Since inclusive BCIs require to consider interface sustainability, we evaluated different ergonomic aspects of the interaction of disabled users with a character-speller (goal: word spelling) and an icon-speller (goal: operating a real smart home). We found the first one as more sustainable in terms of accuracy and cognitive effort.
This paper introduces technical solutions devised to support the Deployment Site - Regione Emilia Romagna (DS-RER) of the ACTIVAGE project. The ACTIVAGE project aims at promoting IoT (Internet of Things)-based solutions for Active and Healthy ageing. DS-RER focuses on improving continuity of care for older adults (65+) suffering from aftereffects of a stroke event. A Wireless Sensor Kit based on Wi-Fi connectivity was suitably engineered and realized to monitor behavioral aspects, possibly relevant to health and wellbeing assessment. This includes bed/rests patterns, toilet usage, room presence and many others. Besides hardware design and validation, cloud-based analytics services are introduced, suitable for automatic extraction of relevant information (trends and anomalies) from raw sensor data streams. The approach is general and applicable to a wider range of use cases; however, for readability’s sake, two simple cases are analyzed, related to bed and toilet usage patterns. In particular, a regression framework is introduced, suitable for detecting trends (long and short-term) and labeling anomalies. A methodology for assessing multi-modal daily behavioral profiles is introduced, based on unsupervised clustering techniques. The proposed framework has been successfully deployed at several real-users’ homes, allowing for its functional validation. Clinical effectiveness will be assessed instead through a Randomized Control Trial study, currently being carried out.
A novel home-automation scheme is presented, based on widely diffused communication protocols. Intelligent control units allows for complex services to be implemented and for integration of different services. A test application, aimed at assistive purposes, illustrates potentialities of the approach and emphasizes low cost and versatility features.
The design of an Ambient Assisted Living (AAL) aims to create better living conditions for the elderly, especially those who choose to live in their own houses, as long as possible. To this objective, AAL systems must mainly monitor the health status of the elderly through the analysis of data gathered via technologies based on sensor devices. Sensors networks produce collections of data of fine-grained nature, regarding general information such as device name, data type, data value, timestamp, but also specific one. The data analysis, due to its granularity and heterogeneity, makes very difficult to infer a clear overall view of the status of the elderly, it demands automatic tools for selecting meaningful data and mapping them in a common conceptual schema. In the last decade, ontologies became widely used tool to describe application domains and to enrich data with its meaning. In this paper, we propose an ontology-based methodology to perform semantic queries on a data repository, where records originated from networks of heterogeneous sources are stored. A semantic query is a pattern matching process that supports the recognition of specific temporal sequences of events that can be extracted from fine-grained data. In our framework a domain ontology are exploited at different levels of abstraction and the reasoning techniques are used to pre-process data for the final temporal analysis. The proposed approach is a deliverable of the ongoing AALISABETH project funded by Region Marche Government; while the software component is integrated into the AALISABETH framework
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