT-based mobile gateway for intelligent personal assistants on mobile health environments , 2016, J. Netw. Comput. Appl..

[19]  Toshiyo Tamura,et al.  A Wearable Airbag to Prevent Fall Injuries , 2009, IEEE Transactions on Information Technology in Biomedicine.

[20]  K. Narendra Swaroop,et al.  A health monitoring system for vital signs using IoT , 2019, Internet Things.

[21]  Sridhar Krishnan,et al.  Biosignal monitoring using wearables: Observations and opportunities , 2017, Biomed. Signal Process. Control..

[22]  Emmanuel Andrès,et al.  From Fall Detection to Fall Prevention: A Generic Classification of Fall-Related Systems , 2017, IEEE Sensors Journal.

[23]  M. S. Huq,et al.  Smartphone Based Data Mining for Fall Detection , 2017 .

[24]  Yaser Mowafi,et al.  A fall prediction methodology for elderly based on a depth camera , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[25]  M. Helbich,et al.  Pedestrian falls: A review of the literature and future research directions. , 2017, Journal of safety research.

[26]  Danilo De Donno,et al.  An IoT-Aware Architecture for Smart Healthcare Systems , 2015, IEEE Internet of Things Journal.

[27]  Neha Bhati mHealth based ubiquitous fall detection for elderly people , 2017, 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT).

[28]  Kumbesan Sandrasegaran,et al.  A survey on data aggregation techniques in IoT sensor networks , 2020, Wirel. Networks.

[29]  Alireza Bagheri,et al.  Indoor navigation systems based on data mining techniques in internet of things: a survey , 2018, Wirel. Networks.

[30]  Yinghuan Shi,et al.  mPadal: a joint local-and-global multi-view feature selection method for activity recognition , 2014, Applied Intelligence.

[31]  Jau-Woei Perng,et al.  Development of a vision based pedestrian fall detection system with back propagation neural network , 2015, 2015 IEEE/SICE International Symposium on System Integration (SII).

[32]  Hannu Tenhunen,et al.  IoT-based fall detection system with energy efficient sensor nodes , 2016, 2016 IEEE Nordic Circuits and Systems Conference (NORCAS).

[33]  M N Nyan,et al.  A wearable system for pre-impact fall detection. , 2008, Journal of biomechanics.

[34]  Bjoern M. Eskofier,et al.  Parkinson’s disease as a Working Model for Global Healthcare Restructuration: The Internet of Things and Wearables Technologies , 2015, IOT 2015.

[35]  Vassilis Athitsos,et al.  A survey on vision-based fall detection , 2015, PETRA.

[36]  Wu Jianfeng,et al.  FALL DETECTION USING THREE WEARABLE TRIAXIAL ACCELEROMETERS AND A DECISION-TREE CLASSIFIER , 2014 .

[37]  Fergyanto E. Gunawan,et al.  Fall Detection Algorithm to Generate Security Alert , 2015 .

[38]  He Jian,et al.  A portable fall detection and alerting system based on k-NN algorithm and remote medicine , 2015, China Communications.

[39]  Kaishun Wu,et al.  WiFall: Device-free fall detection by wireless networks , 2017, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[40]  Shadi Alawneh,et al.  Integrating wearables with cloud-based communication for health monitoring and emergency assistance , 2018, Internet Things.

[41]  Wei Hu,et al.  Fall perception for elderly care: A fall detection algorithm in Smart Wristlet mHealth system , 2014, 2014 IEEE International Conference on Communications (ICC).

[42]  Jung Keun Lee,et al.  Inertial Sensing-Based Pre-Impact Detection of Falls Involving Near-Fall Scenarios , 2015, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[43]  Miguel A. Labrador,et al.  Survey on Fall Detection and Fall Prevention Using Wearable and External Sensors , 2014, Sensors.

