Abnormality detection in wireless medical sensor networks using machine learning model

The monitoring of long-term physiological parameters in hospital settings is costly and requires the presence of important healthcare personnel. Wireless medical sensor networks (WMSNs) can be used to monitor patients' physiological data, making healthcare applications one of the most promising areas for wireless sensor networks. The remote management of patient healthcare may change with the introduction of wireless sensor devices as a part of a Wireless Body Area Network (WBAN) integrated within an overall e-Health system. A crucial component of a comprehensive health monitoring network can include tiny sensor devices that are positioned within or on top of the human body. Although it should be efficient in its process, an energy-efficiently built WBAN and WMSN should have no effect on the patient's mobility or way of life. WBAN technology can be used in a patient's residence, a hospital, or a health care facility. Patients' privacy is jeopardised when new technologies are implemented in healthcare applications without proper security considerations. Security is an essential prerequisite for healthcare apps since physiological data about an individual is extremely sensitive, particularly when it comes to patient privacy.