A. H. Razak, A. Zayegh, R. K. Begg, and Y. Wahab, Foot Plantar Pressure Measurement System: A Review, Sensors, vol.18, issue.12, pp.9884-9912, 2012.
DOI : 10.1080/026404100402421

T. H. An, N. T. Hai, T. Q. Phuc, and T. T. Mai, Support vector machine algorithm for human fall recognition kinect-based skeletal data, 2015 2nd National Foundation for Science and Technology Development Conference on Information and Computer Science (NICS), pp.202-207, 2015.
DOI : 10.1109/NICS.2015.7302191

B. Auvinet, G. Berrut, C. Touzard, N. Collet, D. Chaleil et al., Gait Abnormalities in Elderly Fallers, Journal of Aging and Physical Activity, vol.11, issue.1, pp.40-52, 2003.
DOI : 10.1123/japa.11.1.40

E. Auvinet, F. Multon, A. Saint-arnaud, J. Rousseau, and J. Meunier, Fall Detection With Multiple Cameras: An Occlusion-Resistant Method Based on 3-D Silhouette Vertical Distribution, IEEE Transactions on Information Technology in Biomedicine, vol.15, issue.2, pp.290-300, 2011.
DOI : 10.1109/TITB.2010.2087385

URL : https://hal.archives-ouvertes.fr/hal-00640199

S. J. Bamberg, A. Y. Benbasat, D. M. Scarborough, D. E. Krebs, and J. A. Paradiso, Gait Analysis Using a Shoe-Integrated Wireless Sensor System, IEEE Transactions on Information Technology in Biomedicine, vol.12, issue.4, pp.413-423, 2008.
DOI : 10.1109/TITB.2007.899493

A. Bourke, J. O-'brien, and G. Lyons, Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm, Gait & Posture, vol.26, issue.2, pp.194-199, 2007.
DOI : 10.1016/j.gaitpost.2006.09.012

K. E. Caine, W. A. Rogers, and A. D. Fisk, Privacy perceptions of an aware home with visual sensing devices, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, pp.1856-1858, 2005.

R. Camicioli, D. Howieson, B. Oken, G. Sexton, and J. Kaye, Motor slowing precedes cognitive impairment in the oldest old, Neurology, vol.50, issue.5, pp.1496-1498, 1998.
DOI : 10.1212/WNL.50.5.1496

G. Demiris, D. P. Oliver, J. Giger, M. Skubic, and M. Rantz, Older adults' privacy considerations for vision based recognition methods of eldercare applications, Technology and Health Care, vol.17, issue.1, pp.41-48, 2009.

A. Dubois and F. Charpillet, Human activities recognition with RGB-Depth camera using HMM, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp.4666-4669, 2013.
DOI : 10.1109/EMBC.2013.6610588

URL : https://hal.archives-ouvertes.fr/hal-00914319

A. Dubois and F. Charpillet, A gait analysis method based on a depth camera for fall prevention, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014.
DOI : 10.1109/EMBC.2014.6944627

URL : https://hal.archives-ouvertes.fr/hal-01069640

R. Guimaraes and B. Isaacs, Characteristics of the gait in old people who fall, International Rehabilitation Medicine, vol.75, issue.4, pp.177-180, 1980.
DOI : 10.1093/geronj/24.2.169

S. Hagler, D. Austin, T. L. Hayes, J. Kaye, and M. Pavel, Unobtrusive and Ubiquitous In-Home Monitoring: A Methodology for Continuous Assessment of Gait Velocity in Elders, IEEE Transactions on Biomedical Engineering, vol.57, issue.4, pp.813-820, 2010.
DOI : 10.1109/TBME.2009.2036732

J. M. Hausdorff, D. A. Rios, and H. K. Edelberg, Gait variability and fall risk in community-living older adults: A 1-year prospective study. Archives of physical medicine and rehabilitation, pp.1050-1056, 2001.

