Kristof Van Laerhoven

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Mobile information appliances are increasingly used in numerous different situations and locations, setting new requirements to their interaction methods. When the user's situation, place or activity changes, the functionality of the device should adapt to these changes. In this work we propose a layered real-time architecture for this kind of context-aware(More)
The manual assessment of activities of daily living (ADLs) is a fundamental problem in elderly care. The use of miniature sensors placed in the environment or worn by a person has great potential in effective and unobtrusive long term monitoring and recognition of ADLs. This paper presents an effective and unobtrusive activity recognition system based on(More)
If a wearable device can register what the wearer is currently doing, it can anticipate and adjust its behavior to avoid redundant interaction with the user. However, the relevance and properties of the activities that should be recognized depend on both the application and the user. This requires an adaptive recognition of the activities where the user,(More)
In recent years research on human activity recognition using wearable sensors has enabled to achieve impressive results on real-world data. However, the most successful activity recognition algorithms require substantial amounts of labeled training data. The generation of this data is not only tedious and error prone but also limits the applicability and(More)
Load sensing is a mature and robust technology widely applied in process control. In this paper we consider the use of load sensing in everyday environments as an approach to acquisition of contextual information in ubiquitous computing applications. Since weight is an intrinsic property of all physical objects, load sensing is an intriguing concept on the(More)
Research in classifying and recognizing complex concepts has been directing its focus increasingly on distributed sensing using a large amount of sensors. The colossal amount of sensor data often obstructs traditional algorithms in centralized approaches, where all sensor data is directed to one central location to be processed. Spreading the processing of(More)
Much research has been conducted that uses sensorbased modules with dedicated software to automatically distinguish the user’s situation or context. The best results were obtained when powerful sensors (such as cameras or GPS systems) and/or sensor-specific algorithms (like sound analysis) were applied. A somewhat new approach is to replace the one smart(More)
The last decade has witnessed a surge of interest in new sensing and monitoring devices for healthcare, with implantable in vivo monitoring and intervention devices being key developments in this area. Permanent implants combined with wearable monitoring devices could provide continuous assessment of critical physiological parameters for identifying(More)
Inspired by perception in biological systems, distribution of a massive amount of simple sensing devices is gaining more support in detection applications. A focus on fusion of sensor signals instead of strong analysis algorithms, and a scheme to distribute sensors, results in new issues. Especially in wearable computing, where sensor data continuously(More)