Short-term acoustic forecasting via artificial neural networks for neonatal intensive care units

Journal of the Acoustical Society of America

Volumn 132, Issue 5, 2012, Pages 3234-3239

  Young, Jason ^a   MacKe, Christopher J ^b   Tsoukalas, Lefteri H ^b  

^a Sonicu LLC   (United States)

^b PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AVERAGE ABSOLUTE ERROR; FORECASTING ALGORITHM; NEONATAL INTENSIVE CARE UNITS; NOISE LEVELS;

HOSPITALS; NEONATAL MONITORING; NEURAL NETWORKS;

FORECASTING;

ACOUSTICS; ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; ENVIRONMENTAL EXPOSURE; ENVIRONMENTAL MONITORING; EQUIPMENT; FORECASTING; HOSPITAL DESIGN; HUMAN; METHODOLOGY; NEWBORN; NEWBORN INTENSIVE CARE; NOISE; PRESSURE; PRESSURE TRANSDUCER; SOUND DETECTION; TIME;

ACOUSTICS; ALGORITHMS; ENVIRONMENTAL EXPOSURE; ENVIRONMENTAL MONITORING; FORECASTING; HOSPITAL DESIGN AND CONSTRUCTION; HUMANS; INFANT, NEWBORN; INTENSIVE CARE UNITS, NEONATAL; NEURAL NETWORKS (COMPUTER); NOISE; PRESSURE; SOUND SPECTROGRAPHY; TIME FACTORS; TRANSDUCERS, PRESSURE;

EID: 84869127308     PISSN: 00014966     EISSN: None     Source Type: Journal    
DOI: 10.1121/1.4754556     Document Type: Article

References (19)

1. American Academy of Pediatrics, Noise: A hazard for the fetus and newborn., Pediatrics 100 (4), 724-727 (1997). 10.1542/peds.100.4.724
2. A. Richardson, A. Thompson, E. Coghill, I. Chambers, and C. Turnock, Development and implementation of a noise reduction intervention programme: A pre- and postaudit of three hospital wards., J. Clin. Nurs. 18 (23), 3316-3324 (2009). 10.1111/j.1365-2702.2009.02897.x
3. D. S. Richards, B. Frentzen, K. J. Gerhardt, M. E. McCann, and R. M. Abrams, Sound levels in the human uterus., Obstet. Gynecol. 80 (2), 186-190 (1992).
4. J. G. Long, J. F. Lucey, and A. Philip, Noise and hypoxemia in the intensive care nursery., Pediatrics 65 (1), 143-145 (1980).
5. M. K. Philbin and J. B. Evans, Standards for the acoustic environment of the newborn ICU., J. Perinatol. 26.S3, 27-30 (2006). 10.1038/sj.jp.7211585
6. S. N. Graven, Sound and the developing infant in the NICU: Conclusions and recommendations for care., J. Perinatol. 20 (8), S88-S93 (2000). 10.1038/sj.jp.7200444
7. R. D. White, Recommended standards for newborn ICU design., J. Perinatol. 26 (3), S2-S18 (2006). 10.1038/sj.jp.7211587
8. M. K. Philbin, Planning the acoustic environment of a neonatal intensive care unit., Clinics Perinatol. 31 (2), 331-352 (2004). 10.1016/j.clp.2004.04.014
9. C. Krueger, S. Schue, and L. Parker, Neonatal intensive care unit sound levels before and after structural reconstruction., MCN Am. J. Matern. Child Nurs. 32 (6), 358-362 (2007). 10.1097/01.NMC.0000298131.55032.76
10. W. F. Liu, The impact of a noise reduction quality improvement project upon sound levels in the open-unit-design neonatal intensive care unit., J. Perinatol. 30 (7), 489-496 (2009). 10.1038/jp.2009.188
11. L. H. Tsoukalas and R. E. Uhrig, Fuzzy and Neural Approaches in Engineering, 1st ed. (Wiley, New York, 1996), pp. 191-405.
12. H. S. Hippert, C. E. Pedreira, and R. C. Souza, Neural networks for short-term load forecasting: a review and evaluation., IEEE Trans. Power Syst. 16, 44-55 (2001). 10.1109/59.910780
13. D. C. Park, M. A. Elsharkawi, R. J. Marks, L. E. Atlas, and M. J. Damborg, Electric-load forecasting using an artificial neural network., IEEE Trans. Power Syst. 6, 442-449 (1991). 10.1109/59.76685
14. R. Kuo, C. Chen, and Y. Hwang, An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network., Fuzzy Sets Syst. 118 (1), 21-45 (2001). 10.1016/S0165-0114(98)00399-6
15. M. French, W. Krajewski, and R. Cuykendall, Rainfall forecasting in space and time using a neural network., J. Hydrol. 137 (1-4), 1-31 (1992). 10.1016/0022-1694(92)90046-X
16. V. Chritin, R. Bolognesi, and H. Gubler, FlowCapt: A new acoustic sensor to measure snowdrift and wind velocity for avalanche forecasting., Cold Regions Sci. Technol. 30 (1-3), 125-133. 10.1016/S0165-232X(99)00012-9
17. Y. Xu and D. Xu, The study of forecasting model of rock burst for acoustic emission based on BP neural network and catastrophe theory., in Advances in Neural Network Research and Applications, edited by, Zhigang Zeng, and, Jun Wang, (Springer, Berlin, 2010), Vol. 67, pp. 11-19.
18. M. J. Murphy and D. Pokhrel, Optimization of an adaptive neural network to predict breathing., Med. Phys. 36, 40-47 (2010). 10.1118/1.3026608
19. A. Yoshihiro Nakano, S. Nakagawa, and K. Yamamoto, Automatic estimation of position and orientation of an acoustic source by a microphone array network., J. Acoust. Soc. Am. 126, 3084-3094 (2009). 10.1121/1.3257548