The paper presents an optimized multimodal biometric system for identification applications. This solution is based on innovative and computational-efficient biometric data hierarchical classifiers (with detection and discrimination stages) and also with a post-classification fusion. The detection-based classification is very suitable for applications with several security levels in which the end-users have various authorization degrees. The proposed solution supports an optimal trade-off between the identification accuracy and the computational complexity, which is important for the medium-and large-scale identification biometric applications.
The paper proposes an approach for behavioural recognition in which the individual conditions are recognized using a multimodal analysis method. This approach is an extension of our previously defined multimodal analysis method for biometrics; in this case the target application is the accurate recognition of human behaviour in smart home environments, with main focus in the home tele-assistance integrated services for elderly people. The proposed multimodal analysis method uses a hierarchical approach for data classification together with a fusion rule to combine the matching scores for several behavioural patterns. The approach novelty is given by the hierarchical classification design which provides an optimal performance-cost trade-off for the behavioural recognition system. This optimization could be done at runtime in practical applications.
The paper presents an application of mHealtha mobile app for remote health monitoring, that facilitates using a Bluetooth enabled health measuring device and synchronizing health data to a health care services provider's web portal. The mobile app uses a public API that allows its integration in a complex platform for home care providers, allowing health monitoring of large groups of patients, monitoring vital functions, including body temperature, respiratory rate and arterial blood oxygen saturation, relevant in monitoring COVID-19 patients.
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