SYSTEMS AND METHODS FOR ASSESSING TEAM DYNAMICS AND EFFECTIVENESS

• US 20110213211A1
• Filed: 12/28/2010
• Published: 09/01/2011
• Est. Priority Date: 12/29/2009
• Status: Active Grant

• Current Assignee: Advanced Brain Monitoring
• Original Assignee: Advanced Brain Monitoring
• Inventors: Berka, Christine, Stevens, Ronald H., Behneman, Adrienne, Levendowski, Daniel
• Granted Patent: US 9,836,703 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: G06Q 10/00 Administration; Management

Abstract

Techniques for monitoring neurophysiologic indicators of the members of a team while performing one or more collaborative tasks, for analyzing the collected neurophysiologic data and environmental data, for generating feedback, and for generating assessments of the performance of the team based on the collected data are provided. Feedback can be created based on the assessments of the team performance. Assessments of team performance can be performed in real time and feedback can also be provided in real time. In other embodiments, feedback can be provided to team members and/or the team as a whole after training exercise and/or simulation has been completed.

Claims

1. A computer-implemented method for monitoring and analyzing neurophysiologic indicators of a team, where one or more processors are programmed to perform the steps comprising:

receiving sensor data representing neurophysiologic data collected from the members of a team while the team is performing one or more collaborative tasks;

analyzing the sensor data to identify neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks;

generating feedback for at least one member of the team based on the identified neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks.

2. The method of claim 1, further comprising:

generating at least one performance report providing a visualization of the neurophysiologic synchronies exhibited by the team during the performance of the one or more collaborative tasks.

3. The method of claim 2, further comprising:

receiving environmental condition data related to the environment in which the team is performing the one or more collaborative tasks collected while the team is performing the one or more collaborative tasks;

identifying events occurring during the performance of the one or more collaborative tasks using the environmental condition data;

correlating the neurophysiologic synchronies exhibited by the team with one or more identified events that occurred during the course of the performance of the one or more collaborative tasks to generate event interpretation data for the team; and

wherein generating the at least one performance report includes generating a map providing a visual representation of the association of neurophysiologic synchronies exhibited by the team during the one or more events.

4. The method of claim 3, further comprising:

correlating event interpretation data with expert data to assess the performance of the team in response to the one or more events.

5. The method of claim 3, further comprising:

correlating event interpretation data for the team with event interpretation data from a previous session to assess improvement in learning by the team.

6. The method of claim 3, further comprising:

correlating event interpretation data for the team with event interpretation data for a second team performing the one or more collaborative tasks to assess the performance of the team in comparison to the second team.

7. The method of claim 1 wherein analyzing the sensor data to identify neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks further comprises:

normalizing data collected for the team.

8. The method of claim 7 wherein normalizing the data further comprises:

calculating z-scores for each team member for each of a plurality of epochs;

partitioning the data for each team member into a normalized data vector based on the z-scores;

generating a normalized data vector for the team based by combining the normalized data vectors of the team members.

9. The method of claim 8 wherein analyzing the sensor data to identify neurophysiologic synchronies further comprises:

training an artificial neural network using the normalized data vector for the team to partition the normalized data vector into a set of neurophysiologic synchronies;

generating a map of the neurophysiologic synchronies for the team and a frequency map indicating the number of times that each of the neurophysiologic synchronies was expressed by the team during the one or more collaborative tasks.

10. The method of claim 1 wherein the one or more collaborative tasks comprise a simulation.

11. The method of claim 10 wherein the simulation comprising a training exercise, and wherein generating at least one performance report further comprising assessing the performance of the team in learning at least one skill.

12. The method of claim 1 wherein the one or more task comprise changing task events, and wherein generating at least one performance report further comprising assessing the performance of the team in response to the changing task events.

13. The method of claim 1 wherein the feedback generated is generated based on a task specific metric associated with a task specific metric associated with the at least one collaborative task performed by the team, wherein the task specific metric identifies a neurophysiologic state that should have been exhibited by the team while performing the at least one collaborative task.

14. The method of claim 1 wherein the feedback generated is generated based on a team metric associated with good performance of a team, wherein the team specific metric indentifies a neurophysiologic state that should have been exhibited while performing the at least one collaborative task.

