Using Wearable Accelerometers to Develop a Vertical Ground Reaction Force Prediction Model during Running: A Sensitivity Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Materials
2.3. Protocol
2.4. Data Management
2.5. Pre-Processing
2.6. Model Development
2.7. Statistics and Model Validation
3. Results
3.1. General Results
3.2. Training Phase
3.3. Validation Phase
3.4. Test Phase
4. Discussion
4.1. Training and Validation Phases
4.2. Sensitivity to Cut-Off Frequency Conditions and Size of Training Dataset
4.3. Test Phase
4.4. Personalized Model
4.5. Perspectives
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Cut-Off Freq. (Hz) | Stance # | Training | Validation | ||||||||
R2 | RMSE (BW) | (%) | (%) | (%) | R2 | RMSE (BW) | (%) | (%) | (%) | ||
5 | 10 | 0.987 | 0.08 | 10.95 | 1.71 | 18.08 | 0.712 | 0.48 | 72.31 | 11.39 | 49.41 |
30 | 0.985 | 0.09 | 14.14 | 1.79 | 8.33 | 0.970 | 0.23 | 21.39 | 15.45 | 2.80 | |
50 | 0.988 | 0.08 | 12.50 | 0.87 | 9.26 | 0.979 | 0.15 | 4.86 | 7.19 | 3.51 | |
70 | 0.989 | 0.08 | 11.99 | 0.44 | 8.95 | 0.971 | 0.13 | 1.51 | 1.29 | 1.15 | |
90 | 0.989 | 0.08 | 12.02 | 0.68 | 9.51 | 0.967 | 0.14 | 1.17 | 0.17 | 5.90 | |
10 | 10 | 0.983 | 0.10 | 6.41 | 1.15 | 15.39 | 0.658 | 0.52 | 96.81 | 13.87 | 115.70 |
30 | 0.988 | 0.08 | 11.33 | 1.75 | 7.20 | 0.931 | 0.25 | 35.87 | 11.64 | 21.07 | |
50 | 0.989 | 0.08 | 11.02 | 0.53 | 8.79 | 0.975 | 0.13 | 11.18 | 2.80 | 0.95 | |
70 | 0.990 | 0.07 | 10.39 | 0.70 | 7.23 | 0.968 | 0.14 | 2.71 | 0.61 | 0.85 | |
90 | 0.990 | 0.07 | 10.23 | 0.46 | 7.33 | 0.963 | 0.14 | 1.51 | 2.11 | 1.89 | |
15 | 10 | 0.970 | 0.13 | 1.18 | 1.34 | 13.09 | 0.548 | 0.59 | 114.19 | 15.68 | 176.38 |
30 | 0.990 | 0.07 | 7.77 | 2.20 | 5.83 | 0.900 | 0.28 | 42.23 | 11.68 | 41.68 | |
50 | 0.991 | 0.07 | 8.98 | 0.11 | 8.01 | 0.960 | 0.16 | 15.23 | 1.59 | 10.51 | |
70 | 0.990 | 0.07 | 8.21 | 2.44 | 5.08 | 0.956 | 0.16 | 2.84 | 1.01 | 1.40 | |
90 | 0.990 | 0.07 | 7.80 | 2.20 | 4.71 | 0.951 | 0.17 | 0.26 | 2.48 | 1.54 | |
20 | 10 | 0.952 | 0.16 | 2.71 | 1.72 | 11.73 | 0.425 | 0.68 | 128.22 | 17.94 | 221.23 |
30 | 0.990 | 0.07 | 3.82 | 2.95 | 4.49 | 0.873 | 0.31 | 45.99 | 12.14 | 60.70 | |
50 | 0.992 | 0.07 | 6.57 | 0.96 | 7.11 | 0.935 | 0.20 | 19.38 | 1.21 | 22.37 | |
70 | 0.989 | 0.08 | 5.63 | 4.46 | 3.09 | 0.934 | 0.20 | 3.50 | 0.84 | 6.60 | |
90 | 0.989 | 0.08 | 4.94 | 4.22 | 2.40 | 0.932 | 0.20 | 0.45 | 2.24 | 4.28 | |
25 | 10 | 0.934 | 0.19 | 5.49 | 2.12 | 11.21 | 0.323 | 0.77 | 140.79 | 20.08 | 254.36 |
30 | 0.986 | 0.08 | 0.21 | 3.87 | 3.62 | 0.847 | 0.33 | 48.22 | 12.40 | 77.05 | |
50 | 0.992 | 0.06 | 4.00 | 1.90 | 6.38 | 0.904 | 0.25 | 23.38 | 1.26 | 34.40 | |
70 | 0.986 | 0.09 | 2.91 | 6.49 | 1.72 | 0.908 | 0.24 | 4.63 | 0.35 | 13.38 | |
90 | 0.985 | 0.09 | 1.94 | 6.24 | 0.96 | 0.909 | 0.23 | 0.54 | 1.71 | 9.09 | |
