Adaptive Modeling of a User's Daily Life with a Wearable Sensor Network

Abstract

In an environment where the contexts of users are complex and the degree of freedom of user activity is very high, such as in daily life, several factors need to be considered for constructing user models. Such a model should include changes in the meanings of activities that reflect the user's situation both temporally and individually. In this paper we propose a novel approach for personalizing the user model and adapting it to individual circumstances with a wearable sensor network. We also describe the process for determining the repetitive activities of a user by using incremental clustering and Bayesian network. We show experimental results for an adaptive user model based on a real wearable sensor platform. Multimedia data of user experience are acquired from the multimodal sensors, and processed to metadata that have meanings.

A Service-Oriented User Interaction Analysis Framework Supporting Adaptive Applications

“…Analysing the UDI enables better understanding of a user [1] and provides the basis for personalized services [14], [13]. The UDI can, therefore, be a valuable basis for many applications such as recommender systems [10], [11], games, adaptable services [9]. They can use a user model or presence in order to change their services and systems behaviour.…”

“…The available context (at the time that the user interacts) is important in building a rich user model. Several projects employ a user behavioural model in order to better understand, and provide adaptive and personalized services, to a user [9], [10], [11], [12]. For instance, a software system, MoodScope [13], infers the user's mood based on their smart-phone usage.…”

Multimodal User Guide for Experience Sharing Based on Activity Modeling

“…The entropy-based Quality Threshold clustering method (QT clustering) [5][8] is adaptable to cluster this type of data. Since activity modeling operates autonomously, the system has no information about the number of clusters and exact range of clusters.…”

“…Recent location based systems have had the similar ideas and goals as our system [3] [4]. Many researchers have attempted to model the daily life of a person [5] [6] and discover their abnormal activities [7]. Despite these previous works, this paper presents two contributions.…”

Development of a secure body area network for a wearable physiological monitoring system using a PSoC processor

“…The processed data are sent to a monitoring station using wireless transmission. The primary advantage of such a system is the real-time continuous monitoring of the signals by clinicians in the monitoring station, with activation of alarms during critical conditions [4][5][6][7][8][9][10][11]. It is essential to monitor the physiological signals continuously, so that immediate treatment can be provided during emergency conditions.…”