A guide to intelligent decision and pervasive computing paradigms for healthcare analytics systems with a focus on the use of bio-sensors Intelligent Pervasive Computing Systems for Smarter Healthcare describes the innovations in healthcare made possible by computing through bio-sensors. The pervasive computing paradigm offers tremendous advantages in diversified areas of healthcare research and technology. The authors noted experts in the field provide the state-of-the-art intelligence paradigm that enables optimization of medical assessment for a healthy, authentic, safer, and more productive environment. Today s computers are integrated through bio-sensors and generate a huge amount of information that can enhance our ability to process enormous bio-informatics data that can be transformed into meaningful medical knowledge and help with diagnosis, monitoring and tracking health issues, clinical decision making, early detection of infectious disease prevention, and rapid analysis of health hazards. The text examines a wealth of topics such as the design and development of pervasive healthcare technologies, data modeling and information management, wearable biosensors and their systems, and more. This important resource: Explores the recent trends and developments in computing through bio-sensors and its technological applications Contains a review of biosensors and sensor systems and networks for mobile health monitoring Offers an opportunity for readers to examine the concepts and future outlook of intelligence on healthcare systems incorporating biosensor applications Includes information on privacy and security issues on wireless body area network for remote healthcare monitoring Written for scientists and application developers and professionals in related fields, Intelligent Pervasive Computing Systems for Smarter Healthcare is a guide to the most recent developments in intelligent computer systems that are applicable to the healthcare industry.

A guide to intelligent decision and pervasive computing paradigms for healthcare analytics systems with a focus on the use of bio-sensorsIntelligent Pervasive Computing Systems for Smarter Healthcare describes the innovations in healthcare made possible by computing through bio-sensors. The pervasive computing paradigm offers tremendous advantages in diversified areas of healthcare research and technology. The authors--noted experts in the field--provide the state-of-the-art intelligence paradigm that enables optimization of medical assessment for a healthy, authentic, safer, and more productive environment.Today's computers are integrated through bio-sensors and generate a huge amount of information that can enhance our ability to process enormous bio-informatics data that can be transformed into meaningful medical knowledge and help with diagnosis, monitoring and tracking health issues, clinical decision making, early detection of infectious disease prevention, and rapid analysis of health hazards. The text examines a wealth of topics such as the design and development of pervasive healthcare technologies, data modeling and information management, wearable biosensors and their systems, and more. This important resource:* Explores the recent trends and developments in computing through bio-sensors and its technological applications* Contains a review of biosensors and sensor systems and networks for mobile health monitoring* Offers an opportunity for readers to examine the concepts and future outlook of intelligence on healthcare systems incorporating biosensor applications* Includes information on privacy and security issues on wireless body area network for remote healthcare monitoringWritten for scientists and application developers and professionals in related fields, Intelligent Pervasive Computing Systems for Smarter Healthcare is a guide to the most recent developments in intelligent computer systems that are applicable to the healthcare industry.

List of ContributorsChapter 1 Intelligent Sensing and Ubiquitous Systems (ISUS) for Smarter and Safer Home HealthcareRui S. Moreira, José Torres, Pedro Sobral, and Christophe SoaresChapter 2 PEMO-EC: A Pervasive Platform for ECG Signal ProcessingAngelo Brayner, José Maria Monteiro, and João Paulo MadeiroChapter 3 The Impact of Implantable Sensors in Biomedical Technology on the Future of Healthcare SystemsAshraf Darwish, Gehad Ismail Sayed, and Aboul Ella HassanienChapter 4 Social Network's Security Related to HealthcareFatna Elmendili, Habiba Chaoui, and Younes El Bouzekri El IdrissiChapter 5 Multi-Sensor Fusion for Context-Aware ApplicationsVeeramuthu Venkatesh, P. Balakrishnan, and Pethru RajChapter 6 IoT Based Noninvasive Wearable and Remote Intelligent Pervasive Healthcare Monitoring Systems for ElderlyStela Vitorino SampaioChapter 7 Pervasive Healthcare System Based on Environmental MonitoringSangeetha, A. and Amudha, T.Chapter 8 Secure Pervasive Healthcare System and Diabetes Prediction Using Heuristic AlgorithmP Pabitha and Rajalakshmi Shenbaga MoorthyChapter 9 Threshold-Based Energy Efficient Routing Protocol for Critical Data Transmission to Increase Life Time in Heterogeneous Wireless Body Area Sensor NetworkP.Deepalakshmi and V.NavyaChapter 10 Privacy and Security Issues on Wireless Body Area and IoT for Remote Healthcare MonitoringPrabha Selvaraj and Sumathi DoraikannanChapter 11 Intelligent Pervasive Computing Systems for Smarter HealthcarePadma T and Jayashree NairChapter 12 Image Analysis Using Smartphones for Medical Applications: A SurveyRajeswari, R. and Jothilakshmi, R.Chapter 13 Bounds of Spreading Rate of Virus for a Network Through an Intuitionistic Fuzzy GraphG. Deepa, B. Praba, V.M. Chandrasekaran, K. Rajakumar, and Krishnamoorthy VenkatesanChapter 14 Data Mining Techniques for the Detection of the Risk in Cardiovascular DiseasesK. Dinakaran, S. Vishnu Priya, and P. ValarmathieChapter 15 E-Health: Bio SensorsN. Ruban and A. Mary MekalaChapter 16 Anomaly Detection and Pattern Matching Algorithm for Healthcare Application: Identifying Ambulance Siren in TrafficGowtham Babu K and Sasikala RChapter 17 Detecting Diabetic Retinopathy from Retinal Images Using CUDA DEEP Neural NetworkRicky parmar, Ramanathan Lakshmanan, Swarnalatha Purushotham, and Rajkumar SoundrapandiyanChapter 18 An Energy Efficient Wireless Body Area Network Design in Health Monitoring ScenariosKannan Shanmugam and Karthik Subburathinam