Snizhko Ye.M., Palamarchuk Yu.A., Botsva T.O.
Dnipropetrovsk national university named after
O.Honchar
WIRELESS SENSOR NETWORK SOLUTIONS FOR
HEALTHCARE
Wireless
sensor networks (WSN) are being widely applied in medical domains. Wearable WSN
nodes work for constant monitoring of vital signs, gathering and transmision of
physiological data.
Continuous
health monitoring with wearable or clothing-embedded transducers and
implantable body sensor networks will allow to detect emergency conditions.
Also, these systems provide useful methods to remotely acquire and monitor the
physiological signals without interruption of the patient’s normal life [1].
Although traditional hospital systems allow continuous monitoring of patient
vital signs, these systems require the sensors to be placed bedside monitors
and limit the patient`s free moving to his bed. But now, there is no relation
between the sensors and the bedside equipment due to the wireless devices and
wireless networks. In most cases, health monitoring will be done by
infrastructure-oriented wireless networks. But, the coverage of the
infrastructure-oriented networks changes with time or location. Sometimes, the
coverage of wireless network is not available, or the coverage is available but
we cannot access to the network due to a lack of available bandwidth. So, with
these problems and restrictions, continuous health monitoring is not possible
and emergency signals may not be transmitted from a patient to healthcare
providers.[2] As a possible example, we can solve the problem of continuous
health monitoring by ad hoc wireless network architecture that can transmit
vital signs over a short-range.
In an emergency or disaster scenario, the same solution
would help clinical staff to more effectively care for large numbers of
casualties. Medics could receive immediate notifications on any critical changes
in patient condition, such as respiratory failure or cardiac arrest. Wireless
sensors could possibly replace existing wired telemetry systems for many
specific clinical applications, such as rehabilitation or long-term out-ward
monitoring.
Meeting
the potential of WSNs inhealthcare requires addressing many of technical
challenges. These challenges include more than just the resource limitations
that all WSNs have: network capacity, processing, battery life and memory
constraints. Specifically, unlike applications in other domains, healthcare
applications must meet strict requirements on system reliability, quality of
service, and particularly privacy and security.[3]
Most
medical sensors have traditionally been too costly and complex to be used
outside of clinical environments. But recent inventions in microelectronics and
computing have made medical sensing available to individuals at their living
spaces. Medical sensors have become interconnected with other devices. Earlier
medical sensors were isolated modules with integrated user interfaces for
displaying their measurements. Now sensors became capable of interfacing to
external devices via wired interfaces such as RS 232, USB, and Ethernet. More
recently, medical sensors have incorporated wireless connections, both short
range, such as Bluetooth, Zigbee, and near-field radios to communicate
wirelessly to nearby computers, smartphones, and long range, such as WiFi to communicate
directly with cloud computing services.
Critical
points in WSNs for clinical use
Interoperability. As a result of multiple types of nodes (i.e.
different types of physiological data require
different sensing nodes, alocated on different areas of human body) present in
the system, communication between devices — motes, mplanted medical devices etc.
- may occupy multiple bands and use different protocols. The WSN designed for
out-ward care must provide middleware interoperability between disparate
devices, and support unique relationships among devices, such as implants and
their outside controllers.
Real-time data gathering and analysis. The rate of collection of data is higher in
this type of network than in WSNs used, for example, in environmental studies.
Efficient communication and processing become critical. Event ordering,
time-stamping, synchronization, and quick response in emergency situations
will required here as in any healthcare
IT product.
Robustness. Sensors and other devices must operate with enough
reliability to yield
high-confidence data suitable for medical diagnosis
and treatment. Since the out-ward care network will not be maintained within a
controlled clinic, devices must have long enougth time of autonomous work.
Patient and object tracking. Tracking can be considered at three levels:
symbolic (e.g., ward or X-Ray Lab); geographical (GPS coordinates);
relational/associational. It is complicated by the presence of multiple
patients, periodical leaving the network zone.
Multi-modal interconnection and energy
conservation. Limited
computational and radio communication capabilities require algorithms with
energy-aware communication. Heterogeneous devices will be on very different
duty-cycles, from always-on wired-power units to tiny, wearable units, making calculation
of comunication time-range a difficult algorithm task.
Multi-level data processing. Data may be gathered at
multiple levels, from simple on-body filtering to compression in storage nodes.
Embedded real-time databases store data of interest and allow to query them.
Privacy and security. Data collected by the network is sensitive, and personnel
access issues are not always clear from the very first sight. Data must be
available to any involved doctor during emergencies, but all access attempts
should be trailed. WSN should not “leak” information when even a fact that data
are obtained may violate patient's privacy. When dealing with an out-ward
monitoring system, patients should have a read-only access to their
physiological data to avoid fraud.
References:
1. Carl Falcon.
Wireless medical devices: Satisfying radio requirements. Medical Device &
Diagnostic Industry, Sept.2004.
2. J. A. Stankovic
and others. Wireless Sensor Networks for In-Home Healthcare: Potential and
Challenges
3. JeongGil Ko, Chenyang Lu, Mani B. Srivastava,John A. Stankovic. Wireless Sensor Networks for Healthcare - Proceedings of the IEEE, ol. 98, No. 11, Nov. 2010