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dc.contributor.editorDi Nardo, Francesco
dc.contributor.editorFioretti, Sandro
dc.date.accessioned2022-01-11T13:27:33Z
dc.date.available2022-01-11T13:27:33Z
dc.date.issued2021
dc.identifierONIX_20220111_9783036504384_19
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/76283
dc.description.abstractThe advances in the technology and methodology for human movement capture and analysis over the last decade have been remarkable. Besides acknowledged approaches for kinematic, dynamic, and electromyographic (EMG) analysis carried out in the laboratory, more recently developed devices, such as wearables, inertial measurement units, ambient sensors, and cameras or depth sensors, have been adopted on a wide scale. Furthermore, computational intelligence (CI) methods, such as artificial neural networks, have recently emerged as promising tools for the development and application of intelligent systems in motion analysis. Thus, the synergy of classic instrumentation and novel smart devices and techniques has created unique capabilities in the continuous monitoring of motor behaviors in different fields, such as clinics, sports, and ergonomics. However, real-time sensing, signal processing, human activity recognition, and characterization and interpretation of motion metrics and behaviors from sensor data still representing a challenging problem not only in laboratories but also at home and in the community. This book addresses open research issues related to the improvement of classic approaches and the development of novel technologies and techniques in the domain of motion analysis in all the various fields of application.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issuesen_US
dc.subject.otherfalls
dc.subject.otherslips
dc.subject.othertrips
dc.subject.otherpostural perturbations
dc.subject.otherwearables
dc.subject.otherstretch-sensors
dc.subject.otherankle kinematics
dc.subject.otherrowing
dc.subject.othertechnology
dc.subject.otherinertial sensor
dc.subject.otheraccelerometer
dc.subject.otherperformance
dc.subject.othersignal processing
dc.subject.othersEMG
dc.subject.otherknee
dc.subject.otherrandom forest
dc.subject.otherprincipal component analysis
dc.subject.otherback propagation
dc.subject.otherestimation model
dc.subject.otherknee angle
dc.subject.otherdeep learning
dc.subject.otherneural networks
dc.subject.othergait-phase classification
dc.subject.otherelectrogoniometer
dc.subject.otherEMG sensors
dc.subject.otherwalking
dc.subject.othergait-event detection
dc.subject.otherautomotive radar
dc.subject.othermachine learning
dc.subject.otherwalking analysis
dc.subject.otherseated posture
dc.subject.othercognitive engagement
dc.subject.otherstress level
dc.subject.otherload cells
dc.subject.otherembedded systems
dc.subject.othersensorized seat
dc.subject.otherflexion-relaxation phenomenon
dc.subject.othersurface electromyography
dc.subject.otherwearable device
dc.subject.otherWBSN
dc.subject.otherautomatic detection of the FRP
dc.subject.otherInternet of Things (IoT)
dc.subject.otherhuman activity recognition (HAR)
dc.subject.othermotion analysis
dc.subject.otherwearable sensors
dc.subject.othercerebral palsy
dc.subject.otherhemiplegia
dc.subject.othermotor disorders
dc.subject.othergait variability
dc.subject.othercoefficient of variation
dc.subject.othersurface EMG
dc.subject.otherstatistical gait analysis
dc.subject.otheractivation patterns
dc.subject.otherco-activation
dc.subject.otherParkinson’s disease
dc.subject.otheractivity recognition
dc.subject.otherrate invariance
dc.subject.otherLie group
dc.titleRecent Advances in Motion Analysis
dc.typebook
oapen.identifier.doi10.3390/books978-3-0365-0439-1
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783036504384
oapen.relation.isbn9783036504391
oapen.pages192
oapen.place.publicationBasel, Switzerland


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