ABSTRACT:
Gait
monitoring through the Internet of Things (IoT) is able to provide an overall
assessment of daily living. All existing systems for predicting abnormality in
gait mainly consider the gait related parameters. Their accuracy is limited
because consequences due to injuries are significantly affected by different
events in the gait. The objective of this study is to present a multisensory
system that investigates walking patterns to predict a cautious gait in stroke
patient. For this study, a smartphone built-in sensor and an IoT-shoe with a
WiFi communication module is used to discreetly monitor insole pressure and
accelerations of the patient’s motion. To the best of our knowledge, we are the
first to use the gait spatiotemporal parameters implemented in smartphones to
predict a cautious gait in a stroke patient. The proposed system can warn the
user about their abnormal gait and possibly save them from forthcoming injuries
from fear of falling.
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