Table 2.
Squat classification performance of conventional machine learning (CML) and deep learning (DL) for five IMUs, two IMUs, and one IMU.
| Number of IMUs | Placement of IMUs | Random Forest (CML) | CNN–LSTM (DL) | ||||
|---|---|---|---|---|---|---|---|
| Accuracy | Sensitivity | Specificity | Accuracy | Sensitivity | Specificity | ||
| 5 IMUs | Right thigh, right calf, left thigh, left calf, and lumbar region | 75.4% | 78.6% | 90.3% | 91.7% | 90.9% | 94.6% |
| 2 IMUs | Right thigh and lumbar region | 63.2% | 64.6% | 87.6% | 83.9% | 85.6% | 90.4% |
| Right thigh and right calf | 73.9% | 76.8% | 89.5% | 88.7% | 90.5% | 95.7% | |
| Right calf and lumbar region | 66.0% | 70.1% | 86.1% | 86.2% | 87.1% | 87.6% | |
| 1 IMUs | Right thigh | 58.7% | 66.7% | 88.9% | 80.9% | 80.0% | 93.1% |
| Right calf | 57.6% | 62.7% | 82.2% | 76.1% | 78.9% | 92.8% | |
| Lumbar region | 34.6% | 38.6% | 68.1% | 46.1% | 50.3% | 79.0% | |