Research

LOPSI is a research group specialized in the creation of technological solutions for intelligent environments, which can perceive the presence of people and offer them useful location-based services. We perform both basic research and technological development in this area.

CURRENT RESEARCH LINES

We have two main lines of research :

1.  Localization of people in indoor and outdoor GNSS-challenging areas. The main focus of the LOPSI group is the design and development of Local Positioning Systems (LPS) capable of locating, tracking, and guiding people in indoor environments, where GPS receivers are not operative or reliable. Our current methodological approach to indoor localization is the Bayesian combination of ranging information obtained from radiofrequency emitters (such as wifi access points, Bluetooth nodes or dedicated RF beacons) and dead reckoning from user-wearable inertial sensors (foot-mounted or present in a smartphone). Other information, such as provided by signals of opportunity, maps of the environment, etc, can be integrated flexibly and as available. Our technology is aimed for deployment in portable devices like smartphones. Physical location of users can be complemented by information about their status, such as provided by wearable physiological sensors. We are currently working with wearable motion units with integrated electromyographic and optical pulse sensors to perform activity recognition. The ultimate goal is to improve the performance of Assistance Systems and Health Monitoring applications.  More info.

2.  Human motion analysis based on gait analysis using inertial sensors. In recent years the LOPSI group has been involved in several research projects oriented to gait analysis, especially in elderly people where it is an useful tool for the diagnosis and detection of pathologies as frailty or fall risk. Our work is focused on the use of inertial sensors placed on the foot, including from the design of the device, such as developing algorithms for step detection and parameter extraction. In addition to the development of analytics applications for patients/physicians or the use of AI algorithms for patient group classification from gait data.

OTHERS RESEARCH LINES