mr-easy / Badminton-Stroke-Classification
Classifying badminton strokes based on accelorometer and gyroscope sensor data attached to player's wrist. An end-to-end Machine Learning project, from data collection and preprocessing to final model evaluation.
☆21Updated 4 years ago
Alternatives and similar repositories for Badminton-Stroke-Classification:
Users that are interested in Badminton-Stroke-Classification are comparing it to the libraries listed below
- Deep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data. Human Activity Recognition Challenge. Springer …☆23Updated 3 years ago
- A set of standard ECG processing features described in 'Support vector machine-based arrhythmia classification using reduced features of …☆11Updated 6 years ago
- Some Machine Learning techniques for Time Series classification.☆38Updated 7 years ago
- deadskull7 / Human-Activity-Recognition-with-Neural-Network-using-Gyroscopic-and-Accelerometer-variablesThe VALIDATION ACCURACY is BEST on KAGGLE. Artificial Neural Network with a validation accuracy of 97.98 % and a precision of 95% was ach…☆84Updated 6 years ago
- Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).☆63Updated 2 years ago
- Database for human gait analysis consisting of continues recordings of combined activities, such as walking, running, taking stairs up an…☆91Updated 4 years ago
- Package for analyzing human motion data (e.g. PA, gait)☆90Updated 4 months ago
- Analysis of the SisFall fall detection dataset with readings from accelerometer and gyroscope.☆44Updated 6 years ago
- DANA: Dimension-Adaptive Neural Architecture (UbiComp'21)( ACM IMWUT)☆45Updated 3 years ago
- Human activity recognition, is a challenging time series classification task. It involves predicting the movement of a person based on se…☆75Updated 4 years ago
- Work in progress about activity recognition/prediction using wearable sensors information☆16Updated 4 years ago
- Human Activity Recognition Using Deep Learning☆48Updated 5 years ago
- An implementation of the CNN-LSTM model for Classifying Time Series Human Activities☆23Updated 4 years ago
- Code for our IJCAI 2019 paper "A Novel Distribution-Embedded Neural Network for Sensor-Based Activity Recognition".☆16Updated 4 years ago
- Motion Compensated Pulse Rate Estimation from PPG and Accelerometer Sensor Data☆17Updated 4 years ago
- ECGDL: A framework for comparative study of databases and computational methods for arrhythmia detection from single-lead ECG☆16Updated last year
- ☆12Updated 6 years ago
- ☆12Updated 4 years ago
- ECG Compression using Wavelet Transform and Variable Run-Length Encoding☆29Updated 2 years ago
- Udacity AI for Healthcare Nanodegree Project: Heart Rate Estimation Algorithm From PPG and Accelerometer data☆23Updated last year
- AROMA: A Deep Multi-Task Learning Based Simple and Complex Human Activity Recognition Method Using Wearable Sensors☆28Updated 6 years ago
- A new, short-recorded photoplethysmogram dataset for blood pressure monitoring in China☆20Updated 6 years ago
- Detecting sleep/awake state using wrist-worn accelerometer data☆11Updated 6 years ago
- Transformer Network for Time-Series, Sensor and Wearable Data☆26Updated 4 years ago
- DATA'20 - PPGraw is an analytical tool for the quality review of raw photoplethysmography (PPG) signals, based on 7 multi-varied decision…☆43Updated 4 years ago
- This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Sup…☆23Updated 2 years ago
- Human heart arrhythmia classification based on the MIT-BIH ECG data set with random Fourier feature GLM and kernel parameter estimation.☆34Updated 6 years ago
- Personalized machine learning on the smartphone☆59Updated last year
- Python implementations of machine learning algorithms for motion artifact detection in electrodermal activity (EDA) data☆17Updated 7 years ago
- Transformer for Human Activity Recognition☆70Updated 2 years ago