Information Technology Reference
In-Depth Information
References
R.F. Allen, E. Ambikairajah, N.H. Lovell, B.G. Celler, Classification of a known sequence of
motions and postures from accelerometry data using adapted gaussian mixture models. Physiol.
Meas. 27 , 935 (2006)
K. Altun, B. Barshan, in Human activity recognition using inertial/magnetic sensor units ,Human
Behavior Understanding, 2010
O. Amft, C. Lombriser, T. Stiefmeier, G. Tröster, in Recognition of user activity sequences using
distributed event detection , European Conference on Smart Sensing and Context, 2007
L. Atallah, B. Lo, R. King, G.-Z. Yang, in Sensor placement for activity detection using wearable
accelerometers , International Conference on Body Sensor Networks, 2010
A. Avci, S. Bosch, M. Marin-Perianu, R. Marin-Perianu, P. Havinga, in Activity recognition using
inertial sensing for healthcare, wellbeing and sports applications: a survey , International Con-
ference on Architecture of Computing Systems, 2010
M. Bachlin, M. Plotnik, D. Roggen, I. Maidan, J.M. Hausdorff, N. Giladi, G. Troster, Wearable
assistant for parkinson's disease patients with the freezing of gait symptom. IEEE Trans. Inf.
Technol. Biomed. 14 , 436-446 (2010)
G. Bahle, P. Lukowicz, K. Kunze, K. Kise, in I see you: how to improve wearable activity recogni-
tion by leveraging information from environmental cameras , IEEE International Conference on
Pervasive Computing and Communications Workshops, 2013
L. Bao, S.S. Intille, in Activity recognition from user-annotated acceleration data . Pervasive Com-
put. (2004)
M. Berchtold, M. Budde, D. Gordon, H.R. Schmidtke, M. Beigl, in Activity recognition service for
mobile phones , International Symposium on Wearable Computers, 2010
C.M. Bishop, Pattern Recognition and Machine Learning (Springer, New York, 2006)
T. Brezmes, J.L. Gorricho, J. Cotrina, in Activity recognition from accelerometer data on a mobile
phone , Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and
Ambient Assisted Living, 2009
B. Bruno, F. Mastrogiovanni, A. Sgorbissa, T. Vernazza, R. Zaccaria, in Analysis of human behavior
recognition algorithms based on acceleration data , IEEE International Conference on Robotics
and Automation, 2013
B. Bruno, F. Mastrogiovanni, A. Sgorbissa, T. Vernazza, R. Zaccaria, in Human motion modelling
and recognition: a computational approach , IEEE International Conference on Automation Sci-
ence and Engineering, 2012
C. Cedras, M. Shah, Motion-based recognition a survey. Image Vis. Comput. 13 , 129-155 (1995)
C.-C. Chang, C.-J. Lin, LIBSVM: A library for support vector machines. ACM Trans. Intell. Syst.
Technol. 2 , 27-54 (2011)
L. Chen, C.D. Nugent, H. Wang, A knowledge-driven approach to activity recognition in smart
homes. IEEE Trans. Knowl. Data Eng. 24, 961-974 (2012a).
L. Chen, J. Hoey, C.D. Nugent, D.J. Cook, Z. Yu, Sensor-based activity recognition. IEEE Trans.
Syst. Man Cybern. B Cybern. Part C: Appl. Rev. 42 , 790-808 (2012b).
T. Choudhury, S. Consolvo, B. Harrison, J. Hightower, A. LaMarca, L. Legrand, A. Rahimi, A.
Rea, G. Bordello, B. Hemingway, P. Klasnja, K. Koscher, J.A. Landay, J. Lester, D. Wyatt, D.
Haehnel, The mobile sensing platform: an embedded activity recognition system. IEEE Pervasive
Comput. 7 , 32-41 (2008)
B. Coley, B. Najafi, A. Paraschiv-Ionescu, K. Aminian, Stair climbing detection during daily phys-
ical activity using a miniature gyroscope. Gait Posture 22 , 287-294 (2005)
J.D. Cook, S.K. Das, How smart are our environments? an updated look at the state of the art.
Pervasive Mob. Comput. 3 , 53-73 (2007)
D.J. Cook, S.K. Das, Pervasive computing at scale: transforming the state of the art. Pervasive Mob.
Comput. 8 , 22-35 (2012)
 
Search WWH ::




Custom Search