Abstract: An apparatus for human performance exhalation sensing, comprising a housing, wherein the housing comprises an inlet tube configured to receive exhaled gas from an individual, a sensing device positioned within the inlet tube, at least a processor, and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to receive performance data related to at least a task assigned to the individual, generate a performance metric of the individual as a function of the performance data, wherein the performance metric comprises a performance parameter associated with the at least a task, generate a breath profile of the individual as a function of data collected from the exhaled gas, generate a performance determination of the individual as a function of the performance parameter and the breath profile, and alert the individual based on the performance determination.

Abstract: In an aspect, an apparatus for bias eliminated performance determination is presented. An Apparatus includes at least a processor and a memory communicatively connected to the at least a processor. A memory includes instructions configuring at least a processor to receive, through a sensing device, biological feedback of a user. At least a processor is configured to compare biological feedback to a performance parameter of a task. At least a processor is configured to generate, as a function of a comparison, a performance determination through a performance determination machine learning model. At least a processor is configured to classify a performance determination to a bias category as a function of a bias classifier. At least a processor is configured to train a performance determination machine learning model with biological feedback and a bias classification of a performance determination.

Abstract: Aspects relate to systems and methods for determining actor status according to behavioral phenomena. An exemplary system includes at least an eye sensor, wherein the at least an eye sensor is configured to detect an eye parameter and at least a physiological sensor, wherein the at least a physiological sensor is configured to detect a circulatory parameter, and a processor in communication with the at least an eye speech sensor and the at least a physiological sensor and configured to determine an eye pattern as a function of the eye parameter and correlate the eye pattern and the circulatory parameter to a cognitive status.

Abstract: Aspects relate to systems and methods for correlating cutaneous activity with human performance. An exemplary system includes at least a cutaneous sensor configured to detect at least a cutaneous parameter as a function of a cutaneous phenomenon, a computing device in communication with the at least a cutaneous sensor and including a memory configured to store instructions and a processor configured to perform the instructions, wherein performing the instructions includes receiving, using the computing device, the at least a cutaneous parameter from the at least a cutaneous sensor and determining, using the computing device, at least a user performance parameter as a function of the at least a cutaneous parameter.

Abstract: In an aspect, an apparatus for human performance exhalation sensing is presented. An apparatus includes a housing. A housing includes an inlet tube configured to receive exhaled gas from an individual. A housing includes a sensing device positioned within an inlet tube, wherein the sensing device is configured to detect a breath parameter. A housing includes at least a processor and a memory communicatively connected to the at least a processor. A memory contains instructions configuring at least a processor to receive a breath parameter from a sensing device through a communicative connection. At least a processor is configured to compare a breath parameter to a performance metric. At least a processor is configured to generate a performance determination of an individual as a function of a comparison.

Abstract: Aspects relate to systems and methods for dynamic active noise reduction including at least a sensor configured to sense a physiological characteristic of a user and transmit a physiological signal correlated to the sensed physiological characteristic, at least an environmental microphone configured to transduce an environmental noise to an environmental noise signal, a processor configured to receive the environmental noise signal, generate a noise-reducing sound signal as a function of the environmental noise signal, and, modify the noise-reducing sound signal as a function of the physiological signal, and a speaker configured to transduce a noise-reducing sound from the modified noise-reducing sound signal.

Abstract: Aspects relate to system and methods for determining a user specific mission operational performance, using machine-learning processes.

Abstract: Aspects relate to systems and methods for determining actor status according to behavioral phenomena. An exemplary system includes at least an eye sensor, wherein the at least an eye sensor is configured to detect an eye parameter and at least a physiological sensor, wherein the at least a physiological sensor is configured to detect a circulatory parameter, and a processor in communication with the at least an eye speech sensor and the at least a physiological sensor and configured to determine an eye pattern as a function of the eye parameter and correlate the eye pattern and the circulatory parameter to a cognitive status.

Abstract: Aspects relate to methods and systems for detection of atelectasis in flight. An exemplary system includes at least an exhalation sensor configured to detect at least an exhalation parameter of a flight crew member, at least an inhalation sensor configured to detect at least an inhalation parameter of the flight crew member, at least an environmental sensor configured to detect at least an environmental parameter of a cabin within which the flight crew member is housed, and a computing device configured to determine a likelihood of atelectasis for the flight crew member as a function of the at least an exhalation parameter, the at least an inhalation parameter, and the at least an environmental parameter and generate a dosing schedule as a function of the likelihood of atelectasis.