30 | 10 | 0.917 | 0.21 | 7.38 | 2.54 | 11.25 | 0.249 | 0.85 | 152.24 | 21.94 | 279.08 |
30 | 0.981 | 0.10 | 4.15 | 4.88 | 3.38 | 0.822 | 0.35 | 49.39 | 12.33 | 90.66 | |
50 | 0.992 | 0.07 | 1.42 | 2.87 | 5.98 | 0.869 | 0.29 | 26.95 | 1.48 | 45.47 | |
70 | 0.982 | 0.10 | 0.21 | 8.38 | 1.12 | 0.879 | 0.28 | 5.98 | 0.22 | 20.70 | |
90 | 0.981 | 0.10 | 0.97 | 8.10 | 0.50 | 0.885 | 0.26 | 0.20 | 1.18 | 14.97 | |
35 | 10 | 0.903 | 0.23 | 8.63 | 3.00 | 11.56 | 0.196 | 0.93 | 162.60 | 23.51 | 297.54 |
30 | 0.973 | 0.12 | 7.86 | 5.92 | 3.75 | 0.799 | 0.36 | 49.82 | 11.95 | 101.73 | |
50 | 0.990 | 0.07 | 1.08 | 3.81 | 5.94 | 0.835 | 0.33 | 29.96 | 1.73 | 55.14 | |
70 | 0.978 | 0.11 | 2.33 | 10.06 | 1.22 | 0.851 | 0.31 | 7.34 | 0.71 | 27.85 | |
90 | 0.975 | 0.11 | 3.64 | 9.75 | 0.90 | 0.863 | 0.29 | 0.39 | 0.78 | 21.16 | |
40 | 10 | 0.891 | 0.24 | 9.44 | 3.48 | 11.97 | 0.159 | 0.99 | 171.86 | 24.83 | 311.26 |
30 | 0.964 | 0.14 | 11.27 | 6.96 | 4.61 | 0.778 | 0.38 | 49.74 | 11.32 | 110.54 | |
50 | 0.989 | 0.08 | 3.44 | 4.72 | 6.25 | 0.803 | 0.37 | 32.40 | 1.92 | 63.30 | |
70 | 0.974 | 0.12 | 4.66 | 11.52 | 1.87 | 0.825 | 0.34 | 8.58 | 1.05 | 34.47 | |
90 | 0.970 | 0.13 | 6.01 | 11.18 | 1.93 | 0.842 | 0.31 | 1.04 | 0.56 | 27.18 | |
45 | 10 | 0.880 | 0.26 | 9.93 | 3.97 | 12.36 | 0.134 | 1.04 | 180.03 | 25.94 | 321.39 |
30 | 0.954 | 0.16 | 14.33 | 7.95 | 5.81 | 0.759 | 0.39 | 49.33 | 10.51 | 117.43 | |
50 | 0.986 | 0.08 | 5.61 | 5.55 | 6.83 | 0.775 | 0.39 | 34.31 | 2.02 | 70.07 | |
70 | 0.969 | 0.13 | 6.76 | 12.77 | 2.91 | 0.802 | 0.36 | 9.67 | 1.24 | 40.39 | |
90 | 0.964 | 0.14 | 8.07 | 12.40 | 3.38 | 0.824 | 0.32 | 1.69 | 0.50 | 32.77 | |
50 | 10 | 0.872 | 0.27 | 10.21 | 4.46 | 12.70 | 0.115 | 1.08 | 187.19 | 26.88 | 328.78 |
30 | 0.943 | 0.17 | 17.03 | 8.87 | 7.25 | 0.742 | 0.40 | 48.74 | 9.60 | 122.75 | |
50 | 0.984 | 0.09 | 7.59 | 6.32 | 7.62 | 0.750 | 0.42 | 35.79 | 2.04 | 75.61 | |
70 | 0.965 | 0.14 | 8.61 | 13.85 | 4.20 | 0.782 | 0.38 | 10.57 | 1.29 | 45.60 | |
90 | 0.959 | 0.15 | 9.83 | 13.44 | 5.06 | 0.808 | 0.34 | 2.27 | 0.58 | 37.82 |
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Participant # | Mean | Standard Deviation |
---|---|---|
1 | 3.19 | 0.11 |
2 | 3.13 | 0.25 |
3 | 2.78 | 0.03 |
4 | 3.08 | 0.06 |
5 | 2.75 | 0.06 |
6 | 2.83 | 0.06 |
7 | 3.39 | 0.19 |
8 | 3.11 | 0.06 |
Number of Stances | Cut-Off Frequency (Hz) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
5 | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 | 50 | |
10 | 0.987 | 0.983 | 0.970 | 0.952 | 0.934 | 0.917 | 0.903 | 0.891 | 0.880 | 0.872 |
30 | 0.985 | 0.988 | 0.990 | 0.990 | 0.986 | 0.981 | 0.973 | 0.964 | 0.954 | 0.943 |
50 | 0.988 | 0.989 | 0.991 | 0.992 | 0.992 | 0.992 | 0.990 | 0.989 | 0.986 | 0.984 |
