WP1 dealt with development and implementation of new features of Sentab, based on the core platform. Within the first 12 months of the project, Sentab completed the definition and implementation of the system architecture in view of scalability, security and data interchange (D1.1.). Server side implementation was finalized, API-s defined for front-end integration. Database structures were put in place to host data repositories, including transactional databases, analytical databases, file and media repositories (D1.2.). During the second reporting period, statistical engine implementation was finalized, with relevant User Interface development (D1.3.). Memory agility testing (D1.4) with end users as well as physical tests (D1.5.) were carried out and relevant studies were published.
WP2 focused on testing and optimization of the deliverables coming out from WP1. WP2 ended with the fully functional Sentab system that the company is able to demonstrate and disseminate to the product to end-users and important stakeholders at various events, dedicated road-show and through other channels. During the first 12 months into the project, we ensured robustness of data flows stemming from the administration, use and collected data from Sentab system, to build for big data scalability. During the second project period, the functional blocks built in WP1 were tested and relevant test report released (D2.2.). Based on the developed Sentab TV system, we also carried out a number of further studies measuring the effects of media on older adults mood and emotions (D2.3) short term and long term memory dynamics in older age (D2.4.) and the effect of loneliness on older adults.
Under WP3, we developed a commercialization plan (D4.1) and updated it by the end of the project. A significant dissemination efforts have been performed, whereby Sentab has introduced the project and its product at Care Forums, Web Summit, CeBIT, The Venture global competition, in media, Arctic15, Latitude59, Health behavior conferences etc. We have also directly approached end user organizations such as local councils in UK, cable companies, senior communities etc.
As a result of the project, the company has developed a behavoural analytics engine that analyses users physical activity levels, cognitive agility and social activity. Additionally, the company has developed a 4 platform solution that socially connects older adults to peers, family, caregivers and service providers. All the developed hardware and software modules are part of the final product, which was introduced to the marketplace.
