شبکه هوشمند برای مانیتورینک وضعیت بیمار سرطان سینه
محورهای موضوعی : مهندسی الکترونیکمحمد علی پورمینا 1 , جواد نوری پور 2 , محمد ناصرمقدسی 3 , بهبد قلمکاری 4
1 - دانشکده:مکانیک، برق و کامپیوتر ، دانشگاه آزاد واحد علوم تحقیقات،تهران، ایران
2 - دانشکده:مکانیک، برق و کامپیوتر ، دانشگاه آزاد واحد علوم تحقیقات،تهران، ایران
3 - دانشکده:مکانیک، برق و کامپیوتر ، دانشگاه آزاد واحد علوم تحقیقات،تهران، ایران
4 - دانشکده:مکانیک، برق و کامپیوتر ، دانشگاه آزاد واحد علوم تحقیقات،تهران، ایران
کلید واژه: گره ها, وزن ارتباطی, تومور سینه, آرایش توانمندی شبکه,
چکیده مقاله :
همواره نظارت بلادرنگ بر بیمار بسیار مورد اهمیت بوده است. دستیابی به این دانش که بهصورت یکپارچه بتوان بر بافت آسیبدیده نظارت داشت، کار بسیار مهم میباشد. در روشهای قبلی با استفاده از یک حسگر بر بافت موردنظر نظارت می شد. در این مقاله نهتنها با استفاده از یک حسگر بر بافت نظارت می شود بلکه نظارت و ارزیابی تأثیر بافتهای دیگر، بر بافت تومور مورد ارزیابی قرار می گیرد. شبکه هوشمند که در این مقاله مطرح شده است، بهمنظور نظارت بر وضعیت بیمار دارای تومور سینه طراحی شده است. ساختار شبکه هوشمند با توجه به نوع وزن مسیرهای ارتباطی بین گرهها و توانایی گرهها یک شبکه نیرومند برای ارزیابی وضعیت بیمار را به ما نشان میدهد. با تغییر وضعیت بیمار، گرهها و وزن مسیرهای ارتباطی تغییر میکند که این نشان میدهد که اطلاعات مهمی در شبکه وجود دارد و به متخصصان کمک میکند تا بتوانند بهتر وضعیت بیماری را موردبررسی قرار دهند. نظارت شبکه به این صورت می باشد که به صورت مداوم گره ارزیاب، گره تومور را ارزیابی می کند، با تغییر وضعیت گره تومور، وضعیت سایر گره ها و مسیرهای ارتباطی بین آن تغییر می کند، نتیجه تغییرات در شبکه به وسیله گره ارزیاب مورد ارزیابی قرار می گیرد. نتایج شبیهسازی نشان میدهد که این شبکه از هوشمندی لازم برای ارزیابی وضعیت بیمار در شرایط نامطلوب را دارا میباشد.
Immediate monitoring of the patient has always been very important. Achieving this knowledge, which can be integrated to monitor damaged tissue, is very important. In previous methods, the tissue was monitored using a sensor. In this article, not only is a tissue monitored using a sensor, but also the monitoring and evaluation of the effect of other tissues on tumor tissue is evaluated. The smart grid discussed in this article is designed to monitor the condition of a patient with a breast tumor. The structure of the smart grid, given the weight of the communication paths between the nodes and the ability of the nodes, shows us a strong network to assess the patient's condition. As the patient's condition changes, the nodes and weights of the communication pathways change, indicating that there is important information in the network and helping specialists to better assess the condition of the disease. Network monitoring is such that the evaluator node continuously evaluates the tumor node, by changing the status of the tumor node, the status of other nodes and communication paths between them changes, the result of changes in the network by the node The evaluator is evaluated. The simulation results show that this network has the necessary intelligence to assess the patient's condition in adverse conditions.
[1] A. E. Attaoui, M. Hazmi, A. Jilbab and A. Bourouhou, "Wearable Wireless Sensors Network for ECG Telemonitoring Using Neural Network for Features Extraction," wireless Personal Communications, vol. 111, no. 10, pp. 1955–1976, Nov. 2019, doi:10.1007/s11277-019-06967-x.
[2] GH. Imanian, M. A. Pourmina and A. Salahi, "Compressive Sensing-based Data Aggregation in Wireless Sensor Networks: A Review," Journal of Communication Engineering, vol. 11, no.42, pp. 1-14, 2022(in Persian).
[3] Y. Chen and P. E. Pace, "Simulation of information metrics to assess the value of networking in a general battlespace topology," IEEE International Conference on System of Systems Engineering, 2008, pp. 1-6, doi: 10.1109/SYSOSE.2008.4724133.
[4] M. Magalhaes, T. E. Smith and P. E. Pace, "Adaptive node capability to assess the characteristic tempo in a wireless communication network," IEEE Wireless Communications and Networking Conference (WCNC), 2012, pp. 3013-3018, doi: 10.1109/WCNC.2012.6214321.
[5] J. Tuckman and J. Shillingford, "Effect of different degrees of tilt on cardiac output, heart rate, and blood pressure in normal man," British Heart Journal, vol. 28, no. 1, p. 32, 1966, doi: 10.1136/hrt.28.1.32.
[6] G.-J. Jong and G.-J. Horng, "The PPG physiological signal for heart rate variability analysis," Wireless Personal Communications, vol. 97, no. 6, pp. 5229-5276, 2017, doi: 10.1007/s11277-017-4777-z.
