Author :
Bo Zhou ; Jingyuan Cheng ; Sundholm, Mathias ; Reiss, Attila ; Wuhuang Huang ; Amft, Oliver ; Lukowicz, Paul
Abstract :
We present a novel sensor system for the support of nutrition monitoring. The system is based on smart table cloth equipped with a fine grained pressure textile matrix and a weight sensitive tablet. Unlike many other nutrition monitoring approaches, our system is unobtrusive, non privacy invasive and easily deployable in every day life. It allows the spotting and recognition of food intake related actions, such as cutting, scooping, stirring, etc., the identification of the plate/container on which the action is executed, and the tracking of the weight change in the containers. In other words, we can determine how many pieces are cut on the main dish plate, how many are taken from the side dish, how many sips are taken from the drink, how fast the food is being consumed and how much weight is taken overall. In addition, the distinction between different eating actions, such as cutting, scooping, poking, provides clues to the type of food taken and the way the meal is consumed. We have evaluated our system on 40 meals (5 subjects) in a real life living environment: for seven eating related actions (cutting, scooping, stirring, etc.), resulting in above 90% average recognition rate for person dependent cases, and spotting each action out of continuous data streams (average F1 score 87%).
Keywords :
computerised monitoring; health care; medical computing; notebook computers; ubiquitous computing; container identification; continuous data streams; cutting; dietary monitoring; eating actions; fine grained pressure textile matrix; food intake related action recognition; food intake related action spotting; healthcare; nonprivacy invasive; nutrition monitoring; pervasive computing; pervasive dining monitoring; plate identification; poking; scooping; sensor system; smart table cloth; smart table surface; stirring; weight change tracking; weight sensitive tablet; Accuracy; Containers; Force; Monitoring; Pervasive computing; Sensors; Standards; ambient intelligence; eating activity recognition; pressure sensor;