scholarly journals Fundamental Study of Quantitative Evaluation of Radio Wave Output of Wireless Medical Telemetry Transmitters Operable in Medical Field

2020 ◽  
pp. 5-10
Author(s):  
Kiyotaka Fujii ◽  
Kazumasa Kishimoto ◽  
Munenori Inoue
Keyword(s):  
Radio Wave ◽  
Quantitative Evaluation ◽  
Wave Spectrum ◽  
Threshold Value ◽  
Propagation Model ◽  
Biological Information ◽  
Medical Field ◽  
Long Distance ◽  
Fundamental Study ◽  
Medical Telemetry

Wireless medical telemetry systems (WMTSs) are important medical equipment for monitoring of biological information such as the electrocardiogram of a patient in a remote location in real time. However, because WMTSs have characteristically used channels that are unique to the radio wave spectrum, many institutions have not previously managed WMTSs. Therefore, we examined a method for quantitative evaluation of the radio wave output of a wireless medical telemetry transmitter (WMTT) that can even be implemented in the medical field. In the experiments, we demonstrated the possibility of use of the method for quantitative evaluation of WMTT radio wave output in the medical field using two types of radio wave propagation model: a free-space propagation model and a two-ray ground reflection model. To determine the reference threshold value for use of each model, a breakpoint was found to be important to grasp the change point between short distance and long distance. It was indicated that the measured value was lower than the theoretical value below the breakpoint, while the measured value was slightly higher than the theoretical value beyond the breakpoint.

scholarly journals A Novel Radio Wave Propagation Modeling Method Using System Identification Technique over Wireless Links in East Africa

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Solomon T. Girma ◽  
Dominic B. O. Konditi ◽  
Ciira Maina
Keyword(s):  
Wave Propagation ◽  
System Identification ◽  
Radio Wave ◽  
Free Space ◽  
Urban Areas ◽  
Radio Channel ◽  
Signal Propagation ◽  
Propagation Model ◽  
Radio Wave Propagation ◽  
Study Region

Transmission of a radio signal through a wireless radio channel is affected by refraction, diffraction and reflection, free space loss, object penetration, and absorption that corrupt the originally transmitted signal before radio wave arrives at a receiver antenna. Even though there are many factors affecting wireless radio channels, there are still a number of radio wave propagation models such as Okumura, Hata, free space model, and COST-231 to predict the received signal level at the receiver antenna. However, researchers in the field of radio wave propagation argue that there is no universally accepted propagation model to guarantee a universal recommendation. Thus, this research is aimed at determining the difference between the measured received signal levels and the received signal level calculated from the free space propagation model. System identification method has been proposed to determine this unknown difference. Measured received signal levels were collected from three randomly selected urban areas in Ethiopia using a computer, Nemo test tool, Actix software, Nokia phone, and GPS. The result from the simulations was validated against the received experimental signal level measurement taken in a different environment. From the simulation results, the mean square error (MSE) was 4.169 dB, which is much smaller than the minimum acceptable MSE value of 6 dB for good signal propagation, and 74.76% fit to the estimation data. The results clearly showed that the proposed radio wave propagation model predicts the received signal levels at 900 MHz and 1800 MHz in the study region.

Quantitative evaluation in tumor SPECT and the effect of tumor size: Fundamental study with phantom

1997 ◽  
Vol 11 (1) ◽  
pp. 51-54 ◽  
Author(s):  
Takashi Togawa ◽  
Nobuharu Yui ◽  
Fujimi Kinoshita ◽  
Masamichi Yanagisawa
Keyword(s):  
Quantitative Evaluation ◽  
Tumor Size ◽  
Fundamental Study

scholarly journals Stability and Bifurcation of a Computer Virus Propagation Model with Delay and Incomplete Antivirus Ability

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Jianguo Ren ◽  
Yonghong Xu
Keyword(s):  
Hopf Bifurcation ◽  
Threshold Value ◽  
Computer Virus ◽  
Propagation Model ◽  
Global Dynamics ◽  
Asymptotically Stable ◽  
Virus Propagation ◽  
Globally Asymptotically Stable ◽  
Existence And Stability ◽  
Computer Virus Propagation Model

A new computer virus propagation model with delay and incomplete antivirus ability is formulated and its global dynamics is analyzed. The existence and stability of the equilibria are investigated by resorting to the threshold valueR0. By analysis, it is found that the model may undergo a Hopf bifurcation induced by the delay. Correspondingly, the critical value of the Hopf bifurcation is obtained. Using Lyapunov functional approach, it is proved that, under suitable conditions, the unique virus-free equilibrium is globally asymptotically stable ifR0<1, whereas the virus equilibrium is globally asymptotically stable ifR0>1. Numerical examples are presented to illustrate possible behavioral scenarios of the mode.

The Hybrid HMM for RSS-Based Localization in Wireless Sensor Networks

2013 ◽  
Vol 347-350 ◽  
pp. 796-802 ◽  
Author(s):  
Yan Hong Zang ◽  
Jin Song Wang ◽  
Lin Ling ◽  
Pei Zhong Lu
Keyword(s):  
Wireless Sensor Networks ◽  
Hidden Markov ◽  
Signal Strength ◽  
Threshold Value ◽  
Signal Propagation ◽  
Propagation Model ◽  
Wireless Sensor ◽  
Node Localization ◽  
Localization Accuracy ◽  
Signal Propagation Model

We proposea method of RSS-base localization in WSN (Wireless Sensor Network), called Hybrid HMM, to improve the stabilityof node localization basedon RSS(Received Signal Strength).This model utilizesHMM(Hidden Markov Model) to takeinto account the time factor when receiving the RSS sequence, andconverts the action of ranging into an operationof classification.For the received RSS used for localization,our Hybrid HMMwill compare it withthe preset RSS threshold value, and put the result into one of two categories for subsequent processing: If the received value is higher than the threshold value, the distance value will be drawn from the signal propagation model. If lower, the information will be obtained from a trained HMM. Experimental results show that the Hybrid HMM method can greatly improve the localization accuracy.

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