Machine Learning Model for Predicting Falls in Elderly Persons.
The dataset is sourced from falls incident reports and clinical information from the cStick data file which contains the following parameters
- Distance
- Pressure
- HRV
- Sugar Levels
- Accelerometer readings, etc.
Different machine learning methodologies such as Logistic Regression, SVM, Random Forest, Naive Bayes and more were used to develop models to proactively predict and possibly prevent fall incidents.
Live Predictor Application deployed using Streamlit. Live Predictor App Here