A Granular Computing Classifier for Human Activity with Smartphones
Abstract
:1. Introduction
2. Basic Concepts
2.1. Feature Selection
2.2. Granular Computing
2.2.1. Granularity and Granule Representation
2.2.2. Operators between Granules
3. Methods and Materials
3.1. Feature Selection
3.2. Granular Computing Classifier
3.2.1. Granules Builder
3.2.2. Granular Computing Network
4. Experimental Results and Discussion
4.1. Dataset Description
4.2. Experimental Results on Approach
4.3. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
HAR | Human Activity Recognition |
SFFS | Sequential Floating Forward Search |
SVM | Support Vector Machine |
ID3 | Iterative Dichotomizer 3 |
PCA | Principal Component Analysis |
SVD | Singular Value Decomposition |
LDA | Linear Discriminant Analysis |
GrC | Granular Computing |
KNN | K-Nearest Neighbors |
MLP | Multi-Layer Perceptron |
MCC | Matthews Correlation Coefficient |
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Activity | Training Set | Testing Set |
---|---|---|
Laying | 1407 | 537 |
Sitting | 1286 | 491 |
Standing | 1374 | 533 |
Walking | 1226 | 496 |
Walking Downstairs | 986 | 420 |
Walking upstairs | 1073 | 471 |
Classifier | Correctly Classified Objects | Incorrectly Classified Objects |
---|---|---|
KNN | 2538 | 409 |
Naive Bayes | 2475 | 472 |
MLP | 2731 | 216 |
Random Forest | 2674 | 273 |
SVM | 2745 | 202 |
Peoposed Approach | 2770 | 177 |
Classifier/Class | KNN | Random Forest | MLP | Naive Bayes | SVM | Approach |
---|---|---|---|---|---|---|
LAYING | 1.000 | 1.000 | 0.994 | 0.993 | 1.000 | 1.000 |
SITTING | 0.830 | 0.880 | 0.871 | 0.922 | 0.913 | 0.967 |
STANDING | 0.752 | 0.853 | 0.905 | 0.711 | 0.865 | 0.960 |
WALKING | 0.840 | 0.868 | 0.893 | 0.794 | 0.908 | 0.982 |
WALKING DOWNSTAIRS | 0.930 | 0.972 | 0.985 | 0.845 | 0.973 | 0.977 |
WALKING UPSTAIRS | 0.848 | 0.890 | 0.923 | 0.852 | 0.944 | 0.954 |
Overall Precision | 0.865 | 0.910 | 0.928 | 0.853 | 0.933 | 0.973 |
Classifier/Class | KNN | Random Forest | MLP | Naive Bayes | SVM | Approach |
---|---|---|---|---|---|---|
LAYING | 1.000 | 1.000 | 0.998 | 0.998 | 1.000 | 1.000 |
SITTING | 0.684 | 0.833 | 0.890 | 0.574 | 0.837 | 1.000 |
STANDING | 0.870 | 0.895 | 0.878 | 0.930 | 0.927 | 1.000 |
WALKING | 0.960 | 0.964 | 0.978 | 0.895 | 0.994 | 0.899 |
WALKING DOWNSTAIRS | 0.786 | 0.840 | 0.917 | 0.752 | 0.929 | 0.817 |
WALKING UPSTAIRS | 0.841 | 0.894 | 0.894 | 0.854 | 0.894 | 0.926 |
Overall Recall | 0.861 | 0.907 | 0.927 | 0.840 | 0.931 | 0.940 |
Classifier/Class | KNN | Random Forest | MLP | Naive Bayes | SVM | Approach |
---|---|---|---|---|---|---|
LAYING | 1.000 | 1.000 | 0.996 | 0.995 | 1.000 | 1.000 |
SITTING | 0.750 | 0.856 | 0.880 | 0.708 | 0.874 | 0.983 |
STANDING | 0.807 | 0.873 | 0.891 | 0.806 | 0.895 | 0.980 |
WALKING | 0.896 | 0.913 | 0.934 | 0.842 | 0.949 | 0.939 |
WALKING DOWNSTAIRS | 0.852 | 0.902 | 0.949 | 0.796 | 0.950 | 0.890 |
WALKING UPSTAIRS | 0.844 | 0.892 | 0.908 | 0.853 | 0.918 | 0.940 |
Overall F-measure | 0.860 | 0.907 | 0.927 | 0.836 | 0.931 | 0.955 |
Classifier/Class | KNN | Random Forest | MLP | Naive Bayes | SVM | Approach |
---|---|---|---|---|---|---|
LAYING | 1.000 | 1.000 | 0.995 | 0.994 | 1.000 | 1.000 |
SITTING | 0.710 | 0.828 | 0.856 | 0.690 | 0.851 | 0.980 |
STANDING | 0.763 | 0.845 | 0.868 | 0.767 | 0.871 | 0.976 |
WALKING | 0.876 | 0.896 | 0.921 | 0.809 | 0.940 | 0.929 |
WALKING DOWNSTAIRS | 0.833 | 0.890 | 0.942 | 0.766 | 0.942 | 0.878 |
WALKING UPSTAIRS | 0.815 | 0.871 | 0.891 | 0.825 | 0.904 | 0.929 |
Overall MCC | 0.835 | 0.890 | 0.912 | 0.812 | 0.918 | 0.948 |
Classifier/Class | Time in Seconds |
---|---|
KNN | 5.55 |
Random Forest | 5.83 |
MLP | 440.97 |
Naive Bayes | 0.97 |
SVM | 1.86 |
Approach | 4 |
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Mahmood, M.A.; Almuayqil, S.; Alsalem, K.O.; Gasmi, K. A Granular Computing Classifier for Human Activity with Smartphones. Appl. Sci. 2023, 13, 1175. https://doi.org/10.3390/app13021175
Mahmood MA, Almuayqil S, Alsalem KO, Gasmi K. A Granular Computing Classifier for Human Activity with Smartphones. Applied Sciences. 2023; 13(2):1175. https://doi.org/10.3390/app13021175
Chicago/Turabian StyleMahmood, Mahmood A., Saleh Almuayqil, Khalaf Okab Alsalem, and Karim Gasmi. 2023. "A Granular Computing Classifier for Human Activity with Smartphones" Applied Sciences 13, no. 2: 1175. https://doi.org/10.3390/app13021175