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230202 ||| eng |
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|a books978-3-0365-5859-2
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|a 9783036558592
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|a 9783036558608
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|a Buisseret, Fabien
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|a Wearable Sensors Applied in Movement Analysis
|h Elektronische Ressource
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| 260 |
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|a Basel
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2022
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| 300 |
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|a 1 electronic resource (154 p.)
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| 653 |
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|a machine learning
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|a logistic regression
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|a Bayesian neural network
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|a scoring
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|a ensemble clustering method
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|a Medical equipment and techniques / bicssc
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|a TUG
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|a inertial sensor
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| 653 |
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|a long-track speed skating
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| 653 |
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|a 6 min walking test
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| 653 |
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|a fall risk
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| 653 |
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|a n/a
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|a data augmentation
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|a cerebral palsy
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| 653 |
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|a lifting technique
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| 653 |
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|a neck pain
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| 653 |
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|a gated recurrent unit
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| 653 |
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|a supervised machine learning
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|a home-based
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|a inertial measurement unit
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|a MLP
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|a sample entropy
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|a carving
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|a model search
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|a choreoathetosis
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|a ward clustering method
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|a vascular rehabilitation
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|a principal component analysis
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|a movement complexity
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|a head rotation test
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| 653 |
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|a K-means clustering method
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|a kinematics
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|a dystonia
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|a movement analysis
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|a camera system
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|a pain self-efficacy questionnaire
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|a gesture recognition
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|a wearable
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|a IMU
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|a elderly
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|a inertial measurement unit-IMU
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|a intermittent claudication
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| 653 |
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|a low back pain
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| 653 |
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|a wearable device
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| 653 |
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|a artificial intelligence
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|a balance assessment
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| 653 |
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|a validity
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|a functional walking
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|a trunk flexion
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|a one-dimensional convolutional neural network
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|a flex sensor
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|a neural network
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|a human activity recognition
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| 700 |
1 |
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|a Dierick, Frédéric
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| 700 |
1 |
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|a Van der Perre, Liesbet
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| 700 |
1 |
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|a Buisseret, Fabien
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 028 |
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|a 10.3390/books978-3-0365-5859-2
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| 856 |
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|u https://www.mdpi.com/books/pdfview/book/6426
|7 0
|x Verlag
|3 Volltext
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| 856 |
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|u https://directory.doabooks.org/handle/20.500.12854/94590
|z DOAB: description of the publication
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|a 658
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|a 140
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|a 700
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|a 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.
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