Lenitra M. Durham

A context-management framework for telemedicine: an emergency medicine case study

Patient care can be intense and stressful, especially in emergency care situations. Emergency care has two parts, field care by a paramedic and in-hospital care. Paramedics often consult with physicians before the patient reaches the hospital. To do this effectively, they must convey the patients condition rapidly and effectively. Upon hospital arrival they must also transfer as much patient data as possible to ensure continuation of care. In this paper, we present a context-management framework for telemedicine that is designed to capture sensor data for transfer to a remote location. We further describe an application developed on top of the framework for emergency medicine. We examine design considerations for the application based on collaboration with medical personnel. Finally, we present technical results obtained from use of the technology in simulated emergency scenarios.

Platform Support for Autonomic Computing: a Research Vehicle

Vast majority of autonomic frameworks and agents reported in literature seem to be implemented in higher layers of software. This paper describes a research project focused on exploring the nature and value of providing platform support for autonomic computing. We postulate that autonomic systems can provide increased manageability and higher availability by executing in an autonomous execution environment and by having rich sensory information at their disposal. We describe the system architecture and prototype environment.

Experiences with context management in emergency medicine

In emergency medicine, patient care is intense and stressful, often requiring paramedics to consult with remote physicians to convey the patients condition. We present a framework for context-management in telemedicine developed in collaboration between engineers, physicians, and paramedics. We describe a mobile platform and embedded wireless sensors to capture physiological and audio context into a comprehensive patient record, accessible locally and remotely. We describe a first evaluation of this technology by trained paramedics in simulated scenarios and evaluate key aspects of system performance. Early results suggest that wireless sensing can provide reliable and low latency data both locally and to remote physicians. In addition, audio context capture is a promising approach to capturing a comprehensive patient record, with a low rate of medically important errors.