2019
DOI: 10.1109/jsen.2018.2866802
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Heading Drift Reduction for Foot-Mounted Inertial Navigation System via Multi-Sensor Fusion and Dual-Gait Analysis

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Cited by 85 publications
(48 citation statements)
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References 28 publications
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“…A source of GED timing error is the potential drift introduced with signal integration. Sophisticated techniques, such as zero velocity update [ 45 ], extended Kalman filters [ 46 ] combined with sensor fusion [ 47 ], however, may be used to reduce drift. In addition to timing errors introduced from the signal, previous studies have reported that FVA is not applicable to clinical cases [ 11 , 48 ].…”
Section: Discussionmentioning
confidence: 99%
“…A source of GED timing error is the potential drift introduced with signal integration. Sophisticated techniques, such as zero velocity update [ 45 ], extended Kalman filters [ 46 ] combined with sensor fusion [ 47 ], however, may be used to reduce drift. In addition to timing errors introduced from the signal, previous studies have reported that FVA is not applicable to clinical cases [ 11 , 48 ].…”
Section: Discussionmentioning
confidence: 99%
“…If the predefined threshold of the IMU is set too low, it will detect all of these peaks as strides. Hence, fixed thresholds are not reliable [21][22][23]. At the same time, proposing a displacement estimation method based on the model of human lower-limb biomechanics combined with sensor data fusion technology, portable wearable lower-limb gait analysis of exercise rehabilitation systems can calculate kinematic parameters and spatio-temporal parameters of the human gait, providing a complete assessment of lower-limb motion and achieving the integration of assessment and rehabilitation training [24,25].…”
Section: Related Workmentioning
confidence: 99%
“…Based on different gait models, necessary relations between the step length and various measurable or computable gait variables can be formulated. For the dualsensor configuration shown in Figure 4(a), a modified gait model was presented in our previous study [28], which is driven by the measurements from foot-mounted gyroscopes solely. In this model, human gait is represented by a single inverted pendulum model of a kneeless biped, taking the anthropometric data specific to each subject's biomechanics into consideration, as shown in Figure 7.…”
Section: Step Lengthsmentioning
confidence: 99%