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Journal ArticleDOI

Clinical applications of sensors for human posture and movement analysis: a review.

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TLDR
Electronic sensors and systems with advanced technology, namely accelerometer, gyroscope, flexible angular sensor, electromagnetic tracking system and sensing fabrics, have been developed and applied to solve the relevant application problems of the image-based methods, but other problems for using these electronic sensors emerged, including the environment influence and signal extraction difficulties.
Abstract
Measurement of human posture and movement is an important area of research in the bioengineering and rehabilitation fields. Various attempts have been initiated for different clinical application goals, such as diagnosis of pathological posture and movements, assessment of pre- and post-treatment efficacy and comparison of different treatment protocols. Image-based methods for measurements of human posture and movements have been developed, such as the photogrammetry, optoelectric technique and video analysis. However, it is found that these methods are complicated to set up, time-consuming to operate and could only be applied in laboratory environments. Electronic sensors and systems with advanced technology, namely accelerometer, gyroscope, flexible angular sensor, electromagnetic tracking system and sensing fabrics, have been developed and applied to solve the relevant application problems of the image-based methods. Nonetheless, other problems for using these electronic sensors emerged, including the environment influence and signal extraction difficulties. Further development of these electronic sensors and measurement methods could enhance their clinical applications in institutional as well as community levels. This article reviews the possible applications of these electronic sensors and systems, and precautions of their applications in analysis of human posture and movement. Such information would help researchers and clinicians in selecting and developing the most appropriate measurement techniques of using the electronic sensors for clinical applications of human posture and movement analysis.

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Citations
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Comparative study on classifying human activities with miniature inertial and magnetic sensors

TL;DR: Bayesian decision making (BDM) results in the highest correct classification rate with relatively small computational cost, and a performance comparison of the classification techniques is provided in terms of their correct differentiation rates, confusion matrices, and computational cost.
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Methods for gait event detection and analysis in ambulatory systems.

TL;DR: Various sensors and sensor combinations capable of analyzing gait in ambulatory settings are found, ranging form simple force based binary switches to complex setups involving multiple inertial sensors and advanced algorithms.
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Recognizing Daily and Sports Activities in Two Open Source Machine Learning Environments Using Body-Worn Sensor Units

TL;DR: Comparing the different sensor modalities indicates that if only a single sensor type is used, the highest classification rates are achieved with magnetometers, followed by accelerometers and gyroscopes, which may be preferable because of their lower computational requirements.
Journal ArticleDOI

Development of a wearable sensor system for quantitative gait analysis

TL;DR: In this paper, a study on development of a wearable sensor system for quantitative gait analysis using inertial sensors of gyroscopes and accelerometers is presented, which is designed to detect gait phases including initial contact, loading response, mid stance, terminal stance, pre swing, initial swing, mid swing and terminal swing.
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An Emerging Era in the Management of Parkinson's Disease: Wearable Technologies and the Internet of Things

TL;DR: The existing wearable technologies and the Internet-of-Things concept applied to PD are reviewed and discussed, with an emphasis on how this technological platform may lead to a shift in paradigm in terms of diagnostics and treatment.
References
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