Augmenting Breath Regulation Using a Mobile Driven Virtual Reality Therapy Framework

被引:22
作者
Abushakra, Ahmad [1 ]
Faezipour, Miad [1 ]
机构
[1] Univ Bridgeport, Bridgeport, CT 06604 USA
关键词
Breathing movement classification; lung capacity estimation; virtual therapy; visualization; ACOUSTIC-SIGNAL; LUNG; CANCER;
D O I
10.1109/JBHI.2013.2281195
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a conceptual framework of a virtual reality therapy to assist individuals, especially lung cancer patients or those with breathing disorders to regulate their breath through real-time analysis of respiration movements using a smartphone. Virtual reality technology is an attractive means for medical simulations and treatment, particularly for patients with cancer. The theories, methodologies and approaches, and real-world dynamic contents for all the components of this virtual reality therapy (VRT) via a conceptual framework using the smartphone will be discussed. The architecture and technical aspects of the offshore platform of the virtual environment will also be presented.
引用
收藏
页码:746 / 752
页数:7
相关论文
共 30 条
[1]  
Aboalsamh H., 2011, 2011 IEEE 11th International Conference on Bioinformatics & Bioengineering, P143, DOI 10.1109/BIBE.2011.69
[2]  
Abushakra A., 2012, Proceedings of the IEEE International Conference on Electro/Information Technology (EIT), P1
[3]  
Abushakra A., 2012, Proceedings of the 1st IEEE Healthcare Technology Conference: Translational Engineering in Health Medicine (HIC'12), P232
[4]   Acoustic Signal Classification of Breathing Movements to Virtually Aid Breath Regulation [J].
Abushakra, Ahmad ;
Faezipour, Miad .
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2013, 17 (02) :493-500
[5]  
Abushakra A, 2012, IEEE INT C BIOINF BI, P386, DOI 10.1109/BIBE.2012.6399655
[6]  
[Anonymous], 2013, NUCLEUS MED VIDEO AN
[7]  
[Anonymous], 2013, BREATHING TREATMENTS
[8]  
Becker D.A., 1996, AAAI Workshop on Entertainment and Alife/AI, P17
[9]  
Becker D. A., 1997, 390 MIT
[10]   Lung micronodules: Automated method for detection at thin-section CT - Initial experience [J].
Brown, MS ;
Goldin, JG ;
Suh, RD ;
McNitt-Gray, MF ;
Sayre, JW ;
Aberle, DR .
RADIOLOGY, 2003, 226 (01) :256-262