A machine learning approach for automated recognition of movement patterns using basic, kinetic and kinematic gait data.
about
Classifying lower extremity muscle fatigue during walking using machine learning and inertial sensorsSubspace identification and classification of healthy human gaitEstimation of errors in force platform data.Intra-individual gait patterns across different time-scales as revealed by means of a supervised learning model using kernel-based discriminant regression.Pattern classification of kinematic and kinetic running data to distinguish gender, shod/barefoot and injury groups with feature ranking.An ensemble analysis of electromyographic activity during whole body pointing with the use of support vector machines.Broiler chickens can benefit from machine learning: support vector machine analysis of observational epidemiological data.Shotgun approaches to gait analysis: insights & limitations.Influence of the Lower Jaw Position on the Running Pattern.Vertical ground reaction force marker for Parkinson's disease.Accelerometry-based classification of human activities using Markov modeling.Immediate effects of EVA midsole resilience and upper shoe structure on running biomechanics: a machine learning approach.Detecting knee osteoarthritis and its discriminating parameters using random forests.Recognition of Daily Gestures with Wearable Inertial Rings and Bracelets.Selection of clinical features for pattern recognition applied to gait analysis.Machine learning methods for classifying human physical activity from on-body accelerometers.Machine learning classification of medication adherence in patients with movement disorders using non-wearable sensors.The novel quantitative technique for assessment of gait symmetry using advanced statistical learning algorithm.Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analysesA new training algorithm using artificial neural networks to classify gender-specific dynamic gait patterns.A novel approach for analysis of altered gait variability in amyotrophic lateral sclerosis.A new approach for concealed information identification based on ERP assessment.Support vector machines categorize the scaling of human grip configurations.A neurofuzzy inference system based on biomechanical features for the evaluation of the effects of physical training."You can tell by the way I use my walk." Predicting the presence of cognitive load with gait measurements
P2860
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P2860
A machine learning approach for automated recognition of movement patterns using basic, kinetic and kinematic gait data.
description
2005 nî lūn-bûn
@nan
2005 թուականի Մարտին հրատարակուած գիտական յօդուած
@hyw
2005 թվականի մարտին հրատարակված գիտական հոդված
@hy
2005年の論文
@ja
2005年論文
@yue
2005年論文
@zh-hant
2005年論文
@zh-hk
2005年論文
@zh-mo
2005年論文
@zh-tw
2005年论文
@wuu
name
A machine learning approach fo ...... netic and kinematic gait data.
@ast
A machine learning approach fo ...... netic and kinematic gait data.
@en
type
label
A machine learning approach fo ...... netic and kinematic gait data.
@ast
A machine learning approach fo ...... netic and kinematic gait data.
@en
prefLabel
A machine learning approach fo ...... netic and kinematic gait data.
@ast
A machine learning approach fo ...... netic and kinematic gait data.
@en
P1476
A machine learning approach fo ...... netic and kinematic gait data.
@en
P2093
P304
P356
10.1016/J.JBIOMECH.2004.05.002
P577
2005-03-01T00:00:00Z