-
1
-
-
61849162485
-
-
Technical report. Accessed 2013 June 13
-
World Health Organization (2007) WHO global report on falls prevention in older age. Technical report. http://www.who.int/ageing/publications/ Fallsprevention7March.pdf Accessed 2013 June 13.
-
(2007)
WHO Global Report on Falls Prevention in Older Age
-
-
-
2
-
-
57649219452
-
Fall detection - principles and methods
-
Noury N, Fleury A, Rumeau P, Bourke A, Laighin G, et al. (2007) Fall detection - principles and methods. In: Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE. pp. 1663-1666.
-
(2007)
Engineering in Medicine and Biology Society, 2007 EMBS 2007 29th Annual International Conference of the IEEE
, pp. 1663-1666
-
-
Noury, N.1
Fleury, A.2
Rumeau, P.3
Bourke, A.4
Laighin, G.5
-
3
-
-
84868627131
-
A survey on fall detection: Principles and approaches
-
Mubashir M, Shao L, Seed L (2013) A survey on fall detection: Principles and approaches. Neurocomputing 100: 144-152.
-
(2013)
Neurocomputing
, vol.100
, pp. 144-152
-
-
Mubashir, M.1
Shao, L.2
Seed, L.3
-
5
-
-
29244476234
-
Evaluation of a fall detector based on accelerometers: A pilot study
-
DOI 10.1007/BF02351026
-
Lindemann U, Hock A, Stuber M, Keck W, Becker C (2005) Evaluation of a fall detector based on accelerometers: A pilot study. Medical and Biological Engineering and Computing 43: 548-551. (Pubitemid 41824338)
-
(2005)
Medical and Biological Engineering and Computing
, vol.43
, Issue.5
, pp. 548-551
-
-
Lindemann, U.1
Hock, A.2
Stuber, M.3
Keck, W.4
Becker, C.5
-
6
-
-
34249934082
-
Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm
-
DOI 10.1016/j.gaitpost.2006.09.012, PII S0966636206001895
-
Bourke A, OBrien J, Lyons G (2007) Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. Gait & Posture 26: 194-199. (Pubitemid 46880343)
-
(2007)
Gait and Posture
, vol.26
, Issue.2
, pp. 194-199
-
-
Bourke, A.K.1
O'Brien, J.V.2
Lyons, G.M.3
-
7
-
-
46149107931
-
Comparison of low-complexity fall detection algorithms for body attached accelerometers
-
DOI 10.1016/j.gaitpost.2008.01.003, PII S096663620800026X
-
Kangas M, Konttila A, Lindgren P, Winblad I, Jamsa T (2008) Comparison of low-complexity fall detection algorithms for body attached accelerometers. Gait & Posture 28: 285-291. (Pubitemid 351902256)
-
(2008)
Gait and Posture
, vol.28
, Issue.2
, pp. 285-291
-
-
Kangas, M.1
Konttila, A.2
Lindgren, P.3
Winblad, I.4
Jamsa, T.5
-
8
-
-
63249132839
-
Sensitivity and specificity of fall detection in people aged 40 years and over
-
Kangas M, Vikman I, Wiklander J, Lindgren P, Nyberg L, et al. (2009) Sensitivity and specificity of fall detection in people aged 40 years and over. Gait & Posture 29: 571-574.
-
(2009)
Gait & Posture
, vol.29
, pp. 571-574
-
-
Kangas, M.1
Vikman, I.2
Wiklander, J.3
Lindgren, P.4
Nyberg, L.5
-
9
-
-
78650821682
-
Assessment of waist-worn tri-axial accelerometer based fall-detection algorithms using continuous unsupervised activities
-
Bourke A, vandeVen P, Gamble M, O'Connor R, Murphy K, et al. (2010) Assessment of waist-worn tri-axial accelerometer based fall-detection algorithms using continuous unsupervised activities. In: Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. pp. 2782-2785.