R. Igual, C. Medrano, and I. Plaza, Challenges, issues and trends in fall detection systems, BioMedical Engineering OnLine, vol.12, issue.1, pp.12-2013
DOI : doi:10.1109/ISWC.2003.1241410

B. Jansen, F. Temmermans, and R. Deklerck, 3D human pose recognition for home monitoring of elderly, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.4049-4051, 2007.
DOI : 10.1109/IEMBS.2007.4353222

P. Leusmann, C. Möllering, L. Klack, K. Kasugai, M. Ziefle et al., Your Floor Knows Where You Are: Sensing and Acquisition of Movement Data, 2011 IEEE 12th International Conference on Mobile Data Management, pp.61-66, 2011.
DOI : 10.1109/MDM.2011.29

P. Lopez-meyer, G. D. Fulk, and E. S. Sazonov, Automatic Detection of Temporal Gait Parameters in Poststroke Individuals, IEEE Transactions on Information Technology in Biomedicine, vol.15, issue.4, pp.594-601, 2011.
DOI : 10.1109/TITB.2011.2112773

A. S. Melenhorst, A. D. Fisk, E. D. Mynatt, and W. A. Rogers, Potential intrusiveness of aware home technology: Perceptions of older adults, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, pp.266-270, 2004.

M. Mubashir, L. Shao, and L. Seed, A survey on fall detection: Principles and approaches, Neurocomputing, vol.100, pp.144-152, 2013.
DOI : 10.1016/j.neucom.2011.09.037

A. Muro-de-la-herran, B. Garcia-zapirain, and A. Mendez-zorrilla, Gait Analysis Methods: An Overview of Wearable and Non-Wearable Systems, Highlighting Clinical Applications, Sensors, vol.107, issue.2, pp.3362-3394, 2014.
DOI : 10.1016/S0735-1097(12)61915-9

L. Rabiner, A tutorial on hidden Markov models and selected applications in speech recognition, Proceedings of the IEEE, pp.257-286, 1989.

H. Rimminen, J. Lindström, M. Linnavuo, and R. Sepponen, Detection of falls among the elderly by a floor sensor using the electric near field, IEEE Transactions on Information Technology in Biomedicine, vol.14, issue.6, pp.1475-1476, 2010.
DOI : 10.1109/TITB.2010.2051956

M. Saunders, V. T. Inman, and H. D. Eberhart, THE MAJOR DETERMINANTS IN NORMAL AND PATHOLOGICAL GAIT, The Journal of Bone & Joint Surgery, vol.35, issue.3, pp.543-558, 1953.
DOI : 10.2106/00004623-195335030-00003

E. Stone and M. Skubic, Fall Detection in Homes of Older Adults Using the Microsoft Kinect, IEEE Journal of Biomedical and Health Informatics, vol.19, issue.1, pp.290-301, 2015.
DOI : 10.1109/JBHI.2014.2312180

E. E. Stone and M. Skubic, Unobtrusive, Continuous, In-Home Gait Measurement Using the Microsoft Kinect, IEEE Transactions on Biomedical Engineering, vol.60, issue.10, pp.2925-2932, 2013.
DOI : 10.1109/TBME.2013.2266341

S. Studenski, S. Perera, D. Wallace, J. M. Chandler, P. W. Duncan et al., Physical Performance Measures in the Clinical Setting, Journal of the American Geriatrics Society, vol.56, issue.3, pp.314-322, 2003.
DOI : 10.1093/gerona/56.4.M217

R. Takeda, S. Tadano, A. Natorigawa, M. Todoh, and S. Yoshinari, Gait posture estimation using wearable acceleration and gyro sensors, Journal of Biomechanics, vol.42, issue.15, pp.2486-2494, 2009.
DOI : 10.1016/j.jbiomech.2009.07.016

W. Tao, T. Liu, R. Zheng, and H. Feng, Gait Analysis Using Wearable Sensors, Sensors, vol.28, issue.12, pp.2255-2283, 2012.
DOI : 10.1016/j.gaitpost.2008.01.003

L. Waite, D. Grayson, O. Piguet, H. Creasey, H. Bennett et al., Gait slowing as a predictor of incident dementia: 6-year longitudinal data from the Sydney Older Persons Study, Journal of the Neurological Sciences, vol.229, issue.230, pp.89-93, 2005.
DOI : 10.1016/j.jns.2004.11.009

E. Wentink, V. Schut, E. Prinsen, J. Rietman, and P. Veltink, Detection of the onset of gait initiation using kinematic sensors and EMG in transfemoral amputees, Gait & Posture, vol.39, issue.1, pp.391-396, 2014.
DOI : 10.1016/j.gaitpost.2013.08.008

G. Wu, Distinguishing fall activities from normal activities by velocity characteristics, Journal of Biomechanics, vol.33, issue.11, pp.1497-1500, 2000.
DOI : 10.1016/S0021-9290(00)00117-2