Authors:
Bart Klaassen
1
;
Bert-Jan van Beijnum
1
;
Marcel Weusthof
1
;
Dennis Hofs
2
;
Fokke van Meulen
1
;
Henk Luinge
3
;
Federico Lorussi
4
;
Hermie Hermens
5
and
Peter Veltink
1
Affiliations:
1
University of Twente, Netherlands
;
2
Roessingh Research and Development B.V., Netherlands
;
3
Xsens Technologies B.V, Netherlands
;
4
University of Pisa, Italy
;
5
University of Twente and Roessingh Research and Development B.V., Netherlands
Keyword(s):
Telemedicine, Architecture, Sensing System, Stroke, Home Environment, Daily-life Activities, Monitoring, Performance, Capacity.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Signal Processing
;
Clinical Problems and Applications
;
Data Engineering
;
Data Management and Quality
;
Data Manipulation
;
Data Visualization
;
Decision Support Systems
;
Devices
;
Distributed and Mobile Software Systems
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Human-Computer Interaction
;
Mobile Technologies
;
Mobile Technologies for Healthcare Applications
;
Motion Tracking Technologies
;
Neural Rehabilitation
;
Neurotechnology, Electronics and Informatics
;
Physiological Computing Systems
;
Physiological Modeling
;
Sensor Networks
;
Sensors-Based Applications
;
Software Engineering
;
Telemedicine
;
Wearable Sensors and Systems
Abstract:
Currently, the changes of functional capacity and performance of stroke patients after returning home from a rehabilitation hospital is unknown for a physician, having no objective information about the intensity and quality of a patient's daily-life activities. Therefore, there is a need to develop and validate an unobtrusive and modular system for objectively monitoring the stroke patient's upper and lower extremity motor function in daily-life activities and in home training. This is the main goal of the European FP7 project named “INTERACTION”. A complete sensing system is developed, whereby Inertial Measurement Units (IMU), Knitted Piezoresistive Fabric (KPF) goniometers, KPF strain sensors, EMG electrodes and force sensors are integrated into a modular sensor suit designed for stroke patients. In this paper, we describe the systems architecture. Data from the sensors are captured wirelessly and stored in a remote secure database for later access and processing via portal techno
logy. In collaboration with clinicians and engineers, clinical outcome measures were defined and the question of how to present the data on the web portal was addressed. The first implementation of the complete system includes a basic version of all components and is currently being extended to include all sensors within the INTERACTION system.
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