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Open AccessArticle

Development of a Data Logger for Capturing Human-Machine Interaction in Wheelchair Head-Foot Steering Sensor System in Dyskinetic Cerebral Palsy

1
KU Leuven, Bruges Campus, Department of Computer Science, Mechatronics Research Group, Spoorwegstraat 12, 8200 Bruges, Belgium
2
KU Leuven, Department of Biosystems, Division of Animal and Human Health Engineering, Measure, Model and Manage Bioresponse (M3-BIORES), Kasteelpark Arenberg 30, 3001 Leuven, Belgium
3
KU Leuven, Bruges Campus, Department of Rehabilitation Sciences, Research Group for Neurorehabilitation, Spoorwegstraat 12, 8200 Bruges, Belgium
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(24), 5404; https://doi.org/10.3390/s19245404
Received: 29 October 2019 / Revised: 1 December 2019 / Accepted: 5 December 2019 / Published: 7 December 2019
(This article belongs to the Special Issue Sensors for Biomechanics Application)
The use of data logging systems for capturing wheelchair and user behavior has increased rapidly over the past few years. Wheelchairs ensure more independent mobility and better quality of life for people with motor disabilities. Especially, for people with complex movement disorders, such as dyskinetic cerebral palsy (DCP) who lack the ability to walk or to handle objects, wheelchairs offer a means of integration into daily life. The mobility of DCP patients is based on a head-foot wheelchair steering system. In this work, a data logging system is proposed to capture data from human-wheelchair interaction for the head-foot steering system. Additionally, the data logger provides an interface to multiple Inertial Measurement Units (IMUs) placed on the body of the wheelchair user. The system provides accurate and real-time information from head-foot navigation system pressure sensors on the wheelchair during driving. This system was used as a tool to obtain further insights into wheelchair control and steering behavior of people diagnosed with DCP in comparison with a healthy subject. View Full-Text
Keywords: data logging; human-wheelchair interaction; inertial measurement units; electric-powered wheelchair; time alignment; signal synchronization; dyskinetic cerebral palsy; dystonia; choreoathetosis; clinical tool data logging; human-wheelchair interaction; inertial measurement units; electric-powered wheelchair; time alignment; signal synchronization; dyskinetic cerebral palsy; dystonia; choreoathetosis; clinical tool
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Gakopoulos, S.; Nica, I.G.; Bekteshi, S.; Aerts, J.-M.; Monbaliu, E.; Hallez, H. Development of a Data Logger for Capturing Human-Machine Interaction in Wheelchair Head-Foot Steering Sensor System in Dyskinetic Cerebral Palsy. Sensors 2019, 19, 5404.

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