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dc.contributor.editorBuisseret, Fabien
dc.contributor.editorDierick, Frédéric
dc.contributor.editorVan der Perre, Liesbet
dc.date.accessioned2022-12-06T16:13:16Z
dc.date.available2022-12-06T16:13:16Z
dc.date.issued2022
dc.identifierONIX_20221206_9783036558608_113
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/94590
dc.description.abstractRecent advances in electronics have led to sensors whose sizes and weights are such that they can be placed on living systems without impairing their natural motion and habits. They may be worn on the body as accessories or as part of the clothing and enable personalized mobile information processing. Wearable sensors open the way for a nonintrusive and continuous monitoring of body orientation, movements, and various physiological parameters during motor activities in real-life settings. Thus, they may become crucial tools not only for researchers, but also for clinicians, as they have the potential to improve diagnosis, better monitor disease development and thereby individualize treatment. Wearable sensors should obviously go unnoticed for the people wearing them and be intuitive in their installation. They should come with wireless connectivity and low-power consumption. Moreover, the electronics system should be self-calibrating and deliver correct information that is easy to interpret. Cross-platform interfaces that provide secure data storage and easy data analysis and visualization are needed.This book contains a selection of research papers presenting new results addressing the above challenges.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBG Medical equipment and techniquesen_US
dc.subject.otherinertial measurement unit
dc.subject.othermovement analysis
dc.subject.otherlong-track speed skating
dc.subject.othervalidity
dc.subject.otherIMU
dc.subject.otherprincipal component analysis
dc.subject.otherwearable
dc.subject.otherscoring
dc.subject.othercarving
dc.subject.otherbalance assessment
dc.subject.otherdata augmentation
dc.subject.othergated recurrent unit
dc.subject.otherhuman activity recognition
dc.subject.otherone-dimensional convolutional neural network
dc.subject.otherintermittent claudication
dc.subject.othervascular rehabilitation
dc.subject.other6 min walking test
dc.subject.otherfunctional walking
dc.subject.otherTUG
dc.subject.otherkinematics
dc.subject.otherfall risk
dc.subject.otherlogistic regression
dc.subject.otherelderly
dc.subject.otherinertial sensor
dc.subject.otherartificial intelligence
dc.subject.othersupervised machine learning
dc.subject.otherhead rotation test
dc.subject.otherneck pain
dc.subject.othercerebral palsy
dc.subject.otherdystonia
dc.subject.otherchoreoathetosis
dc.subject.othermachine learning
dc.subject.otherhome-based
dc.subject.otherwearable device
dc.subject.otherMLP
dc.subject.othergesture recognition
dc.subject.otherflex sensor
dc.subject.othermodel search
dc.subject.otherneural network
dc.subject.otherinertial measurement unit—IMU
dc.subject.othermovement complexity
dc.subject.othersample entropy
dc.subject.othertrunk flexion
dc.subject.otherlow back pain
dc.subject.otherlifting technique
dc.subject.othercamera system
dc.subject.otherward clustering method
dc.subject.otherK-means clustering method
dc.subject.otherensemble clustering method
dc.subject.otherBayesian neural network
dc.subject.otherpain self-efficacy questionnaire
dc.subject.othern/a
dc.titleWearable Sensors Applied in Movement Analysis
dc.typebook
oapen.identifier.doi10.3390/books978-3-0365-5859-2
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783036558608
oapen.relation.isbn9783036558592
oapen.pages154
oapen.place.publicationBasel


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