Self-Organizing Maps
Moving Out of the Lab: Deploying Pervasive Technologies in a Hospital
IEEE Pervasive Computing
A survey on wearable sensor-based systems for health monitoring and prognosis
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Detecting stress during real-world driving tasks using physiological sensors
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Information Technology in Biomedicine
WeAidU-a decision support system for myocardial perfusion images using artificial neural networks
Artificial Intelligence in Medicine
| Hi-index | 0.24 |
Developments in computational techniques including clinical decision support systems, information processing, wireless communication and data mining hold new premises in Personal Health Systems. Pervasive Healthcare system architecture finds today an effective application and represents in perspective a real technological breakthrough promoting a paradigm shift from diagnosis and treatment of patients based on symptoms to diagnosis and treatment based on risk assessment. Such architectures must be able to collect and manage a large quantity of data supporting the physicians in their decision process through a continuous pervasive remote monitoring model aimed to enhance the understanding of the dynamic disease evolution and personal risk. In this work an automatic simple, compact, wireless, personalized and cost efficient pervasive architecture for the evaluation of the stress state of individual subjects suitable for prolonged stress monitoring during normal activity is described. A novel integrated processing approach based on an autoregressive model, artificial neural networks and fuzzy logic modeling allows stress conditions to be automatically identified with a mobile setting analysing features of the electrocardiographic signals and human motion. The performances of the reported architecture were assessed in terms of classification of stress conditions.