Human Activity Recognition of Individuals with Lower Limb Amputation in Free-Living Conditions: A Pilot Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Collection and Pre-Processing
2.2. Annotation of Slopes
2.3. Introducing “Label Resolution”
- Level 1: No Terrain Resolution. Labels only contain the condition of the traversed ground (ground is flat, ground is sloped, or is traversing stairs)
- Level 2: Hard/Soft Terrain Resolution. Terrains are resolved into whether the terrain involved is hard/soft. Hard terrains included concrete, stone, and gravel, while soft terrains included grass, sand and red ash (a type of clay pitch).
- Level 3: Full Resolution: All Labels use their full label resolution.
2.4. Experiment 1: Comparison of Supervised Classifiers
2.5. Experiment 2: Label Terrain Resolution
2.6. Experiment 3: Subject Cross-Validation
- Method 1: Healthy Participant Training. For the best performing classifiers, train data on the healthy participants, then use LOSO validation to test the classification accuracy for each of the ILLA participants individually.
- Method 2: Amputee Participant Training. All data from healthy participants are ignored. LOSO validation is again performed with the best classifiers, this time training the data on all-minus-one ILLA participants and testing on the remaining ILLA participant, repeating the process for each ILLA.
3. Results
3.1. Participant Information
3.2. Experiment 1: Classifier Optimization
3.3. Experiment 2: Label Terrain Resolution
3.4. Experiment 3: Subject Cross-Validation
4. Discussion
4.1. Main Findings and Interpretations
4.2. Comparisons with Other Studies
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A. Feature List
Appendix A.1. Condensed Feature List
Feature | Explanation |
---|---|
Statistical and Time Domain Features | |
Mean | |
Median | |
Variance | |
Root Mean Square | |
Crest Factor | |
L1 Norm | |
L2 Norm | |
Variance of the sample-wise Norm | |
Skewness | |
Kurtosis | |
25th Quartile | |
75th Quartile | |
Interquartile Range | |
Maximum | |
Minimum | |
Range | |
Mean Absolute Deviation | |
Signal Magnitude Area | |
Energy | |
Power | |
Entropy | |
Integral Features | [23] |
Inter-axis Correlation Coefficients | |
Eigenvalues of Dominant Direction | [71] |
Frequency Features | |
Spectral Energy | E(FFT(X)) |
Spectral Centroid | |
Spectral Entropy | H(FFT(X)) |
Cepstral Coefficients | [24] |
Wavelet Features c | |
Tamura Coefficients | [72] |
Nyan Coefficients | [73] |
Sekine Coefficients | [74] |
Wang Coefficients | [75] |
Fractal Dimension | [76] |
Preece Coefficients | [77] |
Appendix B. Confusion Matrices
Appendix B.1. Experiment 2: SVM and LSTM Confusion Matrices
Appendix B.2. Experiment 3: Confusion Matrices
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Terrain Label | Total No. of Samples |
---|---|
Concrete, Flat | 12,200 |
Concrete, Camber, Parallel | 3923 |
Concrete, Downhill | 2549 |
Concrete, Uphill | 2427 |
Grass, Flat | 1346 |
Concrete, Camber, Perpendicular | 877 |
Upstairs | 691 |
Downstairs | 656 |
Concrete, Camber, Downhill, Parallel | 572 |
Concrete, Camber, Uphill, Parallel | 540 |
Stone, Flat | 496 |
Sand, Flat | 232 |
Stone, Uphill | 176 |
Grass, Downhill | 151 |
Concrete, Camber, Downhill, Perpendicular | 93 |
Concrete, Camber, Uphill, Perpendicular | 93 |
Stone, Downhill | 80 |
Grass, Uphill | 78 |
Gravel, Downhill | 46 |
Gravel, Flat | 32 |
Sand, Uphill | 31 |
Red Ash, Flat | 26 |
Sand, Downhill | 12 |
Gravel, Uphill | 3 |
Classifier | Parameters Tuned |
---|---|
SVM | Kernel Type, Box Size |
KNN | Number of neighbours, Distance Metric, Distance Weight |
Random Forest | Maximum number of learners, maximum number of splits |
AdaBoost | Maximum number of learners, maximum number of splits, learning rate |
Naïve-Bayes | Type of distribution, Type of kernel (for kernel distribution) |
Discriminant Analysis | Type of discriminant analysis (Linear, Quadratic) |
LSTM | Dropout factor, Number of Hidden Units |
Participant | Height (m) | Weight (kg) | Age (Years) | Gender |
---|---|---|---|---|
#1 | 1.80 | 84 | 24 | Male |
#2 | 1.65 | 63 | 51 | Female |
#3 | 1.62 | 65 | 18 | Female |
#4 | 1.97 | 99 | 25 | Male |
#5 | 1.92 | 102 | 25 | Male |
#6 | 1.83 | 89 | 24 | Male |
