202
A. Henaien et al.
Ubiquitous Monitoring and Patient Tracking: is an optional functionalities provide an instantly monitoring and tracking that may be used for the
already mentioned functionalities.
Patient Reminder: is an optional but highly recommended functionality. It
is hard to imagine a healthcare system that is not providing a patient reminder
about medical appointment, daily medical operations, etc. Aligned with the list
of proposed functionalities, Fig. 2 is the generic architecture for a combined ML
and ontology based situation awareness framework for clinical monitoring and
healthcare decision supporting. The main contribution in this architecture is the
dynamic updates of its knowledge base in its objective and subjective parts.
Our system is a multi modal user interaction application, i.e. different smart
devices are available in the patient’s environment or in the patient’s body. The
data is collected from different devices like: body sensors worn by the user,
ambient sensors surrounding the user or smart devices, as phone, tablet, etc.
Body sensors are used to capture the health profile of the patient, viz, vital
signs, motion, location, etc. Ambient sensor reflect an image of the patient’s
environment, viz, ambient temperature, lightness, existence of a caregiver, etc.
Smart devices are basically used to allow the communication between the user
and the system and between users, viz sending an alert to user about a patient’s
situation, monitoring a patient, etc. The architecture of the proposed system is
layered and detailed in the following:
Active and Assisted Living Sensors Layer: contains all smart devices
including the set of wearable and nearable sensors related directly to the user,
his body and his environment. Its role is collecting data for a complete holistic health profile for each patient: health data, ambient data, location, motion,
personal information, etc.
Networking and Communication Layer: a set of networking device allowing
the communication between the different physical elements and the connection
of those elements to the internet. Ontological model based Data Layer: it
contains the set of the collected (current and previous) data and the ontology
used in this system.
Multi-modal Interactions Application Layer: is the implementation of all
the functionalities of the system providing all the services for ubiquitous and
continuous medical monitoring and supporting the multi-modal interaction.
Semantic Rules Based Knowledge Layer: it is composed by the objective
and the subjective knowledge. It is playing a fundamental role in our system since
it contains the prediction component, i.e. prevention and detection of emergency
cases and alert management.
A. Henaien et al.
Ubiquitous Monitoring and Patient Tracking: is an optional functionalities provide an instantly monitoring and tracking that may be used for the
already mentioned functionalities.
Patient Reminder: is an optional but highly recommended functionality. It
is hard to imagine a healthcare system that is not providing a patient reminder
about medical appointment, daily medical operations, etc. Aligned with the list
of proposed functionalities, Fig. 2 is the generic architecture for a combined ML
and ontology based situation awareness framework for clinical monitoring and
healthcare decision supporting. The main contribution in this architecture is the
dynamic updates of its knowledge base in its objective and subjective parts.
Our system is a multi modal user interaction application, i.e. different smart
devices are available in the patient’s environment or in the patient’s body. The
data is collected from different devices like: body sensors worn by the user,
ambient sensors surrounding the user or smart devices, as phone, tablet, etc.
Body sensors are used to capture the health profile of the patient, viz, vital
signs, motion, location, etc. Ambient sensor reflect an image of the patient’s
environment, viz, ambient temperature, lightness, existence of a caregiver, etc.
Smart devices are basically used to allow the communication between the user
and the system and between users, viz sending an alert to user about a patient’s
situation, monitoring a patient, etc. The architecture of the proposed system is
layered and detailed in the following:
Active and Assisted Living Sensors Layer: contains all smart devices
including the set of wearable and nearable sensors related directly to the user,
his body and his environment. Its role is collecting data for a complete holistic health profile for each patient: health data, ambient data, location, motion,
personal information, etc.
Networking and Communication Layer: a set of networking device allowing
the communication between the different physical elements and the connection
of those elements to the internet. Ontological model based Data Layer: it
contains the set of the collected (current and previous) data and the ontology
used in this system.
Multi-modal Interactions Application Layer: is the implementation of all
the functionalities of the system providing all the services for ubiquitous and
continuous medical monitoring and supporting the multi-modal interaction.
Semantic Rules Based Knowledge Layer: it is composed by the objective
and the subjective knowledge. It is playing a fundamental role in our system since
it contains the prediction component, i.e. prevention and detection of emergency
cases and alert management.