Methods and systems for predicting injury risk include generating state sequences that precede a hazard event based on information regarding a user's state. A cognitive suite of workplace hygiene and injury predictors (WHIP) is generated based on the state sequences using a processor, wherein the cognitive WHIP predicts a degree of risk correlated with each particular user state sequence. A risk heat map of a workplace is generated based on the cognitive WHIP that encodes regions of greater and lesser risk. An ameliorative action is triggered when a user moves into an area of high risk based on the heat map.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for predicting injury risk, comprising: generating state sequences that precede a hazard event based on information regarding a user's state; generating a cognitive suite of workplace hygiene and injury predictors (WHIP) based on the state sequences using a processor, wherein the cognitive WHIP predicts a degree of risk correlated with each particular user state sequence; generating a risk heat map of a workplace based on the cognitive WHIP that encodes regions of greater and lesser risk; and triggering an ameliorative action when a user moves into an area of high risk based on the heat map. 2. The method of claim 1, wherein generating the cognitive WHIP comprises determining state sequences that are related to the hazard event by supervised learning. 3. The method of claim 1, wherein triggering the ameliorative action comprises activating one or more automated system to decrease or mitigate risk to the user. 4. The method of claim 1, wherein triggering the ameliorative action comprises providing information to the user regarding the area of high risk. 5. The method of claim 1, wherein triggering the ameliorative action comprises changing a setting in one or more device in the workplace to decrease a risk in the area of high risk. 6. The method of claim 1, further comprising gathering user state information from a device worn by the user. 7. The method of claim 6, wherein the user state information comprises biometric information relating to at least one measurable aspect of the user's physical or cognitive state. 8. The method of claim 1, further comprising gathering user state information from one or more workplace monitoring devices. 9. The method of claim 8, wherein the user state information comprises user location within the workplace. 10. A computer readable storage medium comprising a computer readable program for predicting injury risk, wherein the computer readable program when executed on a computer causes the computer to perform the steps of claim 1. 11. A method for predicting injury risk, comprising: generating state sequences that precede a hazard event based on information regarding a user's state including user biometric information from a device worn by the user and a user's location from one or more workplace monitoring devices; generating a cognitive suite of workplace hygiene and injury predictors (WHIP) based on the state sequences using a processor and supervised learning, wherein the cognitive WHIP predicts a degree of risk correlated with each particular user state sequence; generating a risk heat map of a workplace based on the cognitive WHIP that encodes regions of greater and lesser risk; and triggering an ameliorative action when a user moves into an area of high risk based on the heat map. 12. A system for predicting injury risk, comprising: a cognitive suite of workplace hygiene and injury predictors (WHIP) module comprising a processor configured to generate state sequences that precede a hazard event based on information regarding a user's state and to generate a cognitive WHIP based on the state sequences, wherein the cognitive WHIP predicts a degree of risk correlated with each particular user state sequence; a heat map module configured to generate a risk heat map of a workplace based on the cognitive WHIP that encodes regions of greater and lesser risk; and an alert module configured to trigger an ameliorative action when a user moves into an area of high risk based on the cognitive WHIP. 13. The system of claim 12, wherein the cognitive WHIP is further configured to determining state sequences that are related to the hazard event by supervised learning. 14. The system of claim 12, wherein the alert module is further configured to activate one or more automated system to decrease or mitigate risk to the user. 15. The system of claim 12, wherein the alert module is further configured to provide information to the user regarding the area of high risk. 16. The system of claim 12, wherein the alert module is further configured to change a setting in one or more device in the workplace to decrease a risk in the area of high risk. 17. The system of claim 12, wherein the cognitive WHIP module is further configured to gather user state information from a device worn by the user. 18. The system of claim 17, wherein the user state information comprises biometric information relating to at least one measurable aspect of the user's physical or cognitive state. 19. The system of claim 12, wherein the cognitive WHIP module is further configured to gather user state information from one or more workplace monitoring devices. 20. The system of claim 19, wherein the user state information comprises user location within the workplace.