-
(2010)
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
, pp. 2782-2785
-
-
Bourke, A.1
Van De Ven, P.2
Gamble, M.3
O'Connor, R.4
Murphy, K.5
-
10
-
-
84856852493
-
Unsupervised machine-learning method for improving the performance of ambulatory falldetection systems
-
Yuwono M, Moulton B, Su S, Celler B, Nguyen H (2012) Unsupervised machine-learning method for improving the performance of ambulatory falldetection systems. BioMedical Engineering OnLine 11: 9.
-
(2012)
BioMedical Engineering OnLine
, vol.11
, pp. 9
-
-
Yuwono, M.1
Moulton, B.2
Su, S.3
Celler, B.4
Nguyen, H.5
-
11
-
-
77950973128
-
Ifall: An android application for fall monitoring and response
-
EMBC 2009. Annual International Conference of the IEEE
-
Sposaro F, Tyson G (2009) ifall: An android application for fall monitoring and response. In: Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE. pp. 6119-6122.
-
(2009)
Engineering in Medicine and Biology Society, 2009
, pp. 6119-6122
-
-
Sposaro, F.1
Tyson, G.2
-
12
-
-
77957018908
-
Mobile phone-based pervasive fall detection
-
Dai J, Bai X, Yang Z, Shen Z, Xuan D (2010) Mobile phone-based pervasive fall detection. Personal Ubiquitous Comput 14: 633-643.
-
(2010)
Personal Ubiquitous Comput
, vol.14
, pp. 633-643
-
-
Dai, J.1
Bai, X.2
Yang, Z.3
Shen, Z.4
Xuan, D.5
-
13
-
-
80054919440
-
Detection of falls using accelerometers and mobile phone technology
-
Carlisle AJ, Lee RYW (2011) Detection of falls using accelerometers and mobile phone technology. Age and ageing 40: 690-696.
-
(2011)
Age and Ageing
, vol.40
, pp. 690-696
-
-
Carlisle, A.J.1
Lee, R.Y.W.2
-
15
-
-
84860498453
-
Developing a mobile phone-based fall detection system on android platform
-
Fang SH, Liang YC, Chiu KM (2012) Developing a mobile phone-based fall detection system on android platform. In: Computing, Communications and Applications Conference (ComComAp), 2012. pp. 143-146.
-
(2012)
Computing, Communications and Applications Conference (ComComAp), 2012
, pp. 143-146
-
-
Fang, S.H.1
Liang, Y.C.2
Chiu, K.M.3
-
16
-
-
84869122881
-
A smartphone-based fall detection system
-
Abbate S, Avvenuti M, Bonatesta F, Cola G, Corsini P, et al. (2012) A smartphone-based fall detection system. Pervasive and Mobile Computing 8: 883-899.
-
(2012)
Pervasive and Mobile Computing
, vol.8
, pp. 883-899
-
-
Abbate, S.1
Avvenuti, M.2
Bonatesta, F.3
Cola, G.4
Corsini, P.5
-
18
-
-
84882939566
-
Guidelines to design smartphone applications for people with intellectual disability: A practical experience
-
Igual R, Plaza I, Martin L, Corbalan M, Medrano C (2013) Guidelines to design smartphone applications for people with intellectual disability: A practical experience. In: Ambient Intelligence - Software and Applications, Springer International Publishing, volume 219 of Advances in Intelligent Systems and Computing. pp. 65-69.
-
(2013)
Ambient Intelligence - Software and Applications, Springer International Publishing, Volume 219 of Advances in Intelligent Systems and Computing
, pp. 65-69
-
-
Igual, R.1
Plaza, I.2
Martin, L.3
Corbalan, M.4
Medrano, C.5
-
19
-
-
84870334401
-
Smartphone-based solutions for fall detection and prevention: The FARSEEING approach
-
Mellone S, Tacconi C, Schwickert L, Klenk J, Becker C, et al. (2012) Smartphone-based solutions for fall detection and prevention: The FARSEEING approach. Z Gerontol Geriatr 45: 722-727.
