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Assistive environments are entering our homes faster than ever. However, there are still various barriers to be broken. One of the crucial points is a personalization of offered services and integration of assistive technologies in common objects and therefore in a regular daily routine. Recognition of sleep patterns for the preliminary sleep study is one of the Health services that could be performed in an undisturbing way. This article proposes the hardware system for the measurement of bio-vital signals necessary for initial sleep study in a nonobtrusive way. The first results confirm the potential of measurement of breathing and movement signals with the proposed system.
A clinically useful system for individual continuous health data monitoring needs an architecture that takes into account all relevant medical and technical conditions. The requirements for a health app to support such a system are collected, and a vendor independent architecture is designed that allows the collection of vital data from arbitrary wearables using a smartphone. A prototypical implementation for the main scenario shows the feasibility of the approach.
Integrating tools and applications into a clinically useful system for individual continuous health data surveillance requires an architecture considering all relevant medical and technical conditions. Therefore, the requirements of an integrated system including a health app to collect and monitor sensor data to support personalized medicine are analyzed. The structure and behavior of the system are defined regarding the specific health use cases and scenarios. A vendor-independent architecture, which enables the collection of vital data from arbitrary wearables using a smartphone, is presented. The data is centrally managed and processed by attending physicians. The modular architecture allows the system to extend to new scenarios, data formats, etc. A prototypical implementation of the system shows the feasibility of the approach.