Robust unobtrusive fall detection using infrared array sensors

As the world's aging population grows, fall is becoming a major problem in public health. It is one of the most vital risk to the elderly. Many technology based fall detection systems have been developed in recent years with hardware ranging from wearable devices to ambience sensors and video cameras. Several machine learning based fall detection classifiers have been developed to process sensor data with various degrees of success. In this paper, we present a fall detection system using infrared array sensors with several deep learning methods, including long-short-term-memory and gated recurrent unit models. Evaluated with fall data collected in two different sets of configurations, we show that our approach gives significant improvement over existing works using the same infrared array sensor.

[1]  R. Bajcsy,et al.  Wearable Sensors for Reliable Fall Detection , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[2]  Mitja Lustrek,et al.  Fall Detection and Activity Recognition with Machine Learning , 2009, Informatica.

[3]  Xuemei Guo,et al.  Elderly-falling detection using distributed direction-sensitive pyroelectric infrared sensor arrays , 2012, Multidimens. Syst. Signal Process..

[4]  Gang Zhou,et al.  Accurate, Fast Fall Detection Using Gyroscopes and Accelerometer-Derived Posture Information , 2009, 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks.

[5]  Sahibsingh A. Dudani.  The Distance-Weighted k-Nearest-Neighbor Rule , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[6]  Stephen J. McKenna,et al.  Activity summarisation and fall detection in a supportive home environment , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[7]  K. S. Park,et al.  Fall detection algorithm for the elderly using acceleration sensors on the shoes , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  Yoshua Bengio,et al.  Attention-Based Models for Speech Recognition , 2015, NIPS.

[9]  Jihoon Hong,et al.  A fall detection system using low resolution infrared array sensor , 2014, 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC).

[10]  Neil Johnson,et al.  A smart sensor to detect the falls of the elderly , 2004, IEEE Pervasive Computing.

[11]  Xinguo Yu.  Approaches and principles of fall detection for elderly and patient , 2008, HealthCom 2008 - 10th International Conference on e-health Networking, Applications and Services.

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

[13]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.

[14]  David A. Landgrebe,et al.  A survey of decision tree classifier methodology , 1991, IEEE Trans. Syst. Man Cybern..

[15]  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.

[16]  Tong Zhang,et al.  Fall Detection by Embedding an Accelerometer in Cellphone and Using KFD Algorithm , 2006 .

[17]  Huan-Wen Tzeng,et al.  Design of fall detection system with floor pressure and infrared image , 2010, 2010 International Conference on System Science and Engineering.

[18]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[19]  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.

[20]  Nan Hu,et al.  A Network-Based Environment of Female Pelvic Region for Anatomical Education Based on Chinese Visible Human Datasets , 2009, 2009 2nd International Conference on Biomedical Engineering and Informatics.

[21]  Zoubin Ghahramani,et al.  An Introduction to Hidden Markov Models and Bayesian Networks , 2001, Int. J. Pattern Recognit. Artif. Intell..

[22]  Tarek F. Abdelzaher,et al.  SATIRE: a software architecture for smart AtTIRE , 2006, MobiSys '06.

[23]  Alistair Armitage,et al.  A touchless passive infrared gesture sensor , 2013, UIST '13 Adjunct.

[24]  Jiewen Zheng,et al.  Design of Automatic Fall Detector for Elderly Based on Triaxial Accelerometer , 2009, 2009 3rd International Conference on Bioinformatics and Biomedical Engineering.

[25]  A K Bourke,et al.  Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. , 2007, Gait & posture.

[26]  Matjaz Gams,et al.  Efficient Activity Recognition and Fall Detection Using Accelerometers , 2013, EvAAL.

[27]  Dimitrios Makris,et al.  Fall detection system using Kinect’s infrared sensor , 2014, Journal of Real-Time Image Processing.

[28]  A. Bourke,et al.  Fall detection - Principles and Methods , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[29]  Yoshua Bengio,et al.  Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.

[30]  A. Bourke,et al.  A threshold-based fall-detection algorithm using a bi-axial gyroscope sensor. , 2008, Medical engineering & physics.

[31]  Gang Zhou,et al.  Accurate, fast fall detection using posture and context information , 2008, SenSys '08.

[32]  Jean Meunier,et al.  Fall Detection from Human Shape and Motion History Using Video Surveillance , 2007, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07).

[33]  Jeffrey M. Hausdorff,et al.  Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls , 2012, PloS one.

[34]  S. Miaou,et al.  A Customized Human Fall Detection System Using Omni-Camera Images and Personal Information , 2006, 1st Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare, 2006. D2H2..

[35]  H.C. Kim,et al.  Development of novel algorithm and real-time monitoring ambulatory system using Bluetooth module for fall detection in the elderly , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[36]  Martina Ziefle,et al.  Future Care Floor: A Sensitive Floor for Movement Monitoring and Fall Detection in Home Environments , 2010, MobiHealth.

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

[38]  Liang Liu,et al.  An automatic fall detection framework using data fusion of Doppler radar and motion sensor network , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[39]  Tong Zhang,et al.  Fall Detection by Wearable Sensor and One-Class SVM Algorithm , 2006 .

[40]  Hsi-Pin Ma,et al.  A fall detection system based on infrared array sensors with tracking capability for the elderly at home , 2015, 2015 17th International Conference on E-health Networking, Application & Services (HealthCom).

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