Abstract: Aspects relate to systems and methods for determining actor status according to behavioral phenomena. An exemplary system includes an eye sensor configured to detect an eye parameter as a function of an eye phenomenon, a speech sensor configured to detect a speech parameter as a function of a speech phenomenon, and a processor in communication with the eye sensor and the speech sensor; the processor is configured to receive the eye parameter and the speech parameter, determine an eye pattern as a function of the eye parameter, determine a speech pattern as a function of the speech parameter, and correlate one or more of the eye pattern and the speech pattern to a cognitive status.

Abstract: Aspects relate to methods and systems for detecting imminent loss of consciousness. An exemplary system includes at least a respiratory sensor configured to detect a respiration parameter associated with a user, at least a circulatory sensor configured to detect a circulation parameter associated with the user, at least a processor configured to receive the at least a respiration parameter and the at least a circulation parameter, detect a condition associated with the user as a function of the at least a respiration parameter and the at least a circulation parameter, and identify an imminent loss of consciousness event associated with the user as a function of the at least a respiration parameter and the at least a circulation parameter, and at least a user interface configured to alert the user as a function of the imminent loss of consciousness event.

Abstract: Aspects relate to system and methods for determining a user specific mission operational performance, using machine-learning processes.

Abstract: Aspects relate to systems and methods for dynamic active noise reduction including at least a sensor configured to sense a physiological characteristic of a user and transmit a physiological signal correlated to the sensed physiological characteristic, at least an environmental microphone configured to transduce an environmental noise to an environmental noise signal, a processor configured to receive the environmental noise signal, generate a noise-reducing sound signal as a function of the environmental noise signal, and, modify the noise-reducing sound signal as a function of the physiological signal, and a speaker configured to transduce a noise-reducing sound from the modified noise-reducing sound signal.

Abstract: A system for detecting unsafe equipment operation conditions using physiological sensors includes a plurality of wearable physiological sensors, each physiological sensor of the plurality of wearable physiological sensors configured to detect at least a physiological parameter of an operator of an item of equipment, and a processor in communication with the at least a physiological sensor and designed and configured to determine an equipment operation parametric model, wherein the equipment operation parametric rule relates physiological parameter sets to equipment operation requirements, detect using the equipment operation parametric model and the plurality of physiological parameters, a violation of an equipment operation requirement, and generate a violation response action in response to detecting the violation.

Abstract: 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.

Abstract: Aspects relate to systems and methods for determining actor status according to behavioral phenomena. An exemplary system includes an eye sensor configured to detect an eye parameter as a function of an eye phenomenon, a speech sensor configured to detect a speech parameter as a function of a speech phenomenon, and a processor in communication with the eye sensor and the speech sensor; the processor is configured to receive the eye parameter and the speech parameter, determine an eye pattern as a function of the eye parameter, determine a speech pattern as a function of the speech parameter, and correlate one or more of the eye pattern and the speech pattern to a cognitive status.

Abstract: Aspects relate to systems and methods for dynamic active noise reduction including at least a sensor configured to sense a physiological characteristic of a user and transmit a physiological signal correlated to the sensed physiological characteristic, at least an environmental microphone configured to transduce an environmental noise to an environmental noise signal, a processor configured to receive the environmental noise signal, generate a noise-reducing sound signal as a function of the environmental noise signal, and, modify the noise-reducing sound signal as a function of the physiological signal, and a speaker configured to transduce a noise-reducing sound from the modified noise-reducing sound signal.

Abstract: 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.

Abstract: 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.

Abstract: Aspects relate to systems and methods for inspirate sensing to determine a probability of an emergent physiological state. An exemplary system an inhalation sensor module configured to sense and transmit a plurality of inhalation parameters as a function of at least an inspirate, an environmental sensor module configured to sense and transmit a plurality of environmental parameters as a function of an environment, and a processor configured to generate a probability of an emergent physiological state by: inputting at least an environmental parameter and at least an inhalation parameter to a probabilistic machine learning model and generating the probability of an emergent physiological state as a function of the machine learning model.