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A. Salman, A. Malony, S. Turovets, V. Volkov, David Ozog, D. Tucker (2016)
Concurrency in electrical neuroinformatics: parallel computation for studying the volume conduction of brain electrical fields in human head tissuesConcurrency and Computation: Practice and Experience, 28
Raymond Lee, A. Carlisle (2011)
Detection of falls using accelerometers and mobile phone technology.Age and ageing, 40 6
Cássio Pereira, R. Mello (2015)
Persistent homology for time series and spatial data clusteringExpert Syst. Appl., 42
Chi Yang, Xuyun Zhang, Changmin Zhong, Chang Liu, J. Pei, K. Ramamohanarao, Jinjun Chen (2014)
A spatiotemporal compression based approach for efficient big data processing on CloudJ. Comput. Syst. Sci., 80
C. Werner, K. Engelhard (2007)
Pathophysiology of traumatic brain injury.British journal of anaesthesia, 99 1
Li Jiang, Xiao-hong Yin, C. Yin, Shuai Zhou, W. Dan, Xiaochuan Sun (2011)
Different quantitative EEG alterations induced by TBI among patients with different APOE genotypesNeuroscience Letters, 505
D. Watts, D. Hanfling, Maureen Waller, C. Gilmore, S. Fakhry, A. Trask (2004)
An evaluation of the use of guidelines in prehospital management of brain injury.Prehospital emergency care : official journal of the National Association of EMS Physicians and the National Association of State EMS Directors, 8 3
A. Irimia, J. Horn, E. Halgren (2012)
Source cancellation profiles of electroencephalography and magnetoencephalographyNeuroImage, 59
A. Irimia, S. Goh, C. Torgerson, N. Stein, M. Chambers, P. Vespa, J. Horn (2013)
Electroencephalographic inverse localization of brain activity in acute traumatic brain injury as a guide to surgery, monitoring and treatmentClinical Neurology and Neurosurgery, 115
Louis Beaumont, H. Théoret, David Mongeon, J. Messier, S. Leclerc, S. Tremblay, D. Ellemberg, M. Lassonde (2009)
Brain Function Decline in Healthy Retired Athletes who Sustained their Last Sports Concussion in Early AdulthoodNeuroImage, 47
Dae-Hyeong Kim, N. Lu, Rui Ma, Yun-Soung Kim, Rak-Hwan Kim, Shuodao Wang, Jian Wu, S. Won, H. Tao, Ahmad Islam, Ki Yu, Tae-il Kim, Raeed Chowdhury, Ming Ying, Lizhi Xu, Ming Li, Hyun‐Joong Chung, H. Keum, Martin McCormick, Ping Liu, Yong-Wei Zhang, F. Omenetto, Yonggang Huang, Todd Coleman, J. Rogers (2011)
Epidermal ElectronicsScience, 333
A. Irimia, J. Horn (2015)
Epileptogenic focus localization in treatment-resistant post-traumatic epilepsyJournal of Clinical Neuroscience, 22
J. Corrigan, C. Harrison-Felix, J. Bogner, M. Dijkers, Melissa Terrill, G. Whiteneck (2003)
Systematic bias in traumatic brain injury outcome studies because of loss to follow-up.Archives of physical medicine and rehabilitation, 84 2
A. Irimia, S. Goh, C. Torgerson, M. Chambers, R. Kikinis, J. Horn (2013)
Forward and inverse electroencephalographic modeling in health and in acute traumatic brain injuryClinical Neurophysiology, 124
R. Chesnut (1998)
Implications of the guidelines for the management of severe head injury for the practicing neurosurgeon.Surgical neurology, 50 3
A. Siegel, S. Phillips, M. Dickey, N. Lu, Z. Suo, G. Whitesides (2010)
Foldable Printed Circuit Boards on Paper SubstratesAdvanced Functional Materials, 20
Ze Tian, TaeHyun Hwang, R. Kuang (2009)
A hypergraph-based learning algorithm for classifying gene expression and arrayCGH data with prior knowledgeBioinformatics, 25 21
Neuroinform (2017) 15:227–230 DOI 10.1007/s12021-017-9335-z EDITORIAL Mobile Monitoring of Traumatic Brain Injury in Older Adults: Challenges and Opportunities 1 2 3 4 Andrei Irimia & Susan Wei & Nanshu Lu & ConstanceM.Moore & David N. Kennedy Published online: 26 July 2017 Springer Science+Business Media, LLC 2017 . . Keywords Mobile device Neuroimaging in popularity, and extensive efforts have been dedicated to the Electroencephalography Traumatic brain injury development of bioinformatic approaches for their automated analysis and interpretation. Older adults constitute a particularly suitable target Throughout the past decade, the use of mobile sensors to monitor population for mobile monitoring due to their greater sus- human physiology has emerged as a promising strategy for en- ceptibility to disease, higher risk for complications fol- couraging healthy behaviors, assisting self-management of lowing clinical interventions, reduced mobility, and nu- chronic disease, reducing health problems, decreasing the num- merous other reasons. For example, individuals over the ber of healthcare visits and facilitating beneficial interventions to age of 65 are considerably more susceptible to traumatic improve well-being. Devices which facilitate periodic and/or brain injury (TBI) than their younger counterparts partly continuous monitoring of key physiological parameters such as because senior citizens have more limited motor ability
Neuroinformatics – Springer Journals
Published: Jul 26, 2017
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