Wireless Body Sensor Networks for Patient Health Monitoring

Remote medical health management is the most attractive research field in the domain of WSN. Wireless body area network (WBAN) produces constant, unbroken observation of the patient. Basically, WBAN acts as the appliance of internet of things (IoT) which offers an opportunity to a medical examiner to supervise chronic disease. Dissimilar protocols, guidelines, policies have been developed and developing in the last decade. In WBAN, minute power sensor nodes deployed toward capturing unusual essential signs of patients at home, hospitals in support of analysis purpose and furthermore advise suitable procedures. The main goal of this chapter is to introduce a complete and advanced understanding of WBANs, energy savings methods, human activity monitoring procedures, challenges and research issues, applications, and a comprehensive literature survey.

Developing Security Solutions for Telemedicine Applications

Telemedicine is defined as the means of providing healthcare for people from a distance by the use of telecommunication and information technology. This technology is mainly useful in overcoming the obstacles of distance and provide enhancement in the access of medical services that would not be easily available in different rural areas. Telemedicine security includes issues such as confidentiality, integrity, and authentication that are also present in other systems involving information and data. Maintaining integrity of data stored and used is a huge problem for medical applications because it contains more sensitive medical records of patients which can cause severe ill effects on slight modification. In order to resolve the confidentiality and integrity issues of telemedicine applications, medical image encryption and watermarking comes into play. The security issues in telemedicine applications is to be given higher importance and thus choosing a reliable and effective approach or framework is more essential.

Sensing and Monitoring of Epileptical Seizure Under IoT Platform

Epilepsy is a disorder that affects the life of the patient. In this neurological disorder, patients may suffer from different types of seizures. From epileptic patients, we may acquire electroencephalogram (EEG) data using various kinds of sensors and transmit them through the cloud. In this chapter, the authors have discussed various platforms related to IoT-enabled cloud for sharing the information and to get quick response in form suggestion. Use of smartphone applications for real-time monitoring of patients and for other applications is presented here. Various wearable devices may provide huge benefits for taking care of seizures and patients. The authors proposed a system model based on IoT-enabled cloud for sharing the information with various sensors and other devices to make a proper judgment about seizures, which will be able to provide improved e-health service. With the increasing rate of improvement in both IoT and e-health field, it is now a challenge to upgrade ourselves and work with the digital world to provide low cost, accurate, and quick solutions.

Feasible Challenges and Applications of IoT in Healthcare

In this chapter, the major enhanced techniques of internet of healthcare things (IoHT) with wearable sensor technologies (WST), stationary medical devices (SMD), and integrated system technologies (IST) for heterogeneous healthcare professionals are explored. A detailed view of the system architecture for developing IoHT device and a lot of issues are also described. The latest innovative technologies are realistic to specific purposes in the field of healthcare assessment. Analysis, sensor, and data studies approach the opportunities to improve personal healthcare and benefits for the medical industry. The ultimate aim of succeeding superior healthcare practice is to competently combine with information from diverse bases, to allocate the accumulated data, to retrieve the collected data. Effective data analysis tools from data with initialed conception services are needed while maintaining their security and privacy. Healthcare professionals, patients, and clients can take benefit of the IoHT for giving personalized smart care guidelines or solutions for existing technologies.

Methodical IoT-Based Information System in Healthcare

Elderly monitoring has become essential to provide comfort and flexible life for the aged. Internet of things is a field that aids in providing accurate information through communication. Using these devices, emergency alerts can be raised. The chapter provides an assistance model that aids the caretakers and doctors to provide appropriate action during emergencies. Different conditions of the patient are considered to analyze the working of the system. The work shows considerable amount of flexibility from the previous system.

Electronic Health Record Security in Cloud

Security is the primary issue nowadays because cybercrimes are increasing. The organizations can store and maintain their data on their own, but it is not cost effective, so for convenience they are choosing cloud. Due to its popularity, the healthcare organizations are storing their sensitive data to cloud-based storage systems, that is, electronic health records (EHR). One of the most feasible methods for maintaining privacy is homomorphism encryption (HE). HE can combine different services without losing security or displaying sensitive data. HE is nothing but computations performed on encrypted data. According to the type of operations and limited number of operations performed on encrypted data, it is categorized into three types: partially homomorphic encryption (PHE), somewhat homomorphic encryption (SWHE), fully homomorphic encryption (FHE). HE method is very suitable for the EHR, which requires data privacy and security.

Smart Healthcare Monitoring System for War-End Soldiers Using CNN

Health monitoring plays a vital role to overcome the health issues of the patients. According to research, approximately 2000 people die due to carelessness of monitoring their health. Wearable monitoring systems record the activities of daily life. A 24-hour wearable monitoring system was developed and changes were identified. This project is designed for helping the soldiers to maintain their health conditions and to identify their health issues at war's end. Different health parameters are monitored using sensors, and the data are transmitted through GSM to the receiver, and the received data are analyzed using convolutional neural networks, which is performed in cloud IoT. If any abnormalities are found during the analyzing process, the message is sent to military personnel and the doctor at the camp so that they could take necessary actions to recover the ill soldier from the war field and provide emergency assistance on time. The location of the soldier is also shared using the input from GPS modem in the smart jacket.

Blended Models for Nearest Neighbour Algorithms for High Dimensional Smart Medical Data

Nearest neighbor algorithms like kNN and Parzen Window are generative algorithms that are used extensively for medical diagnosis and classification of diseases. The data generated or collected in healthcare is high dimensional and cannot be assumed to follow a particular distribution. The conventional approaches fail due to computational complexity, curse of dimensionality, and varying distributions. Hence, this chapter deals with a blending technique for evaluation of nearest neighbor algorithms based on various parameters such as the size of data, dimensions of data, window size, and number of nearest neighbors to make it suitable for massive datasets. Dimensionality reduction and clustering are combined with nearest neighbor classifier such as kNN and Parzen Window to observe the performance of the blended models on various types of datasets. Experimental results on 15 real datasets with various models reveal the efficacy of the proposed blends.

Smart ECG Monitoring Through IoT

The emergence of internet of things allows the integration of health systems by enabling real-time monitoring with a low cost. Therefore, one of the essential targets in this work is the realization of a new smart real-time electrocardiogram remote monitoring system based on cloud networks. This health wireless system allows the acquisition of electrocardiogram signal with the temperature and acceleration measurement of the patient's body using the inertial measurement unit module sensor. A strong access schemes is employed to transfer the data from sensors to cloud environment by keeping the protection of e-health information. The second objective in this chapter is designing a flexible and stretchable health circuit basing on design considerations, aiming the combination of flexible, elastic, and rigid materials around minimal constraints and maximum mechanical dependability in the structures. The flexible fabrication part was inspired from the biocompatible process technology.

mHealth

Mobile health (mHealth), the application of mobile technologies for healthcare services, has been the driving force in healthcare in the last few decades; from healthcare service delivery to low-cost tools for effective disease diagnosis, prediction, monitoring, and management. The main purpose of this chapter was to identify the scope and range of studies on mHealth used as low-cost tools for effective disease diagnosis, prediction, monitoring, and management. The authors identified 55 papers that met the inclusion and exclusion criteria after searching different academic databases. The findings revealed that low-cost mHealth approaches such as text messaging and mobile applications developed using artificial intelligence algorithms have been used for disease diagnosis, prediction, monitoring, and management. The findings of this scoping review present information regarding different mHealth approaches that can be used by researchers and practitioners interested in the application of low-cost mHealth solutions in low-resource settings.