15. The method of claim 1 wherein the feedback is provided to an instructor monitoring the team'"'"'s performance of the at least one collaborative

16. The method of claim 1 wherein the feedback is tactile feedback provided by a haptic device.

17. The method of claim 1 wherein the feedback is provided is audiovisual feedback.

18. The method of claim 1 further comprising:

receiving additional sensor data representing neurophysiologic data collected from the members of a team after providing the feedback to the at least one member of the team;

analyzing the additional sensor data to identify neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks after receiving the feedback;

generating at least one performance report providing a visualization of the neurophysiologic synchronies exhibited by the team during the performance of the one or more collaborative tasks after the feedback was provided in order to determine whether improvement in team performance has resulted from the feedback.

19. A technical system for monitoring and analyzing neurophysiologic indicators of a team, the system comprising:

a plurality of sensors configured to collect neurophysiologic data from members of a team and to output a signal representing a neurophysiologic data collected from each team member while the team member is performing one or more collaborative tasks;

a data analysis server comprising a non-transitory computer readable medium configured to store executable programmed modules and a processor configured to execute programmed modules stored therein, wherein the data analysis server further comprises;

a data interface module stored in the non-transitory computer readable medium and configured to receive sensor data collected by the plurality of sensors and to receive environmental condition data related to the environment in which the one or more collaborative tasks are performed by the team;

a data analysis module stored in the non-transitory computer readable medium and configured to identify events that occurred during the performance of the one or more collaborative tasks based on the external condition data and to analyze the sensor data to identify neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks; and

a feedback module stored in the non-transitory computer readable medium and configured to generate feedback for at least one member of the team based on the identified neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks.

20. The system of claim 19, further comprising:

a monitoring device configured to receive sensor data from sensors, to store the sensor data during at least a portion of the performing the one or more collaborative tasks, wherein the monitoring device is configured to transmit the received sensor data to the data analysis server.

21. The system of claim 20 wherein the monitoring device is configured to wirelessly transmit the sensor data to the data analysis server.

22. The system of claim 19, wherein the data analysis server further comprises:

a report generation module stored in the non-transitory computer readable medium and configured to generate at least one performance report providing a visualization of the neurophysiologic synchronies exhibited by the team during the performance of the one or more collaborative tasks.

23. The system of claim 22 wherein the data analysis module is further configured to correlate the neurophysiologic synchronies exhibited by the team with one or more events that occurred during the course of the performing the one or more collaborative tasks to generate event interpretation data for the team;

and

wherein the report generation module is further configured to generate a map providing a visual representation of the association of neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks.

24. The system of claim 22 wherein the data analysis module is further configured to correlate event interpretation data with expert data to assess the performance of the team in response to the one or more events.

25. The system of claim 22 wherein the data analysis module is further configured to correlate event interpretation data for the team with event interpretation data from a previous session to assess improvement in learning by the team.

26. The system of claim 22 wherein the data analysis module is further configured to correlate correlating event interpretation data for the team with event interpretation data for a second team performing the one or more collaborative tasks to assess the performance of the team in comparison to the second team.

27. The system of claim 22 wherein the data analysis module is configured to normalize sensor data collected for the team before analyzing the sensor data to identify neurophysiologic synchronies exhibited by the team.

28. The system of claim 27 wherein the data analysis module, when normalizing sensor data, is further configured to:

calculate z-scores for each team member for each of a plurality of epochs;

partition the data for each team member into a normalized data vector based on the z-scores;

generate a normalized data vector for the team based by combining the normalized data vectors of the team members.

29. The system of claim 28 wherein the data analysis module, when analyzing the sensor data to identify neurophysiologic synchronies, is further configured to:

train an artificial neural network using the normalized data vector for the team to partition the normalized data vector into a set of neurophysiologic synchronies;

generate a map of the neurophysiologic synchronies for the team and a frequency map indicating the number of times that each of the neurophysiologic synchronies was expressed by the team during the one or more collaborative tasks.

30. The system of claim 22 wherein the one or more collaborative tasks comprise a simulation.

31. The system of claim 30 wherein the simulation comprising a training exercise, and wherein the report generation module is configured to generate at least one performance report assessing the performance of the team in learning at least one skill.

