Biography
Biography: Christl Lauterbach
Abstract
The described sensor floor is a textile-based large-area sensor system, which is installed as an underlay beneath the flooring. It detects people moving across the floor, calculates their trajectories and distinguishes between foot steps and a fall. The use of capacitive proximity sensing instead of pressure sensing gives high flexibility in floor design: even non-elastic flooring, like laminate parquet or tiles are suitable. The installed system is invisible and unobtrusive compared to camera systems. The SensFloor system enables a variety of different applications in the domain of ambient assisted living (AAL) like fall detection, activity monitoring, energy savings, control of automatic doors, intrusion alarm and access control. Presence detection and human movement tracking provide valuable data for Internet of things (IoT) scenarios like i.e. behavioral analysis in retail, workspace, living or healthcare. For example, it allows care organizations to optimize their workflows and improve quality of care. In future, artificial intelligence will provide means to evaluate the health status of people walking on the floor. The proposed processing scheme is able to extract behavioral information from the sensor data, which is fed into a learning algorithm that internally represents typical patterns, and outputs a measure for the divergence of current behavior from typical behavior. Gait pattern analysis by SensFloor provides objective data for medical diagnosis by medical experts like neurologists or physiotherapists. Gait parameters like walking speed, step length, and straightness are important factors for the health status of patients. Regular assessments during the treatment indicate the success of medication and rehabilitation.