Benish Fida, Ivan Bernabucci, Daniele Bibbo, Silvia Conforto, Antonino Proto, Maurizio Schmid

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  1. [1] S.J. Preece, J.Y. Goulermas, L. P J; Kenney & D. Howard, A Comparison of Feature Extraction Methods for the Classification of dynamic Activities From Accelerometer Data, IEEE Transactions on Biomedical Engineering, 56(3), 2009, 871879.
  2. [2] H. Dejnabadi, B.M. Jolles, & K. Aminian, A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes, IEEE Trans. Biomed. Eng., vol.52, 2005, 1478-1484.
  3. [3] D. Karantonis, M. Narayanan , M. Mathie , N. Lovell & B. Celler, Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring, IEEE Trans. Inf. Technol. Biomed., 10(1), 2006, 156 -167.
  4. [4] A.K. Bourke, P. van de Ven, M. Gamble, R. O'Connor, K. Murphy & E. Bogan, Assessment of waist-worn tri-axial accelerometer based fall-detection algorithms using continuous unsupervised activities, Proc. IEEE EMBS, 2010, 2782–2785.
  5. [5] L. Tong, Q. Song, Y. Ge & M. Liu, HMM-Based Human Fall Detection and Prediction Method Using Tri-Axial Accelerometer, IEEE J. Sensors, 13(5), 2013, 1849-1856.
  6. [6] H. Gjoreski, M. Lustrek & M. Gams, Accelerometer Placement for Posture Recognition and Fall Detection, 7th International Conference on Intelligent Environments (IE), 2011, 47-54.
  7. [7] N. Ravi, N. Dandekar, P. Mysore, & M. L. Littman, Activity recognition from accelerometer data, In Proceedings of the 17th conference on Innovative applications of artificial intelligence, Vol. 3. , 2005, 1541-1546.
  8. [8] A.M. Khan, Young-Koo Lee; S.Y. Lee & Tae-Seong Kim, A Triaxial Accelerometer-Based Physical-Activity Recognition via Augmented-Signal Features and a Hierarchical Recognizer, IEEE Transactions on Information Technology in Biomedicine, 14(5), 2010, 1166-1172.
  9. [9] A. Dalton & G. OLaighin, Comparing Supervised Learning Techniques on the Task of Physical Activity Recognition, IEEE Journal of Biomedical and Health Informatics, 17(1), 2013, 4652.
  10. [10] D. Rodriguez-Martin, A. Samà, C. Perez-Lopez, A. Català, J. Cabestany & A. Rodriguez-Molinero, SVM-based posture identification with a single waist-located triaxial accelerometer, Expert Systems with Applications, 40(18), 2013, 7203-7211.
  11. [11] H.-Y. Lau, K.-Y. Tong & H. Zhu. Support vector machine for classification of walking conditions using miniature kinematic sensors, Medical and Biological Engineering and Computing, 46(2), 2008, 563–573.
  12. [12] R. Muscillo, M. Schmid, S. Conforto, & T. D'Alessio, An adaptive Kalman-based Bayes estimation technique to classify locomotor activities in young and elderly adults through accelerometers, Medical Engineering and Physics,32(8), 2010, 849–859.
  13. [13] R. Muscillo, S. Conforto, M. Schmid, P. Caselli & T. D'Alessio, Classification of Motor Activities through Derivative Dynamic Time Warping applied on Accelerometer Data, Proceedings of the 29th IEEE-EMBS Conference, Lyon, France, 2007, 23-26.
  14. [14] R. Muscillo, M. Schmid, S. Conforto & T. D'Alessio, Early recognition of upper limb motor tasks through accelerometers: real-time implementation of a DTW-based algorithm, Computers in Biology and Medicine, 41(3), 2011, 164-172.
