Isometric Plantarflexion Moment Prediction SVR
2021
- 144Usage
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage144
- Views133
- Downloads11
Dataset Description
1. Data collection during isometric ankle joint plantarflexion at 5 different postures, incluidng sEMG raw signals, ultrasound imaging videos, joint moment measurements from nine able-bodied participants. 2. sEMG signal time-domain features extraction and ultrasound imaging structural and functional features extraction results. 3. Correlation analysis results between each neuromuscular feature and measured ankle joint plantarflexion moment. 4. Illustrative support vector machine regresion (SVR) and deep feedforward neural network (FFNN) models training and prediction code and results, including the saved results in .mat files, root mean square error and R-square values between trained and measured joint moments, as well as between predicted and measured joint moment. 5. SVR and FFNN regression models training and prediction results summary for individual participant.
Bibliographic Details
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