1. Recent Advances in Motion Analysis.
- Author
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Di Nardo, Francesco, Di Nardo, Francesco, and Fioretti, Sandro
- Subjects
Technology: general issues ,EMG sensors ,Internet of Things (IoT) ,Lie group ,Parkinson's disease ,WBSN ,accelerometer ,activation patterns ,activity recognition ,ankle kinematics ,automatic detection of the FRP ,automotive radar ,back propagation ,cerebral palsy ,co-activation ,coefficient of variation ,cognitive engagement ,deep learning ,electrogoniometer ,embedded systems ,estimation model ,falls ,flexion-relaxation phenomenon ,gait variability ,gait-event detection ,gait-phase classification ,hemiplegia ,human activity recognition (HAR) ,inertial sensor ,knee ,knee angle ,load cells ,machine learning ,motion analysis ,motor disorders ,neural networks ,performance ,postural perturbations ,principal component analysis ,random forest ,rate invariance ,rowing ,sEMG ,seated posture ,sensorized seat ,signal processing ,slips ,statistical gait analysis ,stress level ,stretch-sensors ,surface EMG ,surface electromyography ,technology ,trips ,walking ,walking analysis ,wearable device ,wearable sensors ,wearables - Abstract
Summary: The 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.