  15. [15] I. Cleland, B. Kikhia, C. Nugent, A. Boytsov, J. Hallberg, K. Synnes, S. McClean & D. Finlay, Optimal Placement of Accelerometers for the Detection of Everyday Activities, Sensors, 13, 2013, 9183-9200. 126
  16. [16] L. Bao & S. S. Intille, Activity recognition from userannotated acceleration data, Proceedings of PERVASIVE, 2004, 1-17.
  17. [17] A. Mannini & A. M. Sabatini, Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers, Sensors, 10(2), 2010, 1154-1175.
  18. [18] Y.-J. Hong, I.-J Kim, S. C. Ahn & H.-G. Kim, Mobile health monitoring system based on activity recognition using accelerometer, Simulation Modelling Practice and Theory, 18(4), 2010, 446-455.
  19. [19] F. Ioana-Iuliana, & D. Rodica-Elena, Detection of daily movements from data collected with two tri-axial accelerometers, 34th International Conference on Telecommunications and Signal Processing (TSP), 2011, 376380.
  20. [20] O. Banos, M. Damas, H. Pomares, A. Prieto & I. Rojas, Daily living activity recognition based on statistical feature quality group selection, Expert Systems with Applications, vol.39(9), 2012, 8013-8021.
  21. [21] L. Atallah, B. Lo, R. King & G.-Z. Yang, Sensor Placement for Activity Detection Using Wearable Accelerometers, Proc. Int. Workshop Wearable Implantable Body Sens. Netw., 2010, 24 -29.
  22. [22] J. Baek, G. Lee, W. Park & B.-J. Yun, Accelerometer Signal Processing for User Activity Detection, KES, 2004, 610617.
  23. [23] H. Chan, M. Yang, H. Wang, H. Zheng, S. I. McClean, R. Sterritt & R. E. Mayagoitia, Assessing Gait Patterns of Healthy Adults Climbing Stairs Employing Machine Learning Techniques, Int. J. Intell. Syst. 28(3), 2013, 257-270.
  24. [24] B. Najafi, K. Aminian, A. Paraschiv-Ionescu, F. Loew, C.J. Bula & P. Robert, Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly, IEEE Transactions on Biomedical Engineering, 50(6), 2003, 711-723.
  25. [25] M. Mathie, B. Celler, N. Lovell & A. Coster, 'Classification of basic daily movements using a triaxial accelerometer, Med. Biol. Eng. Comput., 42, 2004, 670 -687.
  26. [26] N. Wang, E. Ambikairajah, N.H. Lovell, and B.G. Celler, Accelerometry Based Classification of Walking Patterns Using Time-frequency Analysis, Proc. 29th Annu. Conf. IEEE Eng. Med. Biol. Soc., Lyon, France, 2007, 4899 -4902.
  27. [27] M. Schmid, F. Riganti-Fulginei, I. Bernabucci, A. Laudani, D. Bibbo, R. Muscillo, A. Salvini & S. Conforto, SVM versus MAP on accelerometer data to distinguish among locomotor activities executed at different speeds, Computational and Mathematical Methods in Medicine, 2013: Article ID 343084, 2013.
  28. [28] L. Tong; Q. Song; Y. Ge & M. Liu, HMM-Based Human Fall Detection and Prediction Method Using Tri-Axial Accelerometer, IEEE J. Sensors, 13(5), 2013, 1849,1856.
  29. [29] M.-W. Lee, A. M. Khan & T.-S Kim, A single tri-axial accelerometer-based real-time personal life log system capable of human activity recognition and exercise information generation, Personal Ubiquitous Comput., 15, 2011, 887 -898.
  30. [30] M.N. Nayan, F.E. Tay, K.H. Seah, & Y.Y. Sitoh, Classification of gait patterns in the time frequency domain, J. Biomech., 39, 2006, 2647-2656.
  31. [31] R. Herren, A. Sparti, K. Aminian & Y. Schutz, The prediction of speed and incline in outdoor running in humans using accelerometry, Medicine & Science in Sports & Exercise, 31(7), 1999, 1053–1059.

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