https://github.com/didierrlopes/step-detection-ml
Step Detection using SVM on NURVV trackers
https://github.com/didierrlopes/step-detection-ml
ensemble-learning exploratory-data-analysis imu-sensor kmeans-clustering machine-learning sensor-fusion step-detection svm
Last synced: about 1 year ago
JSON representation
Step Detection using SVM on NURVV trackers
- Host: GitHub
- URL: https://github.com/didierrlopes/step-detection-ml
- Owner: DidierRLopes
- License: mit
- Created: 2021-12-06T15:10:29.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2022-02-01T10:58:07.000Z (over 4 years ago)
- Last Synced: 2025-01-24T08:25:33.200Z (over 1 year ago)
- Topics: ensemble-learning, exploratory-data-analysis, imu-sensor, kmeans-clustering, machine-learning, sensor-fusion, step-detection, svm
- Language: Jupyter Notebook
- Homepage:
- Size: 14 MB
- Stars: 4
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Step Detection using SVM on NURVV trackers
| Notebook | Description |
| :--- | :--- |
| [Nurvv Classifier](https://github.com/DidierRLopes/step-detection-SVM/blob/main/Nurvv_Classifier.ipynb) | Understand Nurvv IMU samples, and if there's a way to classify step/no-step using an unsupervised method. |
| [Nurvv K-Means and Feature Extraction](https://github.com/DidierRLopes/step-detection-SVM/blob/main/Nurvv_KMeansFeatureExtraction.ipynb) | Extract insights from K-Means on Nurvv IMU data and try some feature extraction. |
| [Nurvv from EDA to SVM](https://github.com/DidierRLopes/step-detection-SVM/blob/main/Nurvv_fromEDAtoSVM.ipynb) | Reports the entire journey from performing Exploratory Data Analysis (EDA) on the IMU samples, to the signal processing used to label data, and to finally applying Support Vector Machine (SVM) to classify the samples of a model into step or no-step. |
| [Nurvv Pipeline](https://github.com/DidierRLopes/step-detection-SVM/blob/main/Nurvv_Pipeline.ipynb) | Implement a data pipeline to perform ensemble SVM with multiple models. |
## Citation
`Lopes, D., & Trewartha, G. (2021, December). Step Detection using SVM on NURVV Trackers. In 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 351-356). IEEE.`
```
@inproceedings{lopes2021step,
title={Step Detection using SVM on NURVV Trackers},
author={Lopes, Didier and Trewartha, Grant},
booktitle={2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)},
pages={351--356},
year={2021},
organization={IEEE}
}
```