Database Reference
In-Depth Information
logical information collected from body sensors and smart environments,
can dramatically transform both individual as well as community health.
The different healthcare applications in non-clinical settings that we
address in this chapter may be broadly categorized into:
Chronic Disease and Wellness Management Applications
that facilitate preventive care and chronic disease management
and treatment, along with user programs to motivate happy and
healthy behavior.
Activity Monitoring Applications
that capture activities of
daily living especially for elderly users, in remote healthcare set-
tings
Reality Mining applied to Healthcare
that applies machine
learning techniques to data typically sensed with mobile phones to
study complex social systems, including the study of the distribu-
tion and patterns of health-events, health-characteristics and their
causes or influences in specific populations.
4.1 Chronic Disease and Wellness Management
Several researchers have reported on remote patient monitoring sys-
tems with sensor mining capabilities for chronic disease and wellness
management. In [28] the authors report on an interesting prototype
streaming system called T2, designed to monitor mobile patient ECGs
and accelerometers data streams, remotely. The application reports pe-
riods of elevated heart rate to the clinician. The accelerometer is used
to detect periods of physical activity during which ECG data is filtered
to account for different activity levels.
Holter monitors constitute another class of sensors that are worn by a
patient continuously for several days to provide a complete ECG reading
over that time. The analysis of the recorded data is done oine to detect
cardiac conditions of interest. The use of Holter Monitors is expanding
as researchers seek ways to detect conditions and treat patients who
have multiple diseases. In [68], researchers record both glucose and
cardiac readings in diabetes patient with cardiac conditions to detect
correlations between high glucose readings and ECG patterns.
A remote monitoring platform called Personal Care Connect (PCC)
[69] has been extended with advanced distributed analytical capabilities.
The resulting Harmoni platform allows for the distribution of analysis
from back-end servers to remote devices located near the patient. In
addition, the Harmoni platform allows for the distribution and instan-
tiation of monitoring rules, triggered by changes in the context of the
