scholarly article | Q13442814 |
P8978 | DBLP publication ID | journals/sensors/KozlowAY18 |
P356 | DOI | 10.3390/S18103329 |
P932 | PMC publication ID | 6210198 |
P698 | PubMed publication ID | 30287787 |
P50 | author | Svetlana Yanushkevich | Q92046129 |
P2093 | author name string | Noor Abid | |
Patrick Kozlow | |||
P2860 | cites work | Validity of the Kinect for Gait Assessment: A Focused Review | Q26767240 |
Kinematic Validation of a Multi-Kinect v2 Instrumented 10-Meter Walkway for Quantitative Gait Assessments | Q27314807 | ||
A dynamic Bayesian network for estimating the risk of falls from real gait data | Q30573419 | ||
Implementation of machine learning for classifying prosthesis type through conventional gait analysis. | Q40139633 | ||
Gait assessment using the Microsoft Xbox One Kinect: Concurrent validity and inter-day reliability of spatiotemporal and kinematic variables | Q40845684 | ||
Step accumulation per minute epoch is not the same as cadence for free-living adults. | Q45737894 | ||
Surface-EMG analysis for the quantification of thigh muscle dynamic co-contractions during normal gait. | Q51104882 | ||
Support vector machines for automated gait classification. | Q51974282 | ||
A Microsoft Kinect-Based Point-of-Care Gait Assessment Framework for Multiple Sclerosis Patients. | Q53055063 | ||
Recognition of a Person Wearing Sport Shoes or High Heels through Gait Using Two Types of Sensors. | Q55235108 | ||
Concurrent related validity of the GAITRite walkway system for quantification of the spatial and temporal parameters of gait | Q78818359 | ||
How humans walk: bout duration, steps per bout, and rest duration | Q83230105 | ||
P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
P6216 | copyright status | copyrighted | Q50423863 |
P433 | issue | 10 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | Bayesian network | Q812540 |
P577 | publication date | 2018-10-04 | |
P1433 | published in | Sensors | Q3478643 |
P1476 | title | Gait Type Analysis Using Dynamic Bayesian Networks | |
P478 | volume | 18 |
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