#7 | 1.84 | 88 | 25 | Male |
#8 | 1.78 | 98 | 25 | Male |
Participant | Height (m) | Weight (kg) | Age (years) | Gender | Type of Amputation | Type of Prosthesis | Origin | Years since Amputation |
---|---|---|---|---|---|---|---|---|
#1 | 1.79 | 95 | 55 | Male | Unilateral transtibial | TSB socket, ESR foot | Traumatic | 3 |
#2 | 1.70 | 86 | 57 | Male | Unilateral transtibial | TSB socket, ESR foot | Traumatic | 32 |
#3 | 1.72 | 110 | 40 | Male | Unilateral transtibial | PTB socket, ESR foot | Traumatic | 33 |
#4 | 1.52 | 61 | 48 | Female | Bilateral transtibial | TSB socket, ESR foot | Vascular | 4 |
Classifier | 5-Fold Accuracy (%) | Fold Std. (±%) | Best Parameters |
---|---|---|---|
SVM | 77.22 | 0.54 | Kernel: Gaussian | Box Constraint: 193 |
KNN | 75.76 | 2.26 | Num. Neighbours: 12 | Distance Metric: Correlation | Distance Weight: Squared Inverse |
Random Forest | 71.84 | 0.69 | Num. Learners: 188 | Num. Splits: 4392 |
Adaboost | 69.23 | 3.18 | Num. Learners: 211 | Num. Splits: 910 | Learn Rate: 0.07 |
NB | 64.40 | 0.95 | Gaussian Kernel Distribution |
LDA | 73.91 | 0.93 | Quadratic |
LSTM | 78.46 | 2.89 | Dropout Factor: 0.2 | Num. Hidden Units: 190 |
Label Resolution Level | 1 | 2 | 3 |
---|---|---|---|
SVM accuracy (%) | 77.22 ± 0.54 | 62.60 ± 2.73 | 32.74 ± 2.46 |
LSTM accuracy (%) | 78.46 ± 2.89 | 73.77 ± 1.83 | 41.85 ± 4.19 |
Activity | No. of Test Samples | LSTM F1 Scores | SVM F1 Scores |
---|---|---|---|
Downstairs | 131 | 80.0 | 74.6 |
Upstairs | 138 | 80.1 | 75.7 |
Flat | 3826 | 83.8 | 84.2 |
Uphill | 670 | 68.7 | 69.9 |
Downhill | 701 | 62.8 | 61.7 |
Activity | No. of Test Samples | LSTM F1 Scores | SVM F1 Scores |
---|---|---|---|
Downstairs | 131 | 80.3 | 75.8 |
Upstairs | 138 | 77.4 | 75.1 |
Hard, Flat | 3506 | 80.2 | 82.3 |
Hard, Uphill | 647 | 69.9 | 70.8 |
Hard, Downhill | 668 | 63.1 | 61.5 |
Soft, Flat | 321 | 57.1 | 61.3 |
Soft, Uphill | 22 | 27.1 | 36.2 |
Soft, Downhill | 33 | 27.6 | 36.7 |
Activity | No. of Test Samples | LSTM F1 Scores | SVM F1 Scores |
---|---|---|---|
Concrete, Camber, Downhill, Parallel | 114 | 34.8 | 38.0 |
Concrete, Camber, Downhill, Perpendicular | 19 | 3.7 | 0.0 |
Concrete, Camber, Parallel | 784 | 50.8 | 62.3 |
Concrete, Camber, Perpendicular | 176 | 8.9 | 4.4 |
Concrete, Camber, Uphill, Parallel | 108 | 39.3 | 50.5 |
Concrete, Camber, Uphill, Perpendicular | 18 | 3.2 | 0.0 |
Concrete, Downhill | 510 | 48.1 | 58.3 |
Concrete, Flat | 2440 | 42.4 | 72.5 |
Concrete, Uphill | 485 | 55.5 | 69.5 |
Downstairs | 132 | 71.5 | 74.9 |
Grass, Downhill | 30 | 31.5 | 37.1 |
Grass, Flat | 269 | 51.0 | 62.6 |
Grass, Uphill | 16 | 25.1 | 29.1 |
Gravel, Downhill | 9 | 17.8 | 24.2 |
Gravel, Flat | 6 | 7.4 | 0.0 |
Gravel, Uphill | 1 | 0.0 | 0.0 |
Red Ash, Flat | 5 | 17.4 | 25.0 |
Sand, Downhill | 2 | 0.0 | 0.0 |
Sand, Flat | 47 | 33.3 | 52.0 |
Sand, Uphill | 6 | 18.6 | 27.0 |
Stone, Downhill | 16 | 15.9 | 9.4 |
Stone, Flat | 99 | 18.4 | 19.4 |
Stone, Uphill | 35 | 38.3 | 41.3 |
Upstairs | 139 | 69.4 | 73.4 |
Participant | A1 | A2 | A3 | A4 | Mean | Inter-Subject Std. |
---|---|---|---|---|---|---|
SVM accuracy (%) | 52.41 | 60.92 | 46.44 | 58.41 | 54.55 | ±5.61 |
LSTM accuracy (%) | 24.97 | 48.71 | 14.79 | 25.60 | 28.52 | ±12.42 |
Participant | A1 | A2 | A3 | A4 | Mean | Inter-Subject Std. |
---|---|---|---|---|---|---|
SVM accuracy (%) | 58.12 | 52.99 | 54.08 | 61.55 | 56.68 | ±3.40 |
LSTM accuracy (%) | 53.97 | 10.26 | 43.22 | 16.96 | 31.10 | ±18.06 |
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Jamieson, A.; Murray, L.; Stankovic, L.; Stankovic, V.; Buis, A. Human Activity Recognition of Individuals with Lower Limb Amputation in Free-Living Conditions: A Pilot Study. Sensors 2021, 21, 8377. https://doi.org/10.3390/s21248377
Jamieson A, Murray L, Stankovic L, Stankovic V, Buis A. Human Activity Recognition of Individuals with Lower Limb Amputation in Free-Living Conditions: A Pilot Study. Sensors. 2021; 21(24):8377. https://doi.org/10.3390/s21248377
Chicago/Turabian StyleJamieson, Alexander, Laura Murray, Lina Stankovic, Vladimir Stankovic, and Arjan Buis. 2021. "Human Activity Recognition of Individuals with Lower Limb Amputation in Free-Living Conditions: A Pilot Study" Sensors 21, no. 24: 8377. https://doi.org/10.3390/s21248377