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Using the concepts of signal processing, machine learning and neural networks, predicting the motor activity(running,walking,jumping,climbing) of an individual using data collected by accelerometer and gyroscope, by applying time-series analysis

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ronak66/Activity-Classification

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Activity-Classification

Using the concepts of signal processing, machine learning and neural networks trying to predict the motor activity (running,walking,jumping,climbing) of an individual using data collected by accelerometer and gyroscope.
Accelerometer and Gyroscope values are obtained from the sensors in your phone.

Data

Data set contains values gathered by sensors like accelerometer and gyroscope present in mobile devices. Data is collected by actually performing all the motor activities.

Installation

  1. Tensor Flow
pip3 install --user --upgrade tensorflow
  1. Install keras
pip3 install keras
  1. Sklearn
pip3 install -U scikit-learn

Steps

  • Run python3 model.py

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Using the concepts of signal processing, machine learning and neural networks, predicting the motor activity(running,walking,jumping,climbing) of an individual using data collected by accelerometer and gyroscope, by applying time-series analysis

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