System and method for movement data analysis and monitoring
A method for biomechanical data analysis and monitoring is provided. Movement data is collected from one or more wearable devices associated with a user. Environmental data is integrated with the movement data by correlating the environmental data with specific points of the movement data. A power spectral profile is built for the user based on the movement data and environmental data, and includes a movement profile for the user. The power spectra is correlated with environmental factors and with data reported by the user. Variations of the power spectral profile are provided based on the environmental factors.
1 . A method for biomechanical data analysis and monitoring, comprising:
obtaining movement data from one or more wearable devices associated with a user;
adding environmental data comprising outdoor conditions in which the movement data is obtained to the movement data by correlating the environmental data with specific points of the movement data;
building a power spectral profile for the user based on the movement data and environmental data, wherein the power spectral profile comprises one or more movement profiles, which vary based on different activities performed by the user, and peak power metrics, which each represent qualitative measurements;
correlating the power spectra with data reported by the user; and
providing variations of the power spectral profile based on the environmental factors.
2 . A method according to claim 1 , further comprising:
correlating the movement data and the environment data with external data from one or more third parties.
3 . A method according to claim 1 , further comprising:
training an AI model for the user using data collected for the user comprising one or more of user provided data, external data, the environmental data, and the movement data collected from one or more mobile devices associated with the user.
4 . A method according to claim 3 , further comprising:
obtaining the external data from one or more third parties via an application programming interface or a software development kit.
5 . A method according to claim 3 , wherein the one or more mobile devices each comprise one of a phone, laptop, tablet, smart headphones, health monitor, and smart glasses.
6 . A method according to claim 1 , further comprising:
labelling segments of the movement data with an activity type.
7 . A method according to claim 1 , wherein the movement data comprises one or more of time, acceleration, angular velocity/rotation, attitude, altitude, elevation and global positioning satellite data.
8 . A method according to claim 1 , further comprising:
utilizing the power spectra profile to make a prediction of injury; and
notifying the user based on the prediction.
9 . A method according to claim 8 , further comprising:
calculating a value for the prediction of injury to the user based on the power spectral profile.
10 . A method according to claim 1 , wherein the power spectra varies by day of week, location, surface type, weather, velocity, pain or injury, and over time.