[7] S. Lorente, M. Hautefeuille, and A. Sanchez-Cedillo, "The liver, a functionalized vascular structure," Scientific Reports, vol. 10, no. 1, pp. 1-10, 2020, doi: 10.1038/s41598-020-73208-8.
[8] S. Lorente, A. Torres, M. Hautefeuille, and A. Sanchez-Cedillo, "Hierarchical modeling of the liver vascular system," Frontiers in physiology, p. 1946, 2021, doi:10.3389/fphys.2021.733165.
[9] B. M. Hussen et al., "Signaling pathways modulated by miRNAs in breast cancer angiogenesis and new therapeutics," Pathology-Research and Practice, p. 153764, 2022, doi: 10.1016/j.prp.2022.153764.
[10] M. Ahmadi and K. Mohamedpour, "A New Method for Recognizing Pulse Repetition Interval Modulation," International Conference on Signal Processing Systems, 2009, pp. 146-151, doi: 10.1109/ICSPS.2009.8.
[11] E. Cianca and B. Gupta, "FM-UWB for communications and radar in medical applications," Wireless Personal Communications, vol. 51, no. 4, pp.793-809,2009, doi:10.1007/s11277-009-9772-6.
[12] I. E. Khuda, M. I. Anis, and M. Aamir, "Numerical modeling of human tissues and scattering parameters for microwave cancer imaging systems," Wireless Personal Communications, vol. 95, no. 2, pp. 331-351, 2017, doi:10.1007/s11277-016-3895-3.
[13] E. J. Bond, Xu Li, S. C. Hagness and B. D. Van Veen, "Microwave imaging via space-time beamforming for early detection of breast cancer," in IEEE Transactions on Antennas and Propagation, vol. 51, no. 8, pp. 1690-1705, Aug. 2003, doi: 10.1109/TAP.2003.815446.
_||_[1] A. E. Attaoui, M. Hazmi, A. Jilbab and A. Bourouhou, "Wearable Wireless Sensors Network for ECG Telemonitoring Using Neural Network for Features Extraction," wireless Personal Communications, vol. 111, no. 10, pp. 1955–1976, Nov. 2019, doi:10.1007/s11277-019-06967-x.
[2] GH. Imanian, M. A. Pourmina and A. Salahi, "Compressive Sensing-based Data Aggregation in Wireless Sensor Networks: A Review," Journal of Communication Engineering, vol. 11, no.42, pp. 1-14, 2022(in Persian).
[3] Y. Chen and P. E. Pace, "Simulation of information metrics to assess the value of networking in a general battlespace topology," IEEE International Conference on System of Systems Engineering, 2008, pp. 1-6, doi: 10.1109/SYSOSE.2008.4724133.
[4] M. Magalhaes, T. E. Smith and P. E. Pace, "Adaptive node capability to assess the characteristic tempo in a wireless communication network," IEEE Wireless Communications and Networking Conference (WCNC), 2012, pp. 3013-3018, doi: 10.1109/WCNC.2012.6214321.
[5] J. Tuckman and J. Shillingford, "Effect of different degrees of tilt on cardiac output, heart rate, and blood pressure in normal man," British Heart Journal, vol. 28, no. 1, p. 32, 1966, doi: 10.1136/hrt.28.1.32.
[6] G.-J. Jong and G.-J. Horng, "The PPG physiological signal for heart rate variability analysis," Wireless Personal Communications, vol. 97, no. 6, pp. 5229-5276, 2017, doi: 10.1007/s11277-017-4777-z.
[7] S. Lorente, M. Hautefeuille, and A. Sanchez-Cedillo, "The liver, a functionalized vascular structure," Scientific Reports, vol. 10, no. 1, pp. 1-10, 2020, doi: 10.1038/s41598-020-73208-8.
[8] S. Lorente, A. Torres, M. Hautefeuille, and A. Sanchez-Cedillo, "Hierarchical modeling of the liver vascular system," Frontiers in physiology, p. 1946, 2021, doi:10.3389/fphys.2021.733165.
[9] B. M. Hussen et al., "Signaling pathways modulated by miRNAs in breast cancer angiogenesis and new therapeutics," Pathology-Research and Practice, p. 153764, 2022, doi: 10.1016/j.prp.2022.153764.
[10] M. Ahmadi and K. Mohamedpour, "A New Method for Recognizing Pulse Repetition Interval Modulation," International Conference on Signal Processing Systems, 2009, pp. 146-151, doi: 10.1109/ICSPS.2009.8.
[11] E. Cianca and B. Gupta, "FM-UWB for communications and radar in medical applications," Wireless Personal Communications, vol. 51, no. 4, pp.793-809,2009, doi:10.1007/s11277-009-9772-6.
[12] I. E. Khuda, M. I. Anis, and M. Aamir, "Numerical modeling of human tissues and scattering parameters for microwave cancer imaging systems," Wireless Personal Communications, vol. 95, no. 2, pp. 331-351, 2017, doi:10.1007/s11277-016-3895-3.
[13] E. J. Bond, Xu Li, S. C. Hagness and B. D. Van Veen, "Microwave imaging via space-time beamforming for early detection of breast cancer," in IEEE Transactions on Antennas and Propagation, vol. 51, no. 8, pp. 1690-1705, Aug. 2003, doi: 10.1109/TAP.2003.815446.