32. The system of claim 22 wherein the one or more task comprise changing task events, and wherein the report generation module is configured to generate at least one performance report assessing the performance of the team in response to the changing task events.

33. The system of claim 19 wherein the feedback module is configure to generate feedback based on a task specific metric associated with a task specific metric associated with the at least one collaborative task performed by the team, wherein the task specific metric identifies a neurophysiologic state that should have been exhibited by the team while performing the at least one collaborative task.

34. The system of claim 19 wherein the feedback module is configured to generate feedback based on a team metric associated with good performance of a team, wherein the team specific metric indentifies a neurophysiologic state that should have been exhibited while performing the at least one collaborative task.

35. The system of claim 19 wherein the feedback module is configured to provide feedback to an instructor monitoring the team'"'"'s performance of the at least one collaborative

36. The system of claim 19 wherein the feedback module is configured to generate a control signal to a haptic device to provide tactile feedback to a team member.

37. The system of claim 19 wherein the feedback module is configured to provide audiovisual feedback.

38. The system of claim 22 wherein the data interface module is configured to receive additional sensor data representing neurophysiologic data collected from the members of a team after providing the feedback to the at least one member of the team;

wherein the data analysis module is further configured to analyze the additional sensor data to identify neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks after receiving the feedback; and

wherein the report generation module is further configured to generate at least one performance report providing a visualization of the neurophysiologic synchronies exhibited by the team during the performance of the one or more collaborative tasks after the feedback was provided in order to determine whether improvement in team performance has resulted from the feedback.

39. A computer-implemented method for monitoring and analyzing neurophysiologic indicators of a team, where one or more processors are programmed to perform the steps comprising:

receiving sensor data representing neurophysiologic data collected from the members of a team while the team is performing one more tasks, the sensor data comprising a plurality of neurophysiologic metrics collected from each member of the team;

analyzing the sensor data to identify neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks, wherein analyzing the sensor data to identify neurophysiologic synchronies exhibited by the team includes combining the plurality of neurophysiologic metrics collected from each of the members of the team into each neurophysiologic synchrony exhibited by the team; and

generating feedback for at least one member of the team based on the identified neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks.

40. The method of claim 39, further comprising:

generating at least one performance report providing a visualization of the neurophysiologic synchronies exhibited by the team during the performance of the one or more collaborative tasks.

41. The method of claim 39 wherein combining the plurality of neurophysiologic metrics collected from each of the members of the team into each neurophysiologic synchrony exhibited by the team further comprises:

normalizing data collected for the team.

42. The method of claim 41 wherein normalizing the data further comprises:

calculating z-scores for each of the plurality of neurophysiologic metrics for each team member for each of a plurality of epochs;

partitioning the data for each of the plurality of metrics each team member into a normalized data vector based on the z-scores;

generating a normalized data vector for the team based by combining the normalized data vectors of the team members.

43. The method of claim 42 wherein analyzing the sensor data to identify neurophysiologic synchronies further comprises:

training an artificial neural network using the normalized data vector for the team to partition the normalized data vector into a set of neurophysiologic synchronies that include each of the plurality of metrics collected for each of the team members;

generating a map of the neurophysiologic synchronies for the team and a frequency map indicating the number of times that each of the neurophysiologic synchronies was expressed by the team during the one or more collaborative tasks.

44. The method of claim 39 wherein the feedback generated is generated based on a task specific metric associated with a task specific metric associated with the at least one collaborative task performed by the team, wherein the task specific metric identifies a neurophysiologic state that should have been exhibited by the team while performing the at least one collaborative task.

45. The method of claim 39 wherein the feedback generated is generated based on a team metric associated with good performance of a team, wherein the team specific metric indentifies a neurophysiologic state that should have been exhibited while performing the at least one collaborative task.

46. The method of claim 39 wherein the feedback is provided to an instructor monitoring the team'"'"'s performance of the at least one collaborative

47. The method of claim 39 wherein the feedback is tactile feedback provided by a haptic device.

48. The method of claim 39 wherein the feedback is provided is audiovisual feedback.

49. The method of claim 39 further comprising:

receiving additional sensor data representing neurophysiologic data collected from the members of a team after providing the feedback to the at least one member of the team;

analyzing the additional sensor data to identify neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks after receiving the feedback;

generating at least one performance report providing a visualization of the neurophysiologic synchronies exhibited by the team during the performance of the one or more collaborative tasks after the feedback was provided in order to determine whether improvement in team performance has resulted from the feedback.

