04172nam 2200985z- 450 991063779410332120231214132956.03-0365-5859-4(CKB)5470000001631595(oapen)https://directory.doabooks.org/handle/20.500.12854/94590(EXLCZ)99547000000163159520202212d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierWearable Sensors Applied in Movement AnalysisBaselMDPI - Multidisciplinary Digital Publishing Institute20221 electronic resource (154 p.)3-0365-5860-8 Recent 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.Medical equipment & techniquesbicsscinertial measurement unitmovement analysislong-track speed skatingvalidityIMUprincipal component analysiswearablescoringcarvingbalance assessmentdata augmentationgated recurrent unithuman activity recognitionone-dimensional convolutional neural networkintermittent claudicationvascular rehabilitation6 min walking testfunctional walkingTUGkinematicsfall risklogistic regressionelderlyinertial sensorartificial intelligencesupervised machine learninghead rotation testneck paincerebral palsydystoniachoreoathetosismachine learninghome-basedwearable deviceMLPgesture recognitionflex sensormodel searchneural networkinertial measurement unit-IMUmovement complexitysample entropytrunk flexionlow back painlifting techniquecamera systemward clustering methodK-means clustering methodensemble clustering methodBayesian neural networkpain self-efficacy questionnaireMedical equipment & techniquesBuisseret Fabienedt1290155Dierick FrédéricedtVan der Perre LiesbetedtBuisseret FabienothDierick FrédéricothVan der Perre LiesbetothBOOK9910637794103321Wearable Sensors Applied in Movement Analysis3021362UNINA