A fall detection study on the sensors placement location and a rule-based multi-thresholds algorithm using both accelerometer and gyroscopes

Falls are dangerous among the elderly population and are a major health concern. Many investigators have reported the use of accelerometers for fall detection. In addition, the use of miniature gyroscopes has also been reported to be able to detect falls, but the effects of sensor placement on the back of a person have not been studied thoroughly. In this paper we present a simple solution for effective fall detection using both an accelerometer and two gyroscopes placed, as a single unit, on three different positions along the thoracic vertebrae (i.e., T-4, T-7, and T-10). Results indicated that T-10 was not a good location for the gyroscope placement for fall detection. However, both T-4 and T-7 were suitable, with the results for T-4 being slightly better. Using a simple rule-based multi-thresholds algorithm that utilizes the recorded resultant gravitational acceleration, angular change, angular velocity, and angular acceleration, we were able to successfully detect all 60 falls and differentiate between falls and activities of daily living (ADL) with no false positives on young volunteers. More testing data is needed, especially for backward falls, to test the robustness of our simple algorithm and to improve the sensor portability for future trial studies on geriatric populations.

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

[2]  Ernesto Damiani,et al.  A reputation-based approach for choosing reliable resources in peer-to-peer networks , 2002, CCS '02.

[3]  Giorgos Zacharia,et al.  Trust management through reputation mechanisms , 2000, Appl. Artif. Intell..

[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]  Paolo Traverso,et al.  Service-Oriented Computing: a Research Roadmap , 2008, Int. J. Cooperative Inf. Syst..

[6]  Vijay Varadharajan,et al.  Trust management towards service-oriented applications , 2008, Service Oriented Computing and Applications.

[7]  Lei Li,et al.  Trust-Oriented Composite Service Selection and Discovery , 2009, ICSOC/ServiceWave.

[8]  Brian Livesley,et al.  Home and leisure accident research: A review of research on falls among elderly people. Janet Askham, Edward Glucksman, Patricia Owen et al. Consumer Safety Unit, Department of Trade and Industry, London, 1990. No. of pages: ii + 83 , 1991 .

[9]  Hector Garcia-Molina,et al.  The Eigentrust algorithm for reputation management in P2P networks , 2003, WWW '03.

[10]  Wolfgang Näther Regression with fuzzy random data , 2006, Comput. Stat. Data Anal..

[11]  Dug Hun Hong,et al.  Support vector fuzzy regression machines , 2003, Fuzzy Sets Syst..

[12]  Witold Pedrycz,et al.  A Tabu–Harmony Search-Based Approach to Fuzzy Linear Regression , 2011, IEEE Transactions on Fuzzy Systems.

[13]  Rafik A. Aliev,et al.  Genetic algorithms-based fuzzy regression analysis , 2002, Soft Comput..

[14]  R. Baumgartner,et al.  Fear of falling and restriction of mobility in elderly fallers. , 1997, Age and ageing.

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

[16]  William H. Woodall,et al.  Further examination of fuzzy linear regression , 1996, Fuzzy Sets Syst..

[17]  G. Wu,et al.  Distinguishing fall activities from normal activities by velocity characteristics. , 2000, Journal of biomechanics.

[18]  Ling Liu,et al.  PeerTrust: supporting reputation-based trust for peer-to-peer electronic communities , 2004, IEEE Transactions on Knowledge and Data Engineering.

[19]  Phil Diamond,et al.  Fuzzy least squares , 1988, Inf. Sci..

[20]  Lei Li,et al.  Subjective Trust Inference in Composite Services , 2010, AAAI.

[21]  Andrzej Bargiela,et al.  Multiple regression with fuzzy data , 2007, Fuzzy Sets Syst..

[22]  Vijay Varadharajan,et al.  Fuzzy Regression Based Trust Prediction in Service-Oriented Applications , 2009, ATC.

[23]  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.

[24]  Karl Aberer,et al.  QoS-Based Service Selection and Ranking with Trust and Reputation Management , 2005, OTM Conferences.

[25]  Lei Li,et al.  Trust Evaluation in Composite Services Selection and Discovery , 2009, 2009 IEEE International Conference on Services Computing.

[26]  Manas Ranjan Patra,et al.  Web-services classification using intelligent techniques , 2010, Expert Syst. Appl..

[27]  Ram R. Bishu,et al.  Evaluation of fuzzy linear regression models by comparing membership functions , 1998, Fuzzy Sets Syst..

[28]  Eyhab Al-Masri,et al.  Discovering the best web service , 2007, WWW '07.

[29]  Audun Jøsang,et al.  A survey of trust and reputation systems for online service provision , 2007, Decis. Support Syst..

[30]  Eyhab Al-Masri,et al.  Investigating web services on the world wide web , 2008, WWW.

[31]  Eyhab Al-Masri,et al.  Discovering the best web service: A neural network-based solution , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[32]  Patrick Boissy,et al.  A smart sensor based on rules and its evaluation in daily routines , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[33]  Ruili Wang,et al.  An enhanced fuzzy linear regression model with more flexible spreads , 2009, Fuzzy Sets Syst..

[34]  M. Tinetti,et al.  Risk factors for falls among elderly persons living in the community. , 1988, The New England journal of medicine.

[35]  Kamiar Aminian,et al.  Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly , 2003, IEEE Transactions on Biomedical Engineering.

[36]  Chiang Kao,et al.  Least-squares estimates in fuzzy regression analysis , 2003, Eur. J. Oper. Res..

[37]  Lei Li,et al.  Trust-Oriented Composite Service Selection with QoS Constraints , 2010, J. Univers. Comput. Sci..

[38]  Yan Wang,et al.  The Evaluation of Situational Transaction Trust in E-Service Environments , 2008, 2008 IEEE International Conference on e-Business Engineering.