A Synergistic Co-operative Framework of Health Diagnostic Systems for People with Disabilities and the Elderly: A Case Study

摘要

Millions of people worldwide have (or will due to aging) experienced some kind of unexpected disability throughout their lives. For this population health care costs increase, quality of life and productivity decline, and in many cases family members serve as primary care assistants. Early detection and diagnosis of critical health changes could enable prevention of most of these problems, saving billions of dollars annually (Newsweek, 2006 - "Fixing the American Hospital") Early detection, however, requires continual vigilance. Due to the nature of their conditions or the lack of training and experience, many among this population are patients of either disinclined or unable to detect and report the critical observations that could make a difference. A common solution is for health care professionals to monitor patients directly or via relatively crude patient data collection devices; however, that solution does not scale to large populations. New generation of inexpensive, unobtrusive wearable/implanted devices automatically detect critical changes on their health condition. These devices will not be simple data collection appliances, nor will they only report variations from sampled population norms. Rather, they will learn individual user baselines and employ advanced detection and diagnostics to discover problems autonomously and signal medical professionals for further assistance. These wearable/implanted systems will be engineered to integrate seamlessly both with portable equipment carried by first-responders and with fixed-location systems installed in hospitals. In addition to providing advanced detection in field, our devices will continually capture data, organize it into customized patient and condition models, and communicate each patient's unique information to first-responders and hospital personnel. This paper describes the fundamental steps for the systematic development and cooperation of three layers of health diagnosis systems. These explorations will result in new fundamental knowledge and catalyze a revolution in low-cost, high-reliability, ubiquitously deployable automated health detection and diagnostic equipment.