Bioelectrics
Zahra Sadat Hosseini; Seyed Mohammad Reza Hashemi Golpayegani
Volume 13, Issue 1 , April 2019, , Pages 69-84
Abstract
The esophageal carcinoma is the eight most predominate malignancy in the world and the sixth deadliest cancer. 80% of esophageal cancers occur in squamous cells. In Iran, this type of cancer is more prevalent in Golestan province. Before the onset of this type of cancer, histological precursor lesions ...
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The esophageal carcinoma is the eight most predominate malignancy in the world and the sixth deadliest cancer. 80% of esophageal cancers occur in squamous cells. In Iran, this type of cancer is more prevalent in Golestan province. Before the onset of this type of cancer, histological precursor lesions emerge in the epithelial tissue of esophageal mucosa that their progression and penetration into the underlying layers of epithelium lead to cancer. This disease starts from a pre-clinical phase in most patients. In most cases, the disease progresses to the same clinical stage in the absence of appropriate therapeutic interventions. In the literature of this cancer, there is no model for the progression of these lesions (dysplasia) at the mesoscopic level. In this study, by using microscopic images of normal and low-grade dysplasia biopsy samples, we proposed a dynamical model based on the globally coupled logistic maps. The model was designed and its parameters were set based on the assumptions of the esophageal epithelium structure, functionality and using the information about the fractal geometry of this tissue. The model performance was evaluated by computation the pattern of Lyapunov exponent variations across the epithelium thickness. In this model, the decreasing trend of this index for normal tissue had a reasonable accuracy and sensitivity to diagnose it from the low-grade dysplasia. Besides, the model results show that it can be a direct relationship between the structural complexity of this biological system and its timeliness uncertainty.
Zahra sadat Hosseini; Mohadese Arabgari; Ali Farmad; Leili Goldoozian; Hamid Reza Maghari; Sara Aghajari; Edmond Zahedi
Volume 7, Issue 3 , June 2013, , Pages 277-285
Abstract
In this article a wireless patient monitoring system for vital signs (respiratory rate and heart beat) is presented. The recorded biosignal is the photoplethysmogram using a probe attached to the patient's finger. This signal is amplified, filtered and digitized by an on-board processor unit before finally ...
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In this article a wireless patient monitoring system for vital signs (respiratory rate and heart beat) is presented. The recorded biosignal is the photoplethysmogram using a probe attached to the patient's finger. This signal is amplified, filtered and digitized by an on-board processor unit before finally being sent wirelessly via a transmitter. The capacity of the current system is 16 patients whose data can be received through a common receiver by a central server which measures and displays the heart beat and respiratory rate for each patient on the monitor.
