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Wearable Sensors Applied in Movement Analysis
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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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Keywords
- 6 min walking test
- artificial intelligence
- balance assessment
- Bayesian neural network
- camera system
- carving
- Cerebral palsy
- choreoathetosis
- data augmentation
- Dystonia
- elderly
- ensemble clustering method
- fall risk
- flex sensor
- functional walking
- gated recurrent unit
- gesture recognition
- head rotation test
- home-based
- human activity recognition
- IMU
- Inertial measurement unit
- inertial measurement unit—IMU
- inertial sensor
- intermittent claudication
- K-means clustering method
- kinematics
- lifting technique
- logistic regression
- long-track speed skating
- Low back pain
- Machine learning
- Medical equipment & techniques
- medicine
- Medicine: General Issues
- MLP
- model search
- movement analysis
- movement complexity
- n/a
- Neck pain
- Neural Network
- one-dimensional convolutional neural network
- pain self-efficacy questionnaire
- principal component analysis
- sample entropy
- scoring
- supervised machine learning
- trunk flexion
- TUG
- validity
- vascular rehabilitation
- ward clustering method
- wearable
- Wearable Device
Links
DOI: 10.3390/books978-3-0365-5859-2Editions