Abstract

In a clinical scenario when the patient is far from the hospital, the patient is not treated in time. In that scenario, the medical telemetry network plays a vital role. So, it is intended to develop a medical body area network for remote health care monitoring utilizing cognitive radio methods. A Medical Body Area Network (MBAN) consists of multiple sensor nodes, these nodes may be wearable and implantable devices and by using this device we get the patient physiological data and each having the capability of sampling, processing and communicating with vital signals. Medical Telemetry is a technology, it involves information processing and communication technologies to utilize in healthcare services. In wireless communications, medical telemetry plays a vital role to use in health care applications like telemedicine, remote patient monitoring, etc., Spectrum sensing is one of the cognitive radio methods, it can be used in the field of medical telemetry. Spectrum sensing using an energy detection technique can be used in medical telemetry for health care monitoring. The proposed implementation finds an immediate application in the development of smart cities and smart hospitals. Here, we use a Modified Normalized LMS algorithm for this purpose. Problems of energy detection and measurement lead to spectrum sensing in a telemetry network that can be solved by the proposed method. Results show that the performance of Modified Normalized LMS gives better simulations in terms of detection probability (P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> ) and false alarm (P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> ).

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.