[44]  Yasuhisa Hasegawa,et al.  Tandem Stance Avoidance Using Adaptive and Asymmetric Admittance Control for Fall Prevention. , 2016, IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[45]  Hadi Tabatabaee Malazi,et al.  Combining emerging patterns with random forest for complex activity recognition in smart homes , 2018, Applied Intelligence.

[46]  Jonghoon Kim,et al.  An Internet-of-Things (IoT) System Development and Implementation for Bathroom Safety Enhancement , 2016 .

[47]  Abbes Amira,et al.  CS-based fall detection for connected health applications , 2017, 2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME).

[48]  Surapa Thiemjarus,et al.  Automatic Fall Monitoring: A Review , 2014, Sensors.

[49]  Lih-Jen Kau,et al.  A Smart Phone-Based Pocket Fall Accident Detection, Positioning, and Rescue System , 2015, IEEE Journal of Biomedical and Health Informatics.

[50]  G. Earhart,et al.  Two-Year Trajectory of Fall Risk in People With Parkinson Disease: A Latent Class Analysis. , 2016, Archives of physical medicine and rehabilitation.

[51]  Bogdan Kwolek,et al.  Event-driven system for fall detection using body-worn accelerometer and depth sensor , 2018, IET Comput. Vis..

[52]  Mohammed Riyaz Ahmed,et al.  Architecture for IOT based geriatric care fall detection and prevention , 2017, 2017 International Conference on Intelligent Computing and Control Systems (ICICCS).

[53]  Albert Y. Zomaya,et al.  On the Correlation of Sensor Location and Human Activity Recognition in Body Area Networks (BANs) , 2018, IEEE Systems Journal.

[54]  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.

[55]  Ercan Erdis,et al.  Decision tree analysis of construction fall accidents involving roofers , 2015, Expert Syst. Appl..

[56]  Marjan Moradi,et al.  Message-Efficient Localization in Mobile Wireless Sensor Networks , 2012 .

[57]  Ding Liang,et al.  Pre-impact & impact detection of falls using wireless Body Sensor Network , 2012, Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics.

[58]  Andrea Zanella,et al.  Internet of Things for Smart Cities , 2014, IEEE Internet of Things Journal.

[59]  A. Bourke,et al.  The identification of vertical velocity profiles using an inertial sensor to investigate pre-impact detection of falls. , 2008, Medical Engineering and Physics.

[60]  Ling Shao,et al.  A survey on fall detection: Principles and approaches , 2013, Neurocomputing.

[61]  Roberto Setola,et al.  Fall-detection solution for mobile platforms using accelerometer and gyroscope data , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[62]  Abdul Rahman Ramli,et al.  Development of Wearable Human Fall Detection System using Multilayer Perceptron Neural Network , 2013, Int. J. Comput. Intell. Syst..

[63]  Javad Rezazadeh,et al.  Mobile Wireless Sensor Networks Overview , 2012 .

[64]  Ahmad Almogren,et al.  A robust human activity recognition system using smartphone sensors and deep learning , 2018, Future Gener. Comput. Syst..

[65]  Hannu Tenhunen,et al.  Energy efficient wearable sensor node for IoT-based fall detection systems , 2018, Microprocess. Microsystems.

[66]  Panagiotis G. Sarigiannidis,et al.  Securing the Internet of Things: Challenges, threats and solutions , 2019, Internet Things.

[67]  Francesco Piazza,et al.  Human Fall Detection by Using an Innovative Floor Acoustic Sensor , 2018, Multidisciplinary Approaches to Neural Computing.

[68]  Marjorie Skubic,et al.  Fall Detection in Homes of Older Adults Using the Microsoft Kinect , 2015, IEEE Journal of Biomedical and Health Informatics.

[69]  Dong-Soo Kwon,et al.  Histogram based fall prediction of patients using a thermal imagery camera , 2017, 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI).

[70]  Wei Xiang,et al.  Internet of Things for Smart Healthcare: Technologies, Challenges, and Opportunities , 2017, IEEE Access.

