Walid Bourennane, Fehd Bettahar, Eric Campo


  1. [1] K. Kinsella, & D.R. Phillips, Global Aging : Thechallenge of success, Population Bulletin, 60(1), 2005.
  2. [2] M. Chan, E. Campo, D. Estève, & J.Y. Fourniols,Smart homes — Current features and future perspectives,Maturitas, 64(2), 2009, 90-97.
  3. [3] Institut national de la statistique et des étudeséconomiques. [Online]. Available:
  4. [4] J.D. Price, D. Hermans, & J. Grimley Evans,Subjective barriers to prevent wandering of cognitivelyimpaired people, Cochrane Dementia and CognitiveImprovement Group, 2009.
  5. [5] V. Faucounau, M. Riguet, G. Orvoen, A.Lacombe, V. Rialle, J. Extra, & A.S. Rigaud, Electronictracking system and wandering in Alzheimer’s disease: Acase study, Annals of Physical and RehabilitationMedicine, 52(7-8), 2009, 579-587.
  6. [6] M. Laila, V. Rialle, C. Brissonneau, D.Princiaux, C. Secheresse, D. Boukhalfa, O. Magnillat, &A. Franco, Utility and feasibility of an electronic trackingsystem for prevention of wandering in demented elderlypatients, Proc. 6th Conf. of the International Society forGerontechnology, 7(2), 2008.
  7. [7] S. Matsuoka, H. Ogawa, H. Maki, Y. Yonezawa,& W.M. Caldwell, A new safety support system forwandering elderly persons, Proc. IEEE Conf. onSelf-adaptive areasProhibited areaPresence detection inthe prohibited area258Engineering in Medicine and Biology Society, Boston,MA, 2011, 5232-5235.
  8. [8] C.C. Lin, M.J. Chiu, C.C. Hsiao, R.G. Lee, &Y.S. Tsai, Wireless Health Care Service System forElderly With Dementia, IEEE Transactions onInformation Technology in Biomedicine, 10(4), 2006,696-704.
  9. [9] J. Sablier, V. Rialle, & B. Robert, Tracking ortalking? What do people with Alzheimer disease and theircaregivers expect from assistive technologies? Exampleof a GPS-based tracking system, Proc. 22nd AlzheimerEurope Conference « Changing perceptions, practice andpolicy », 2012.
  10. [10] Pole Star, Indoor positioning solution “NaoCampus” , Pole Star. [Online]. Available:
  11. [11] K. Fukunaga, & L. Hostetler, The estimation ofthe gradient of a density function, with applications inpattern recognition, IEEE Transactions on InformationTheory, 21(1), 1975, 32–40.
  12. [12] K.L. Wu, & M.S. Yang, Mean shift-basedclustering, Pattern Recognition, 40(11), 2007, 3035-3052.
  13. [13] Y. Cheng, Mean shift, mode seeking, andclustering , IEEE Transactions on Pattern Analysis andMachine Intelligence,17(8), 1995, 790–799.
  14. [14] D. Comaniciu, & P. Meer, Mean Shift: A robustapproach toward feature space analysis, IEEETransactions on Pattern Analysis and MachineIntelligence, 24(5), 2002, 603–619.
  15. [15] K.I. Kim, K. Jung, & J.H. Kim, Texture-basedapproach for text detection in images using support vectormachines and continuously adaptive mean shiftalgorithm , IEEE Transactions on Pattern Analysis andMachine Intelligence, 25(12), 2003, 1631–1639.
  16. [16] D. Comaniciu, V. Ramesh, & P. Meer, Kernel-based object tracking, IEEE Transactions on PatternAnalysis and Machine Intelligence, 25(5), 2003, 564–577.
  17. [17] H. Chen, & P. Meer, Robust Fusion of UncertainInformation, IEEE Transactions on Systems, Man andCybernetics, Part B (Cybernetics), 35(3), 2005, 578-586.

Important Links:

Go Back