Accelerometer Data Analysis for Gait and Health Monitoring
Budget: $10 – $30 CAD
My project involves data analysis of accelerometer data for a variety of purposes. Your primary focus will be on gait analysis and monitoring health and behavior data.
Key responsibilities and requirements include:
- Conducting in-depth analysis of the provided accelerometer data to identify abnormal walking patterns.
- Using the data to monitor health conditions.
- Analyzing behavior data related to lying, standing, and resting.
Ideal skills and experiences for this project include:
- Proficiency with data analysis tools and techniques.
- Experience working with accelerometer data or similar data types.
- Strong understanding of health monitoring and gait analysis.
- Ability to derive meaningful insights from behavioral patterns.
- Prior work with identifying abnormal patterns in data.
This project offers you the opportunity to work on cutting-edge research that could potentially impact sports performance, health, and behavior studies. I have data in 4 excel (csv) files - results of accelerometer data - also have python script for this - quick job - do time series analysis - Analyze the temporal patterns of the activity metrics. - Analyze walking patterns, including step length and symmetry - Examine differences in daily activity patterns - Identify indicators of altered behavior. - Show trends over time - plot activity metrics for each file based on the two group or two categories
Show distribution and variability of activity metrics - show box plots for step counts - compare distribution of
step counts between the two types and compare the distribution of resting times
Histogram for step counts - compare frequency distribution of step counts and also frequency distribution of activity intensity counts -
Correlation Heatmaps - between different activity metrics -
bar plots - compare mean activity metrics between lame and healthy cows - mean step counts - mean rest times -
scatter plots of step count vs activity intensity - - compare relationship for the two categories
-
python code to generate plots and visuals will be shared
Key responsibilities and requirements include:
- Conducting in-depth analysis of the provided accelerometer data to identify abnormal walking patterns.
- Using the data to monitor health conditions.
- Analyzing behavior data related to lying, standing, and resting.
Ideal skills and experiences for this project include:
- Proficiency with data analysis tools and techniques.
- Experience working with accelerometer data or similar data types.
- Strong understanding of health monitoring and gait analysis.
- Ability to derive meaningful insights from behavioral patterns.
- Prior work with identifying abnormal patterns in data.
This project offers you the opportunity to work on cutting-edge research that could potentially impact sports performance, health, and behavior studies. I have data in 4 excel (csv) files - results of accelerometer data - also have python script for this - quick job - do time series analysis - Analyze the temporal patterns of the activity metrics. - Analyze walking patterns, including step length and symmetry - Examine differences in daily activity patterns - Identify indicators of altered behavior. - Show trends over time - plot activity metrics for each file based on the two group or two categories
Show distribution and variability of activity metrics - show box plots for step counts - compare distribution of
step counts between the two types and compare the distribution of resting times
Histogram for step counts - compare frequency distribution of step counts and also frequency distribution of activity intensity counts -
Correlation Heatmaps - between different activity metrics -
bar plots - compare mean activity metrics between lame and healthy cows - mean step counts - mean rest times -
scatter plots of step count vs activity intensity - - compare relationship for the two categories
-
python code to generate plots and visuals will be shared