[71]  Young-Koo Lee,et al.  Semi-Markov conditional random fields for accelerometer-based activity recognition , 2010, Applied Intelligence.

[72]  Jafri Mohd Rohani,et al.  Perception Study on Leading Factors of Slip and Fall Incidents in Manufacturing Industry , 2015 .

[73]  Laurence T. Yang,et al.  An Intelligent Information Forwarder for Healthcare Big Data Systems With Distributed Wearable Sensors , 2016, IEEE Systems Journal.

[74]  Yun Li,et al.  A Microphone Array System for Automatic Fall Detection , 2012, IEEE Transactions on Biomedical Engineering.

[75]  Mohammad Mansour Riahi Kashani,et al.  Efficient job scheduling in cloud computing based on genetic algorithm , 2019 .

[76]  Luis González Abril,et al.  Mobile activity recognition and fall detection system for elderly people using Ameva algorithm , 2017, Pervasive Mob. Comput..

[77]  Jin-xiang Wang,et al.  Pedestrian Fall Action Detection and Alarm in Video Surveillance , 2016, 2016 3rd International Conference on Information Science and Control Engineering (ICISCE).

[78]  Jiann Shing Shieh,et al.  A threshold-based algorithm of fall detection using a wearable device with tri-axial accelerometer and gyroscope , 2015, 2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS).

[79]  Victor R. L. Shen,et al.  The implementation of a smartphone-based fall detection system using a high-level fuzzy Petri net , 2015, Appl. Soft Comput..

[80]  Hiroshi Mizoguchi,et al.  Living Function Resilient Service Using a Mock Living Lab and Real Living Labs: Development of Balcony-IoT and Handrail-IoT for Healthcare , 2017, EUSPN/ICTH.

[81]  Giuseppe De Pietro,et al.  A supervised approach to automatically extract a set of rules to support fall detection in an mHealth system , 2015, Appl. Soft Comput..

[82]  Yunjian Ge,et al.  HMM-Based Human Fall Detection and Prediction Method Using Tri-Axial Accelerometer , 2013, IEEE Sensors Journal.

[83]  M. Popescu,et al.  Acoustic fall detection using one-class classifiers , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[84]  Max A. Little,et al.  Freezing of gait and fall detection in Parkinson’s disease using wearable sensors: a systematic review , 2017, Journal of Neurology.

[85]  Senem Velipasalar,et al.  Wearable Camera- and Accelerometer-Based Fall Detection on Portable Devices , 2016, IEEE Embedded Systems Letters.

[86]  Ren-Jye Dzeng,et al.  Accelerometer-based fall-portent detection algorithm for construction tiling operation , 2017 .

[87]  Jie Li,et al.  An improved classification method for fall detection based on Bayesian framework , 2015, 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[88]  Miao Yu,et al.  An Online One Class Support Vector Machine-Based Person-Specific Fall Detection System for Monitoring an Elderly Individual in a Room Environment , 2013, IEEE Journal of Biomedical and Health Informatics.

[89]  Joel J. P. C. Rodrigues,et al.  A mobile health application for falls detection and biofeedback monitoring , 2013, 2013 IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013).

[90]  Hesham A. El Zouka,et al.  Secure IoT communications for smart healthcare monitoring system , 2019, Internet Things.

[91]  S. Rihana,et al.  Wearable fall detection system , 2016, 2016 3rd Middle East Conference on Biomedical Engineering (MECBME).

[92]  Ilias Maglogiannis,et al.  Emergency Fall Incidents Detection in Assisted Living Environments Utilizing Motion, Sound, and Visual Perceptual Components , 2011, IEEE Transactions on Information Technology in Biomedicine.

[93]  Tao Xu,et al.  New Advances and Challenges of Fall Detection Systems: A Survey , 2018 .

[94]  Daniela De Venuto,et al.  Gait analysis for fall prediction using EMG triggered movement related potentials , 2015, 2015 10th International Conference on Design & Technology of Integrated Systems in Nanoscale Era (DTIS).