70 | 0.989 | 0.990 | 0.990 | 0.989 | 0.986 | 0.982 | 0.978 | 0.974 | 0.969 | 0.965 |
90 | 0.989 | 0.990 | 0.990 | 0.989 | 0.985 | 0.981 | 0.975 | 0.970 | 0.964 | 0.959 |
Number of Stances | Cut-Off Frequency (Hz) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
5 | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 | 50 | |
10 | 0.712 | 0.658 | 0.548 | 0.425 | 0.323 | 0.249 | 0.196 | 0.159 | 0.134 | 0.115 |
30 | 0.970 | 0.931 | 0.900 | 0.873 | 0.847 | 0.822 | 0.799 | 0.778 | 0.759 | 0.742 |
50 | 0.979 | 0.975 | 0.960 | 0.935 | 0.904 | 0.869 | 0.835 | 0.803 | 0.775 | 0.750 |
70 | 0.971 | 0.968 | 0.956 | 0.934 | 0.908 | 0.879 | 0.851 | 0.825 | 0.802 | 0.782 |
90 | 0.967 | 0.963 | 0.951 | 0.932 | 0.909 | 0.885 | 0.863 | 0.842 | 0.824 | 0.808 |
Participant # | R2 | RMSE (BW) | (%) | (%) | (%) |
---|---|---|---|---|---|
1 | 0.924 | 0.45 | 30.77 | 32.42 | 40.90 |
2 | 0.661 | 0.45 | 47.25 | 23.62 | 56.36 |
3 | 0.742 | 0.84 | 33.26 | 43.95 | 3.64 |
4 | 0.985 | 0.17 | 1.57 | 4.27 | 15.15 |
5 | 0.793 | 0.36 | 51.20 | 12.81 | 25.42 |
6 | 0.900 | 0.42 | 26.30 | 33.21 | 28.59 |
7 | 0.340 | 0.74 | 68.45 | 23.80 | 21.77 |
8 | 0.411 | 0.75 | 60.16 | 23.15 | 55.65 |
Participant # | R2 | RMSE (BW) | (%) | (%) | (%) |
---|---|---|---|---|---|
1 | 0.957 ± 0.016 | 0.45 ± 0.08 | 18.32 ± 7.36 | 24.33 ± 7.09 | 34.94 ± 2.75 |
2 | 0.749 ± 0.136 | 0.41 ± 0.10 | 21.28 ± 15.36 | 18.91 ± 6.15 | 48.78 ± 5.94 |
3 | 0.785 ± 0.055 | 1.02 ± 0.28 | 25.45 ± 7.07 | 58.77 ± 19.22 | 14.74 ± 10.46 |
4 | 0.947 ± 0.036 | 0.45 ± 0.29 | 21.96 ± 19.39 | 21.96 ± 18.04 | 20.09 ± 9.81 |
5 | 0.898 ± 0.062 | 0.43 ± 0.15 | 51.41 ± 11.74 | 12.06 ± 7.84 | 13.25 ± 7.49 |
6 | 0.807 ± 0.084 | 0.48 ± 0.08 | 10.49 ± 7.83 | 29.83 ± 5.97 | 15.35 ± 6.85 |
7 | 0.294 ± 0.111 | 0.88 ± 0.23 | 77.05 ± 15.64 | 28.43 ± 6.83 | 23.43 ± 5.36 |
8 | 0.574 ± 0.111 | 0.63 ± 0.08 | 56.87 ± 4.23 | 16.09 ± 4.75 | 49.69 ± 3.51 |
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Provot, T.; Choupani, S.; Bourgain, M.; Valdes-Tamayo, L.; Chadefaux, D. Using Wearable Accelerometers to Develop a Vertical Ground Reaction Force Prediction Model during Running: A Sensitivity Study. Vibration 2023, 6, 680-694. https://doi.org/10.3390/vibration6030042
Provot T, Choupani S, Bourgain M, Valdes-Tamayo L, Chadefaux D. Using Wearable Accelerometers to Develop a Vertical Ground Reaction Force Prediction Model during Running: A Sensitivity Study. Vibration. 2023; 6(3):680-694. https://doi.org/10.3390/vibration6030042
Chicago/Turabian StyleProvot, Thomas, Samaneh Choupani, Maxime Bourgain, Laura Valdes-Tamayo, and Delphine Chadefaux. 2023. "Using Wearable Accelerometers to Develop a Vertical Ground Reaction Force Prediction Model during Running: A Sensitivity Study" Vibration 6, no. 3: 680-694. https://doi.org/10.3390/vibration6030042