Fall Detection Using Wearable Accelerometers and Smartphone

The governments are investing in research on solutions for independent living, active ageing, at home health monitoring, with the objective of a significant prolongation of personal autonomy of older people. Fall avoidance and fall detection are important aspects of health care of ageing people. The proposed fall detection system consists in a wireless network with a smartphone and a board with another 3-axis accelerometer. The algorithm for fall detection is a part of a user friendly application developed for the smartphone. A comparison with existing fall detection systems and algorithms is reported.

[1]  Pietro Siciliano,et al.  Supervised machine learning scheme for tri-axial accelerometer-based fall detector , 2013, 2013 IEEE SENSORS.

[2]  Ya-Hsin Hsueh,et al.  Real-Time Fall Detecting System Using a Tri-axial Accelerometer for Home Care , 2012, 2012 International Conference on Biomedical Engineering and Biotechnology.

[3]  Jong Hyuk Park,et al.  Adaptive Body Posture Analysis for Elderly-Falling Detection with Multisensors , 2010, IEEE Intelligent Systems.

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

[5]  Waskitho Wibisono,et al.  Falls Detection and Notification System Using Tri-axial Accelerometer and Gyroscope Sensors of a Smartphone , 2013, 2013 Conference on Technologies and Applications of Artificial Intelligence.

[6]  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.

[7]  N. Noury.  A smart sensor for the remote follow up of activity and fall detection of the elderly , 2002, 2nd Annual International IEEE-EMBS Special Topic Conference on Microtechnologies in Medicine and Biology. Proceedings (Cat. No.02EX578).

[8]  Wan Young Chung,et al.  Activity monitoring from real-time triaxial accelerometer data using sensor network , 2007, 2007 International Conference on Control, Automation and Systems.

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

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

[11]  Javier Reina-Tosina,et al.  Design and Implementation of a Distributed Fall Detection System—Personal Server , 2009, IEEE Transactions on Information Technology in Biomedicine.

[12]  Wenlong Zhang,et al.  Fall-prediction algorithm using a neural network for safety enhancement of elderly , 2013, 2013 CACS International Automatic Control Conference (CACS).

[13]  Shuwan Xue,et al.  Portable Preimpact Fall Detector With Inertial Sensors , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[14]  Kamiar Aminian,et al.  Heel and Toe Clearance Estimation for Gait Analysis Using Wireless Inertial Sensors , 2012, IEEE Transactions on Biomedical Engineering.

[15]  Miao Yu,et al.  A Posture Recognition-Based Fall Detection System for Monitoring an Elderly Person in a Smart Home Environment , 2012, IEEE Transactions on Information Technology in Biomedicine.

[16]  Hassan Ghasemzadeh,et al.  Structural Action Recognition in Body Sensor Networks: Distributed Classification Based on String Matching , 2010, IEEE Transactions on Information Technology in Biomedicine.

[17]  E. Thammasat,et al.  A simply fall-detection algorithm using accelerometers on a smartphone , 2012, The 5th 2012 Biomedical Engineering International Conference.

[18]  A K Bourke,et al.  Evaluation of waist-mounted tri-axial accelerometer based fall-detection algorithms during scripted and continuous unscripted activities. , 2010, Journal of biomechanics.

[19]  Binh Q. Tran,et al.  Fall Detection System Using Combination Accelerometer and Gyroscope , 2013 .

[20]  Simone Orcioni,et al.  Low Power Fall Detection System , 2015 .

[21]  Jing Luo,et al.  Fall Monitoring Device for Old People based on Tri-Axial Accelerometer , 2015 .