Geintra

Global aging is a social triumph, but also a challenge for healthcare systems. The advent and evolution of decline in individuals is difficult to detect on-time just from sporadic medical consultations, so it would be very valuable to have technological means for unobtrusive continuous tracing of functional changes or deficits. A great effort has been made during the last years on this topic and different technological solutions exist for assessing physical and mental decline and providing support, but they need to be more reliable, more portable, accessible, affordable and easy-to-use. The main objective of the INDRI Project is providing novel sensory system solutions, including all the electronic processing levels and data communication, storage, analysis and presentation, to detect the localization and some physical and physiological states of monitored persons (e. g. movements of body’s parts, tremors detection, the motion of the person, etc.) and behavioral states of people (e. g. repetition of routines in activities of the daily living). A big technological challenge of the project is to customize the developed aids to a diversity of situations: for example, in assisted and non-assisted environments; for short- and long-term; and for collaborating and non-collaborating persons. The development of such successful human tracing systems involves the customization of the sensors and data management layers to a well-defined application. Thus, the execution of the project requires scientific and technological advances at different stages: a) global approach to applications of digital tracing of human activity, from the base technologies to the final implementation; b) design of new sensory systems and combination with off-the-shelf ones for localization and physical and physiological data acquisition, considering, as a first case,  the combinations of sensors installed in the environment, as homes or nursing homes, not requiring the use of any wearable (radar or TOF cameras, energy consumption monitoring, RF tomography) and, as a second case, the design and inclusion of advanced data acquisition systems using wearable sensors (smart-bands with BLE signaling, smartphones with RTK-GNSS, ultrasound, UWB and IR ranging tags, inertial sensors, smart textiles, etc.); c) fusion methods for integrating the sensor information from different sensory systems and with signals of opportunity, map data, etc, increasing the availability, accuracy, and trust in the estimates generated by the positioning and tracing system, as well as achieving seamless transitions between different scenarios, in which real-time operation, computation in de edge, use of IoT protocols and storage are required; d) analysis of all the sources or information (with state of the art pattern recognition and classification methodologies) to infer and produce human understandable labels about the short- and long- term user’s activity or behavior; and e) development of two applications or case studies in collaboration with medical personnel: 1) study of the quality of human motion (gait, displacements, etc.) for diagnosis or rehabilitation purposes in short- or large-scale displacements at home and outer spaces, and 2) the digital tracing of daily activities and analysis of the behaviour of people, including early detection of anomalies and the onset of frailty or mental impairments, for both collaborative and non-collaborative users and allowing several degrees of supervision.

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