Table 9.
Comparison with the other studies
| Author(s) | Sensor(s) | Method(s) | Success Rate |
|---|---|---|---|
| Tunçel et al. [36] | Gyroscope | Bayesian Decision Theory, KNN, ANN, SVM | 80–96% |
| Györbíró et al. [3] | Accelerometer (Smart mobile phone) | ANN | 54–99% |
| Kwapisz et al. [8] | Accelerometer | Decision Tree, Logistic Regression, and MNN | 91.70% |
| Atallah et al. [22] | Accelerometer | Relief Feature Selection, Simba Feature Selection Bayes, KNN | 90% |
| Siirtola et al. [37] | Accelerometer (Smart mobile phone) | Decision Tree KNN/QDA | 95% |
| Chernbumroong et al. [23] | Accelerometer, Altimeter | MLP, RBF and SVM | 90.23% |
| Elvira et al. [24] | Magnetometer, Accelerometer, Gyroscope | Hidden Markov Models (HMM) | 89% |
| Bayat et al. [25] | Accelerometer (Smart mobile phone) | ANN, SVM, Random Forest | 81–91% |
| Kurban [38] | Accelerometer | ANN, SVM, NB, | 83–98% |
| Capela et al. [39] | Accelerometer, Gyroscope (Smart mobile phone) | Naive Bayes, SVM, j48 Decision Tree | 90–97% |
| Ponce et al. [26] | Magnetometer, Accelerometer, Gyroscope | Artificial Hydrocarbon Networks (AHN) | 97% |
| Damaševičius et al. [40] | Accelerometer, Gyroscope | Jaccard Distance | 95,6% |
| Howcroft et al. [41] | Accelerometer, Pressure Sensor | Correlation-Based Feature Selection, Fast Correlation-Based Filter (FCBF), and Relief-F | 95% |
| Chen et al. [42] | Accelerometer, Gyroscope (Smart mobile phone) | KNN, Linear Kernel and RBF, SVM, Random Forest | 96.26% |
| Wang et al. [43] | Wireless signal | PCA, DWT, Activity Recognition and Monitoring system (CARM) | 96% |
| Hassan et al. [9] | Accelerometer, Gyroscope (Smart mobile phone) | Deep Learning, Belief Network | 94.12% |
| San-Segundo et al. [12] | Accelerometer, Gyroscope (Smart mobile phone, Smart watch) | ANN, SVM, Random Forest | 98.8–99.4% |
| Huynh-The et al. [44] | Accelerometer, Gyroscope | CNN | 95.7% |
| Debache et al. [13] | Accelerometer, Gyroscope | LR (Logistic Regression) | 97.3% |
| Tuncer et al. [27] | Magnetometer, Accelerometer, Gyroscope | TP-DWT | 99.14% |
| Tuncer et al. [28] | Magnetometer, Accelerometer, Gyroscope | MK-LDP | 99.36–99.47- 99.71% |
| Tuncer et al. [29] | Magnetometer, Accelerometer, Gyroscope | ResNet18, ResNet50 and ResNet101 | 99.96 -99.61% |
| Tuncer et al. [45] | Magnetometer, Accelerometer, Gyroscope | Novel Tent Pooling | 99.81% |
| This Study | Magnetometer, Accelerometer, Gyroscope | 1D-GLCM | 96.67% and 93.89% |
Bold values indicate the highest and lowest performances