Linguistic summarization of sensor data for eldercare

Ubiquitous passive, as well as active, monitoring of elders is a growing field of research and development with the goal of allowing seniors to live safe active independent lives with minimal intrusion. Much useful information, fall detection, fall risk assessment, activity recognition, early illness detection, etc. can be inferred from the mountain of data. Healthcare must be human centric and human friendly, and so, methods to consolidate the data into linguistic summaries for enhanced communication and problem detection with elders, family and healthcare providers is essential. Long term trends can be most easily identified using summarized information. This paper explores the soft computing methodology of protoforms to produce linguistic summaries of one dimensional data, motion and restlessness. The technique is demonstrated on a 15 month sensor collection for an elder participant.