50. A technical system for monitoring and analyzing neurophysiologic indicators of a team, the system comprising:

a plurality of sensors configured to collect neurophysiologic data from members of a team and to output a signal representing a neurophysiologic data collected from each team member while the team member is performing one or more collaborative tasks, the sensor data comprising a plurality of neurophysiologic metrics collected from each member of the team;

a data analysis server comprising a non-transitory computer readable medium configured to store executable programmed modules and a processor configured to execute programmed modules stored therein, wherein the data analysis server further comprises;

a data interface module stored in the non-transitory computer readable medium and configured to receive sensor data collected by the plurality of sensors and to receive environmental condition data related to the environment in which the one or more collaborative tasks are performed by the team;

a data analysis module stored in the non-transitory computer readable medium and configured to identify events that occurred during the performance of the one or more collaborative tasks based on the external condition data and to analyze the sensor data to identify neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks, wherein analyzing the sensor data to identify neurophysiologic synchronies exhibited by the team includes combining the plurality of neurophysiologic metrics collected from each of the members of the team into each neurophysiologic synchrony exhibited by the team; and

a feedback module stored in the non-transitory computer readable medium and configured to generate feedback for at least one member of the team based on the identified neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks.

51. The system of claim 50, wherein the data analysis server further comprises:

a report generation module stored in the non-transitory computer readable medium and configured to generate at least one performance report providing a visualization of the neurophysiologic synchronies exhibited by the team during the performance of the one or more collaborative tasks.

52. The system of claim 50 wherein the data analysis module is configured to normalize sensor data collected for the team before analyzing the sensor data to identify neurophysiologic synchronies exhibited by the team.

53. The system of claim 52 wherein the data analysis module, when normalizing sensor data, is further configured to:

calculate z-scores for each of the plurality of neurophysiologic metrics for each team member for each of a plurality of epochs;

partition the data for each of the plurality of metrics each team member into a normalized data vector based on the z-scores;

generate a normalized data vector for the team based by combining the normalized data vectors of the team members.

54. The system of claim 53 wherein the data analysis module, when analyzing the sensor data to identify neurophysiologic synchronies, is further configured to:

train an artificial neural network using the normalized data vector for the team to partition the normalized data vector into a set of neurophysiologic synchronies that include each of the plurality of metrics collected for each of the team members;

generate a map of the neurophysiologic synchronies for the team and a frequency map indicating the number of times that each of the neurophysiologic synchronies was expressed by the team during the one or more collaborative tasks.

55. The system of claim 50 wherein the feedback module is configure to generate feedback based on a task specific metric associated with a task specific metric associated with the at least one collaborative task performed by the team, wherein the task specific metric identifies a neurophysiologic state that should have been exhibited by the team while performing the at least one collaborative task.

56. The system of claim 50 wherein the feedback module is configured to generate feedback based on a team metric associated with good performance of a team, wherein the team specific metric indentifies a neurophysiologic state that should have been exhibited while performing the at least one collaborative task.

57. The system of claim 50 wherein the feedback module is configured to provide feedback to an instructor monitoring the team'"'"'s performance of the at least one collaborative

58. The system of claim 50 wherein the feedback module is configured to generate a control signal to a haptic device to provide tactile feedback to a team member.

59. The system of claim 50 wherein the feedback module is configured to provide audiovisual feedback.

60. The system of claim 51 wherein the data interface module is configured to receive additional sensor data representing neurophysiologic data collected from the members of a team after providing the feedback to the at least one member of the team;

wherein the data analysis module is further configured to analyze the additional sensor data to identify neurophysiologic synchronies exhibited by the team while performing the one or more collaborative tasks after receiving the feedback; and

wherein the report generation module is further configured to generate at least one performance report providing a visualization of the neurophysiologic synchronies exhibited by the team during the performance of the one or more collaborative tasks after the feedback was provided in order to determine whether improvement in team performance has resulted from the feedback.