A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington's Disease Patients.
about
Real-Time Classification of Patients with Balance Disorders vs. Normal Subjects Using a Low-Cost Small Wireless Wearable Gait Sensor.Smart Annotation of Cyclic Data Using Hierarchical Hidden Markov Models.Artificial intelligence in healthcare: past, present and future.Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine.Detection of Hemiplegic Walking Using a Wearable Inertia Sensing Device.Two Fronts of Future MedicineAn Overview of Smart Shoes in the Internet of Health Things: Gait and Mobility Assessment in Health Promotion and Disease MonitoringMultiple Wearable Sensors in Parkinson and Huntington Disease Individuals: A Pilot Study in Clinic and at HomeWearable Sensor Data to Track Subject-Specific Movement Patterns Related to Clinical Outcomes Using a Machine Learning Approach
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P2860
A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington's Disease Patients.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
A Machine Learning Framework f ...... Huntington's Disease Patients.
@ast
A Machine Learning Framework f ...... Huntington's Disease Patients.
@en
type
label
A Machine Learning Framework f ...... Huntington's Disease Patients.
@ast
A Machine Learning Framework f ...... Huntington's Disease Patients.
@en
prefLabel
A Machine Learning Framework f ...... Huntington's Disease Patients.
@ast
A Machine Learning Framework f ...... Huntington's Disease Patients.
@en
P2093
P2860
P356
P1433
P1476
A Machine Learning Framework f ...... Huntington's Disease Patients
@en
P2093
Andrea Cereatti
Angelo M Sabatini
Diana Trojaniello
P2860
P356
10.3390/S16010134
P407
P577
2016-01-21T00:00:00Z