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open-source matlab script (paired-samples t-test) of one-dimensional spm (spm 1d)  (MathWorks Inc)
90
MathWorks Inc open-source matlab script (paired-samples t-test) of one-dimensional spm (spm 1d)
Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and <t>the</t> <t>three-dimensional</t> kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of <t>1-SPM</t> to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.
Open Source Matlab Script (Paired Samples T Test) Of One Dimensional Spm (Spm 1d), supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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one-dimensional statistical parametric mapping (spm)  (MathWorks Inc)
90
MathWorks Inc one-dimensional statistical parametric mapping (spm)
Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and <t>the</t> <t>three-dimensional</t> kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of <t>1-SPM</t> to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.
One Dimensional Statistical Parametric Mapping (Spm), supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/one-dimensional statistical parametric mapping (spm)/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
one-dimensional statistical parametric mapping (spm) - by Bioz Stars, 2026-04
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software package for one-dimensional statistical parametric mapping  (MathWorks Inc)
90
MathWorks Inc software package for one-dimensional statistical parametric mapping
Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and <t>the</t> <t>three-dimensional</t> kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of <t>1-SPM</t> to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.
Software Package For One Dimensional Statistical Parametric Mapping, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/software package for one-dimensional statistical parametric mapping/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
software package for one-dimensional statistical parametric mapping - by Bioz Stars, 2026-04
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one-dimensional spm package for  (MathWorks Inc)
90
MathWorks Inc one-dimensional spm package for
Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and <t>the</t> <t>three-dimensional</t> kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of <t>1-SPM</t> to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.
One Dimensional Spm Package For, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/one-dimensional spm package for/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
one-dimensional spm package for - by Bioz Stars, 2026-04
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one-dimensional statistical parametric mapping (1d spm)  (MathWorks Inc)
90
MathWorks Inc one-dimensional statistical parametric mapping (1d spm)
Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and <t>the</t> <t>three-dimensional</t> kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of <t>1-SPM</t> to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.
One Dimensional Statistical Parametric Mapping (1d Spm), supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/one-dimensional statistical parametric mapping (1d spm)/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
one-dimensional statistical parametric mapping (1d spm) - by Bioz Stars, 2026-04
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one-dimensional statistical parametric mapping (spm) program  (MathWorks Inc)
90
MathWorks Inc one-dimensional statistical parametric mapping (spm) program
Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and <t>the</t> <t>three-dimensional</t> kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of <t>1-SPM</t> to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.
One Dimensional Statistical Parametric Mapping (Spm) Program, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/one-dimensional statistical parametric mapping (spm) program/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
one-dimensional statistical parametric mapping (spm) program - by Bioz Stars, 2026-04
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one-dimensional spm (1d-spm)  (MOCAP Inc)
90
MOCAP Inc one-dimensional spm (1d-spm)
Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and <t>the</t> <t>three-dimensional</t> kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of <t>1-SPM</t> to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.
One Dimensional Spm (1d Spm), supplied by MOCAP Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/one-dimensional spm (1d-spm)/product/MOCAP Inc
Average 90 stars, based on 1 article reviews
one-dimensional spm (1d-spm) - by Bioz Stars, 2026-04
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one-dimensional spm spm1d  (MathWorks Inc)
90
MathWorks Inc one-dimensional spm spm1d
Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and <t>the</t> <t>three-dimensional</t> kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of <t>1-SPM</t> to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.
One Dimensional Spm Spm1d, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/one-dimensional spm spm1d/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
one-dimensional spm spm1d - by Bioz Stars, 2026-04
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one-dimensional statistical parametric mapping (spm)  (Human Kinetics Inc)
90
Human Kinetics Inc one-dimensional statistical parametric mapping (spm)
Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and <t>the</t> <t>three-dimensional</t> kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of <t>1-SPM</t> to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.
One Dimensional Statistical Parametric Mapping (Spm), supplied by Human Kinetics Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/one-dimensional statistical parametric mapping (spm)/product/Human Kinetics Inc
Average 90 stars, based on 1 article reviews
one-dimensional statistical parametric mapping (spm) - by Bioz Stars, 2026-04
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Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and the three-dimensional kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of 1-SPM to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.

Journal: Heliyon

Article Title: A new method applied for explaining the landing patterns: Interpretability analysis of machine learning

doi: 10.1016/j.heliyon.2024.e26052

Figure Lengend Snippet: Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and the three-dimensional kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of 1-SPM to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.

Article Snippet: For the implementation of SPM, the open-source MATLAB script (paired-samples T-test) of One-Dimensional SPM (SPM 1D) was employed to test the statistical differences, and the significance threshold was set as 0.05 [ , ].

Techniques: