Showing papers by "Jamie A. Ward published in 2004"
01 Dec 2004
TL;DR: The AMON system includes continuous collection and evaluation of multiple vital signs, intelligent multiparameter medical emergency detection, and a cellular connection to a medical center, and is validated by a medical study with a set of 33 subjects.
Abstract: This paper describes an advanced care and alert portable telemedical monitor (AMON), a wearable medical monitoring and alert system targeting high-risk cardiac/respiratory patients. The system includes continuous collection and evaluation of multiple vital signs, intelligent multiparameter medical emergency detection, and a cellular connection to a medical center. By integrating the whole system in an unobtrusive, wrist-worn enclosure and applying aggressive low-power design techniques, continuous long-term monitoring can be performed without interfering with the patients' everyday activities and without restricting their mobility. In the first two and a half years of this EU IST sponsored project, the AMON consortium has designed, implemented, and tested the described wrist-worn device, a communication link, and a comprehensive medical center software package. The performance of the system has been validated by a medical study with a set of 33 subjects. The paper describes the main concepts behind the AMON system and presents details of the individual subsystems and solutions as well as the results of the medical validation.
747 citations
21 Apr 2004
TL;DR: In this article, the authors presented a technique to automatically track the progress of maintenance or assembly tasks using body worn sensors based on a novel way of combining data from accelerometers with simple frequency matching sound classification.
Abstract: The paper presents a technique to automatically track the progress of maintenance or assembly tasks using body worn sensors. The technique is based on a novel way of combining data from accelerometers with simple frequency matching sound classification. This includes the intensity analysis of signals from microphones at different body locations to correlate environmental sounds with user activity. To evaluate our method we apply it to activities in a wood shop. On a simulated assembly task our system can successfully segment and identify most shop activities in a continuous data stream with zero false positives and 84.4% accuracy.
275 citations
01 Jan 2004
TL;DR: Two data sets are presented which are recorded to evaluate the usefulness of sensors and to develop, test and improve the recognition strategies with respect to two specific recognition tasks.
Abstract: . The use of body-worn sensors for recognizing a person’s context has gained much popularity recently. For the development of suitable context recognition approaches and their evaluation, real-world data is essential. In this paper, we present two data sets which we recorded to evaluate the usefulness of sensors and to develop, test and improve our recognition strategies with respect to two specific recognition tasks.
8 citations