An Intelligent cognitive sensing and detection strategy for medical telemetry networks

In medical telemetry networks, cognitive radio technology is mostly used to avoid licensed spectrum underutilization and by providing access to unlicensed spectrum users without causing interference to primary users, this concept is widely used in development of smart hospitals and smart cities. In medical telemetry networks frequency spectrum concept is used for providing treatment to patients who are far away from hospitals. In cognitive radios, spectrum sensing concept is used in which energy detection method is mostly used because it is simple to implement. While measuring health care environments using cognitive radios probability detection, false alarm probability and threshold parameters are calculated. In this paper for identifying spectrum holes in spectrum sensing using energy detection, distributed diffusion non-negative least mean square algorithm is proposed. It gives better results compared to energy detection concept alone in terms of probability detection converged earlier. If number of nodes are increasing probability detection is decreased from one and move towards left and its SNR is around 1.5-2 dB with proposed method. Hence simulation results give better results in terms of sensing ability while measuring patient condition.

Investigation on Wireless Link for Medical Telemetry Including Impedance Matching of Implanted Antennas

The development of biomedical devices benefits patients by offering real-time healthcare. In particular, pacemakers have gained a great deal of attention because they offer opportunities for monitoring the patient’s vitals and biological statics in real time. One of the important factors in realizing real-time body-centric sensing is to establish a robust wireless communication link among the medical devices. In this paper, radio transmission and the optimal characteristics for impedance matching the medical telemetry of an implant are investigated. For radio transmission, an integral coupling formula based on 3D vector far-field patterns was firstly applied to compute the antenna coupling between two antennas placed inside and outside of the body. The formula provides the capability for computing the antenna coupling in the near-field and far-field region. In order to include the effects of human implantation, the far-field pattern was characterized taking into account a sphere enclosing an antenna made of human tissue. Furthermore, the characteristics of impedance matching inside the human body were studied by means of inherent wave impedances of electrical and magnetic dipoles. Here, we demonstrate that the implantation of a magnetic dipole is advantageous because it provides similar impedance characteristics to those of the human body.

Measuring the Bio-Electrical Parameters of a Person Using Bio-Telemetry System for Health Care Monitoring

Biotelemetry is a method of measuring a persons’s Bio-electrical parameters and a Physio-logical parameters from a distance. It’s like a updation of existing methods of measuring physiological parameters and bioelectrical parameters to a method of transmission of resulting data. This will help the consulting doctor for making a better diagnosis without movement or ensuring mobility of both the doctor and patient. Here the parameters of the wireless remote medical system for health monitoring include body temperature, blood oxygen saturation, pulse, electrocardiogram and Electrooculography. In order to measure, monitor and updating the data we require five sensors for each respective parameter so the respective five sensors are AD8232 sensor for measuring Electrocardiogram, pulse sensor for measuring pulse, EOG sensor for measuring Electrooculography, Max30100 sensor for measuring oxygen levels in blood and finally LM35 sensor used for measuring the hotness or coldness of a body. These are connected as one system using Arduino. Transferring of data to the cloud or update the data in cloud, whatever the data came from the sensors will be sent to a WiFi module called Node MCU ESP8266, through which the data will be uploaded on cloud platforms like Ubidots and Things speak. Finally from this Paper it gives the concept of Bio-Telemetry System, in other words a Medical Telemetry System. This system allows continuous monitoring of a patient’s health condition, as well as updating that respective data into their medical history like cloud platform, thus improving the efficiency of nursing care through more effective time management.