Detecting falls with wearable sensors using machine learning techniques.
about
Novel Hierarchical Fall Detection Algorithm Using a Multiphase Fall Model.Analysis of a Smartphone-Based Architecture with Multiple Mobility Sensors for Fall Detection.An Energy-Efficient Multi-Tier Architecture for Fall Detection Using Smartphones.A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson's Disease Patients.An Unobtrusive Fall Detection and Alerting System Based on Kalman Filter and Bayes Network Classifier.A wavelet-based approach to fall detectionNew Fast Fall Detection Method Based on Spatio-Temporal Context Tracking of Head by Using Depth Images.Feature Selection and Predictors of Falls with Foot Force Sensors Using KNN-Based Algorithms.Human Activity Recognition in AAL Environments Using Random Projections.The Evaluation of Physical Stillness with Wearable Chest and Arm Accelerometer during Chan Ding Practice.An Analysis on Sensor Locations of the Human Body for Wearable Fall Detection Devices: Principles and Practice.Activity Recognition Invariant to Sensor Orientation with Wearable Motion SensorsFaller Classification in Older Adults Using Wearable Sensors Based on Turn and Straight-Walking Accelerometer-Based Features.Progress in Biomedical Knowledge Discovery: A 25-year Retrospective.Characterizing Dynamic Walking Patterns and Detecting Falls with Wearable Sensors Using Gaussian Process Methods.On the Comparison of Wearable Sensor Data Fusion to a Single Sensor Machine Learning Technique in Fall Detection.Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine.Biomechanical and human behavior assessment using virtual reality to challenge balance and posture for the elderly and patients with Parkinson's disease.Personalized medicine: from genotypes, molecular phenotypes and the quantified self, towards improved medicine.A Novel Detection Model and Its Optimal Features to Classify Falls from Low- and High-Acceleration Activities of Daily Life Using an Insole Sensor System.Generative Adversarial Networks for Generation and Classification of Physical Rehabilitation Movement EpisodesActivity Recognition Invariant to Wearable Sensor Unit Orientation Using Differential Rotational Transformations Represented by QuaternionsA Smart Device Enabled System for Autonomous Fall Detection and Alert
P2860
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P2860
Detecting falls with wearable sensors using machine learning techniques.
description
2014 nî lūn-bûn
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2014 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի հունիսին հրատարակված գիտական հոդված
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2014年の論文
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2014年論文
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2014年論文
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2014年論文
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2014年論文
@zh-mo
2014年論文
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2014年论文
@wuu
name
Detecting falls with wearable sensors using machine learning techniques.
@ast
Detecting falls with wearable sensors using machine learning techniques.
@en
type
label
Detecting falls with wearable sensors using machine learning techniques.
@ast
Detecting falls with wearable sensors using machine learning techniques.
@en
prefLabel
Detecting falls with wearable sensors using machine learning techniques.
@ast
Detecting falls with wearable sensors using machine learning techniques.
@en
P2860
P356
P1433
P1476
Detecting falls with wearable sensors using machine learning techniques.
@en
P2093
Ahmet Turan Özdemir
Billur Barshan
P2860
P304
10691-10708
P356
10.3390/S140610691
P407
P577
2014-06-18T00:00:00Z