-
(2012)
Z Gerontol Geriatr
, vol.45
, pp. 722-727
-
-
Mellone, S.1
Tacconi, C.2
Schwickert, L.3
Klenk, J.4
Becker, C.5
-
20
-
-
84888363784
-
Development of a standard fall data format for signals from body-worn sensors: The FARSEEING consensus
-
Klenk J, Chiari L, Helbostad JL, Zijlstra W, Aminian K, et al. (2013) Development of a standard fall data format for signals from body-worn sensors: The FARSEEING consensus. Z Gerontol Geriatr 46: 720-726.
-
(2013)
Z Gerontol Geriatr
, vol.46
, pp. 720-726
-
-
Klenk, J.1
Chiari, L.2
Helbostad, J.L.3
Zijlstra, W.4
Aminian, K.5
-
21
-
-
84861214566
-
Evaluation of accelerometer-based fall detection algorithms on real-world falls
-
Bagala F, Becker C, Cappello A, Chiari L, Aminian K, et al. (2012) Evaluation of accelerometer-based fall detection algorithms on real-world falls. PLoS ONE 7: e37062.
-
(2012)
PLoS ONE
, vol.7
-
-
Bagala, F.1
Becker, C.2
Cappello, A.3
Chiari, L.4
Aminian, K.5
-
23
-
-
77951003210
-
Acoustic fall detection using one-class classifiers
-
EMBC 2009. Annual International Conference of the IEEE
-
Popescu M, Mahnot A (2009) Acoustic fall detection using one-class classifiers. In: Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE. pp. 3505-3508.
-
(2009)
Engineering in Medicine and Biology Society, 2009
, pp. 3505-3508
-
-
Popescu, M.1
Mahnot, A.2
-
24
-
-
61549108880
-
A proposal for the classification and evaluation of fall detectors
-
Noury N, Rumeau P, Bourke AK, OLaighin G, Lundy JE (2008) A proposal for the classification and evaluation of fall detectors. IRBM 29: 340-349.
-
(2008)
IRBM
, vol.29
, pp. 340-349
-
-
Noury, N.1
Rumeau, P.2
Bourke, A.K.3
Olaighin, G.4
Lundy, J.E.5
-
25
-
-
0345019840
-
Common protective movements govern unexpected falls from standing height
-
DOI 10.1016/S0021-9290(97)00114-0, PII S0021929097001140
-
Hsiao ET, Robinovitch SN (1998) Common protective movements govern unexpected falls from standing height. Journal of Biomechanics 31: 1-9. (Pubitemid 28192644)
-
(1998)
Journal of Biomechanics
, vol.31
, Issue.1
, pp. 1-9
-
-
Hsiao, E.T.1
Robinovitch, S.N.2
-
26
-
-
84857993513
-
Comparison of real-life accidental falls in older people with experimental falls in middle-aged test subjects
-
Kangas M, Vikman I, Nyberg L, Korpelainen R, Lindblom J, et al. (2012) Comparison of real-life accidental falls in older people with experimental falls in middle-aged test subjects. Gait & Posture 35: 500-505.
-
(2012)
Gait & Posture
, vol.35
, pp. 500-505
-
-
Kangas, M.1
Vikman, I.2
Nyberg, L.3
Korpelainen, R.4
Lindblom, J.5
-
27
-
-
79952317138
-
Comparison of acceleration signals of simulated and real-world backward falls
-
Klenk J, Becker C, Lieken F, Nicolai S, Maetzler W, et al. (2011) Comparison of acceleration signals of simulated and real-world backward falls. Medical Engineering & Physics 33: 368-373.
-
(2011)
Medical Engineering & Physics
, vol.33
, pp. 368-373
-
-
Klenk, J.1
Becker, C.2
Lieken, F.3
Nicolai, S.4
Maetzler, W.5
-
28
-
-
80555140075
-
Scikit-learn: Machine learning in Python
-
Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, et al. (2011) Scikit-learn: Machine learning in Python. Journal of Machine Learning Research 12: 2825-2830.
-
(2011)
Journal of Machine Learning Research
, vol.12
, pp. 2825-2830
-
-
Pedregosa, F.1
Varoquaux, G.2
Gramfort, A.3
Michel, V.4
Thirion, B.5
|