[95]  Marjan Moradi,et al.  Efficient localization via Middle-node cooperation in wireless sensor networks , 2011, International Conference on Electrical, Control and Computer Engineering 2011 (InECCE).

[96]  Larinni Malheiros,et al.  Fall detection system and Body positioning with Heart Rate Monitoring , 2017, IEEE Latin America Transactions.

[97]  Jeffrey M. Voas,et al.  Stakeholder Identification and Use Case Representation for Internet-of-Things Applications in Healthcare , 2018, IEEE Systems Journal.

[98]  Paola Pierleoni,et al.  A High Reliability Wearable Device for Elderly Fall Detection , 2015, IEEE Sensors Journal.

[99]  Daqing Zhang,et al.  RT-Fall: A Real-Time and Contactless Fall Detection System with Commodity WiFi Devices , 2017, IEEE Transactions on Mobile Computing.

[100]  Kumbesan Sandrasegaran,et al.  Crowdsourcing and Sensing for Indoor Localization in IoT: A Review , 2019, IEEE Sensors Journal.

[101]  Luca Benini,et al.  Accelerometer-based fall detection using optimized ZigBee data streaming , 2010, Microelectron. J..

[102]  Turgay Tugay Bilgin,et al.  A data mining approach for fall detection by using k-nearest neighbour algorithm on wireless sensor network data , 2012, IET Commun..

[103]  Abdul Rahman Ramli,et al.  A pervasive neural network based fall detection system on smart phone , 2015, J. Ambient Intell. Smart Environ..

[104]  Senem Velipasalar,et al.  Automatic Fall Detection and Activity Classification by a Wearable Embedded Smart Camera , 2013, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[105]  Kumbesan Sandrasegaran,et al.  Novel iBeacon Placement for Indoor Positioning in IoT , 2018, IEEE Sensors Journal.

[106]  Javad Rezazadeh,et al.  Middleware Technologies for Cloud of Things - a survey , 2017, Digit. Commun. Networks.

[107]  Hiroaki Nishino,et al.  A robot motion design scheme for watching the elderly based on human gesture sensing , 2019, Internet Things.

[108]  Pramod K. Varshney,et al.  Autonomous Fall Detection With Wearable Cameras by Using Relative Entropy Distance Measure , 2017, IEEE Transactions on Human-Machine Systems.

[109]  Ming-Yuan Huang,et al.  Elderly Taiwanese's intrinsic risk factors for fall-related injuries , 2016 .

[110]  Ali Javed,et al.  A framework for fall detection of elderly people by analyzing environmental sounds through acoustic local ternary patterns , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[111]  Marjan Moradi,et al.  A Reverse Localization Scheme for Underwater Acoustic Sensor Networks , 2012, Sensors.

[112]  Nelson Luis Saldanha da Fonseca,et al.  The Internet of Things, Fog and Cloud Continuum: Integration and Challenges , 2018, Internet Things.

[113]  Ennio Gambi,et al.  Radar and RGB-Depth Sensors for Fall Detection: A Review , 2017, IEEE Sensors Journal.

[114]  Li Chen,et al.  Implementation of a Physical Activity Monitoring System for the Elderly People with Built-in Vital Sign and Fall Detection , 2009, 2009 Sixth International Conference on Information Technology: New Generations.

[115]  Shahrokh Valaee,et al.  Locomotion Activity Recognition Using Stacked Denoising Autoencoders , 2018, IEEE Internet of Things Journal.

[116]  Barathram Ramkumar,et al.  Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier. , 2015, Healthcare technology letters.

[117]  Basel Kikhia,et al.  Utilizing a Wristband Sensor to Measure the Stress Level for People with Dementia , 2016, Sensors.

[118]  Wei Sun,et al.  A Survey of Fall Detection Algorithm for Elderly Health Monitoring , 2015, 2015 IEEE Fifth International Conference on Big Data and Cloud Computing.

