Methods and systems for individualized content media delivery
Aspects relate to systems and methods for individualized content media delivery. An exemplary system includes a sensor configured to detect a biofeedback signal as a function of a biofeedback of a user, a display configured to present content to the user, and a computing device configured to control an environmental parameter for an environment surrounding the user as a function of the biofeedback signal, wherein controlling the environmental parameter additionally includes generating an environmental machine-learning model as a function of an environmental machine-learning algorithm, training the environmental machine-learning model as a function of an environmental training set, wherein the environmental training set comprises biofeedback inputs correlated to environmental parameter outputs and generating the environmental parameter as a function of the biofeedback signal and the environmental machine-learning model.
1. A method of individualized content media delivery, the method comprising:
detecting, using at least a sensor, at least a biofeedback signal as a function of a biofeedback of a user;
presenting, using at least a display, content to the user; and
controlling, using at least a computing device, at least an environmental parameter for an environment of the user as a function of the at least a biofeedback signal, wherein the at least an environmental parameter comprises a thermal parameter and controlling the at least an environmental parameter further comprises:
generating an environmental machine-learning model as a function of an environmental machine-learning algorithm;
training the environmental machine-learning model as a function of an environmental training set, wherein the environmental training set comprises biofeedback inputs correlated to environmental parameter outputs; and
generating the at least an environmental parameter as a function of the at least a biofeedback signal and the environmental machine-learning model.
2. The method of claim 1 , further comprising:
controlling, using the computing device, at least a display parameter for the at least a display as a function of the at least a biofeedback signal, wherein controlling the at least a display parameter further comprises:
generating a display machine-learning model as a function of a display machine-learning algorithm;
training the display machine-learning model as a function of a display training set, wherein the display training set comprises biofeedback inputs correlated to display parameter outputs; and
generating the at least a display parameter as a function of the at least a biofeedback signal and the display machine-learning model.
3. The method of claim 2 , wherein the at least a display comprises an audio-visual display.
4. The method of claim 3 , wherein the at least a display parameter comprises an audio parameter.
5. The method of claim 2 , wherein the at least a display parameter comprises a speed of presentation for the content.
6. The method of claim 1 , wherein the at least an environmental parameter comprises a lighting parameter.
7. The method of claim 1 , further comprising:
classifying, using the computing device, a user state as a function of the at least a biofeedback signal, wherein classifying the state of the user further comprises:
generating a user state classifier as a function of a user state machine-learning algorithm;
training the user state classifier as a function of a user state training set; and
classifying the user state as a function of the user state classifier and the biofeedback signal;
wherein generating the at least an environmental parameter further comprises selectively generating the at least an environmental parameter as a function of the user state.
8. The method of claim 7 , wherein the user state is associated with attentiveness.
9. The method of claim 7 , further comprising:
generating, using the computing device, a confidence metric associated with classifying the user state.
10. A system for individualized content media delivery, the system comprising:
at least a sensor configured to detect at least a biofeedback signal as a function of a biofeedback of a user;
at least a display configured to present content to the user; and
at least a computing device configured to control at least an environmental parameter for an environment of the user as a function of the at least a biofeedback signal, wherein the at least an environmental parameter comprises a thermal parameter and controlling the at least an environmental parameter further comprises:
generating an environmental machine-learning model as a function of an environmental machine-learning algorithm;
training the environmental machine-learning model as a function of an environmental training set, wherein the environmental training set comprises biofeedback inputs correlated to environmental parameter outputs; and
generating the at least an environmental parameter as a function of the at least a biofeedback signal and the environmental machine-learning model.
11. The system of claim 10 , wherein the computing device is further configured to control at least a display parameter for the at least a display as a function of the at least a biofeedback signal, wherein controlling the at least a display parameter further comprises:
generating a display machine-learning model as a function of a display machine-learning algorithm;
training the display machine-learning model as a function of a display training set, wherein the display training set comprises biofeedback inputs correlated to display parameter outputs; and
generating the at least a display parameter as a function of the at least a biofeedback signal and the display machine-learning model.
12. The system of claim 11 , wherein the at least a display comprises an audio-visual display.
13. The system of claim 12 , wherein the at least a display parameter comprises an audio parameter.
14. The system of claim 11 , wherein the at least a display parameter comprises a speed of presentation for the content.
15. The system of claim 10 , wherein the at least an environmental parameter comprises a lighting parameter.
16. The system of claim 10 , further comprising:
classifying, using the computing device, a user state as a function of the at least a biofeedback signal, wherein classifying the user state further comprises:
generating a user state classifier as a function of a user state machine-learning algorithm;
training the user state classifier as a function of a user state training set; and
classifying the user state as a function of the user state classifier and the biofeedback signal;
wherein generating the at least an environmental parameter further comprises selectively generating the at least an environmental parameter as a function of the user state.
17. The system of claim 16 , wherein the user state is associated with attentiveness.
18. The system of claim 16 , wherein the computing device is further configured to generate a confidence metric associated with classifying the user state.