Characterizing Dynamic Walking Patterns and Detecting Falls with Wearable Sensors Using Gaussian Process Methods.

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Characterizing Dynamic Walking Patterns and Detecting Falls with Wearable Sensors Using Gaussian Process Methods.

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2017 nî lūn-bûn

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2017年の論文

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2017年論文

@yue

2017年論文

@zh-hant

2017年論文

@zh-hk

2017年論文

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2017年論文

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2017年论文

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2017年论文

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2017年论文

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Characterizing Dynamic Walking ...... sing Gaussian Process Methods.

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Characterizing Dynamic Walking ...... sing Gaussian Process Methods.

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Characterizing Dynamic Walking ...... sing Gaussian Process Methods.

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Characterizing Dynamic Walking ...... sing Gaussian Process Methods.

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Characterizing Dynamic Walking ...... sing Gaussian Process Methods.

@en

Characterizing Dynamic Walking ...... sing Gaussian Process Methods.

@nl

P1476

Characterizing Dynamic Walking ...... sing Gaussian Process Methods.

@en

P2093

Jeongho Park

http://www.w3.org/2001/XMLSchema#string

Jooyoung Park

http://www.w3.org/2001/XMLSchema#string

Keehoon Sung

http://www.w3.org/2001/XMLSchema#string

Seongman Heo

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Taehwan Kim

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P2860

Matplotlib: A 2D Graphics Environment

Nonlinear Component Analysis as a Kernel Eigenvalue Problem

Detecting falls with wearable sensors using machine learning techniques.

Sensor data acquisition and processing parameters for human activity classification.

Nonlinear dimensionality reduction by locally linear embedding.

Fall detection with the support vector machine during scripted and continuous unscripted activities.

A global geometric framework for nonlinear dimensionality reduction.

Gaussian process dynamical models for human motion.

SVDD-based pattern denoising.

Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring.

P31

scholarly article

P356

10.3390/S17051172

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P407

English

P433

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P478

http://www.w3.org/2001/XMLSchema#string

P577

2017-05-20T00:00:00Z

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P698

28531125

http://www.w3.org/2001/XMLSchema#string

P921

wearable technology

P932

5470917

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