[119]  Satish Narayana Srirama,et al.  Edge Process Management: A case study on adaptive task scheduling in mobile IoT , 2019, Internet Things.

[120]  Zhenyu Wang,et al.  Algorithm of the fall prediction based on the double foot pressure and Micro Inertial sensors , 2016, 2016 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER).

[121]  Pietro Siciliano,et al.  Support Vector Machine for tri-axial accelerometer-based fall detector , 2013, 5th IEEE International Workshop on Advances in Sensors and Interfaces IWASI.

[122]  Victor R. L. Shen,et al.  A Novel Fall Prediction System on Smartphones , 2017, IEEE Sensors Journal.

[123]  Widyawan,et al.  Fall detection system using accelerometer and gyroscope based on smartphone , 2014, 2014 The 1st International Conference on Information Technology, Computer, and Electrical Engineering.

[124]  Mehmet C. Vuran,et al.  Semi-supervised near-miss fall detection for ironworkers with a wearable inertial measurement unit , 2016 .

[125]  Eryk Dutkiewicz,et al.  Impact of static trajectories on localization in wireless sensor networks , 2015, Wirel. Networks.

[126]  Widyawardana Adiprawita,et al.  A simple design of wearable device for fall detection with accelerometer and gyroscope , 2016, 2016 International Symposium on Electronics and Smart Devices (ISESD).

[127]  Riad Kanan,et al.  An IoT-based autonomous system for workers' safety in construction sites with real-time alarming, monitoring, and positioning strategies , 2018 .

[128]  Yun Gao,et al.  A low-power, wireless, wrist-worn device for long time heart rate monitoring and fall detection , 2014, 2014 International Conference on Orange Technologies.

[129]  Chao-Ting Chu,et al.  A Laypunov base fuzzy expert knowledge model identify elders fall signal , 2018, 2018 7th International Symposium on Next Generation Electronics (ISNE).

[130]  Li Feng,et al.  Deep Learning for Fall Detection: Three-Dimensional CNN Combined With LSTM on Video Kinematic Data , 2019, IEEE Journal of Biomedical and Health Informatics.

[131]  Haibo Wang,et al.  Silhouette Orientation Volumes for Efficient Fall Detection in Depth Videos , 2017, IEEE Journal of Biomedical and Health Informatics.

[132]  Y. Choi,et al.  A Study on Machine Learning Algorithms for Fall Detection and Movement Classification , 2011, 2011 International Conference on Information Science and Applications.

[133]  Jennifer Howcroft,et al.  Prospective Fall-Risk Prediction Models for Older Adults Based on Wearable Sensors , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[134]  Kumbesan Sandrasegaran,et al.  A location-based smart shopping system with IoT technology , 2018, 2018 IEEE 4th World Forum on Internet of Things (WF-IoT).

[135]  Wen-Chang Cheng,et al.  Triaxial Accelerometer-Based Fall Detection Method Using a Self-Constructing Cascade-AdaBoost-SVM Classifier , 2013, IEEE Journal of Biomedical and Health Informatics.

[136]  N. Kumar,et al.  Novel fall detection algorithm for the elderly people , 2014, 2014 International Conference on Science Engineering and Management Research (ICSEMR).

[137]  Michael Cheffena,et al.  Fall Detection Using Smartphone Audio Features , 2016, IEEE Journal of Biomedical and Health Informatics.

[138]  M. Shamim Hossain,et al.  A knowledge-driven approach for activity recognition in smart homes based on activity profiling , 2020, Future Gener. Comput. Syst..

[139]  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).

[140]  Athanasios I. Kyritsis,et al.  F2D: A Location Aware Fall Detection System Tested with Real Data from Daily Life of Elderly People , 2016, EUSPN/ICTH.

[141]  Keiichiro Hoashi,et al.  Primitive activity recognition from short sequences of sensory data , 2018, Applied Intelligence.