(2007) Advances in Engineering Software, 38 (4), pp. 256-266. , DOI 10.1016/j.advengsoft.2006.08.014, PII S0965997806001402; http://www.mathworks.com/help/toolbox/dotnetbuilder/, MATLAB Builder NE [accessed 28.04.11]UR - 1272. Hariharan M, Fook CY, Sindhu R, Ilias B, Yaacob S. A comparative study of wavelet families for classification of wrist motions. Comput Electr Eng. 2012;38(6):1798-807. doi: 10.1016/j.compeleceng.2012.08.009. 1273. Heinrich C, Pennington RR, Kuiper R. Virtual Case Studies in the Classroom Improve Student Knowledge. Clinical Simulation in Nursing. 2012;8(8):e353-e61. doi: http://doi.org/10.1016/j.ecns.2011.02.002. 1274. Hock Ong ME, Lee Ng CH, Goh K, Liu N, Koh ZX, Shahidah N, et al. Prediction of cardiac arrest in critically ill patients presenting to the emergency department using a machine learning score incorporating heart rate variability compared with the modified early warning score. Crit Care. 2012;16(3). doi: 10.1186/cc11396. 1275. Hodge AB, Snyder AC, Fernandez AL, Boan AD, Malek AM, Sistino JJ. The effect of acute sleep deprivation and fatigue in cardiovascular perfusion students: A mixed methods study. J Extra-Corpor Technol. 2012;44(3):116-25. 1276. Hoover A, Singh A, Fishel-Brown S, Muth E. Real-time detection of workload changes using heart rate variability. Biomed Signal Process Control. 2012;7(4):333-41. doi: 10.1016/j.bspc.2011.07.004. 1277. Howitt P, Darzi A, Yang GZ, Ashrafian H, Atun R, Barlow J, et al. Technologies for global
(2007) Advances in Engineering Software, 38 (4), pp. 256-266. , DOI 10.1016/j.advengsoft.2006.08.014, PII S0965997806001402; http://www.mathworks.com/help/toolbox/dotnetbuilder/, MATLAB Builder NE [accessed 28.04.11]UR - 1272. Hariharan M, Fook CY, Sindhu R, Ilias B, Yaacob S. A comparative study of wavelet families for classification of wrist motions. Comput Electr Eng. 2012;38(6):1798-807. doi: 10.1016/j.compeleceng.2012.08.009. 1273. Heinrich C, Pennington RR, Kuiper R. Virtual Case Studies in the Classroom Improve Student Knowledge. Clinical Simulation in Nursing. 2012;8(8):e353-e61. doi: http://doi.org/10.1016/j.ecns.2011.02.002. 1274. Hock Ong ME, Lee Ng CH, Goh K, Liu N, Koh ZX, Shahidah N, et al. Prediction of cardiac arrest in critically ill patients presenting to the emergency department using a machine learning score incorporating heart rate variability compared with the modified early warning score. Crit Care. 2012;16(3). doi: 10.1186/cc11396. 1275. Hodge AB, Snyder AC, Fernandez AL, Boan AD, Malek AM, Sistino JJ. The effect of acute sleep deprivation and fatigue in cardiovascular perfusion students: A mixed methods study. J Extra-Corpor Technol. 2012;44(3):116-25. 1276. Hoover A, Singh A, Fishel-Brown S, Muth E. Real-time detection of workload changes using heart rate variability. Biomed Signal Process Control. 2012;7(4):333-41. doi: 10.1016/j.bspc.2011.07.004. 1277. Howitt P, Darzi A, Yang GZ, Ashrafian H, Atun R, Barlow J, et al. Technologies for global
8203875.f1.docx