04213nam 2201009z- 450 9910637794103321202212063-0365-5859-4(CKB)5470000001631595(oapen)https://directory.doabooks.org/handle/20.500.12854/94590(oapen)doab94590(EXLCZ)99547000000163159520202212d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierWearable Sensors Applied in Movement AnalysisBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online 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 and techniquesbicssc6 min walking testartificial intelligencebalance assessmentBayesian neural networkcamera systemcarvingcerebral palsychoreoathetosisdata augmentationdystoniaelderlyensemble clustering methodfall riskflex sensorfunctional walkinggated recurrent unitgesture recognitionhead rotation testhome-basedhuman activity recognitionIMUinertial measurement unitinertial measurement unit-IMUinertial sensorintermittent claudicationK-means clustering methodkinematicslifting techniquelogistic regressionlong-track speed skatinglow back painmachine learningMLPmodel searchmovement analysismovement complexityn/aneck painneural networkone-dimensional convolutional neural networkpain self-efficacy questionnaireprincipal component analysissample entropyscoringsupervised machine learningtrunk flexionTUGvalidityvascular rehabilitationward clustering methodwearablewearable deviceMedical equipment and techniquesBuisseret Fabienedt1290155Dierick FrédéricedtVan der Perre LiesbetedtBuisseret FabienothDierick FrédéricothVan der Perre LiesbetothBOOK9910637794103321Wearable Sensors Applied in Movement Analysis3021362UNINA