An apparatus includes a memory and a processor. The processor is configured to execute instructions stored in the memory to determine interrupt events from a plurality of notification events generated by one or more of a plurality of computer systems; receive alert data indicating occurrence of monitored conditions in a managed information technology environment; assign, based on the alert data, incidents to the responder; modify, with respect to the responder, a notification configuration based on resolution data associated with the incidents and the interrupt events; and transmit a notification to the responder according to the modified notification configuration in response to assigning a new incident to the responder. The interrupt events are determined based on respective corresponding notification events being sent in respective manners designed to immediately alert a responder.

A system predicts the mental state of a user using a variety of contact or contactless sensors that measure heart rate, breathing or other data of the user. The mental state may be flow, overload, underload, stress, attention, motivation, valence, arousal, etc. While performing a game-playing task the difficulty of the task is adjusted based upon the predicted mental state of the user. A classifier for classifying a mental state is trained using event marking and ground truth data. Computer usage generates event markers. Game playing is used to simulate a mental state. Interruptions of a user are prevented when the user enters a flow, focused, or effortful attention state by classifying that state and indicating physically or electronically that the user should not be interrupted. Interruptions of a user are also prevented when the user enters a mind wandering state by classifying or predicting that state and indicating physically or electronically that the user should not be interrupted. A cost of interrupting is calculated and displayed. Users may also be coached regarding mental state. Advertisements to the user may vary based upon a classified mental state of the user.

In an aspect of the invention, a method of identifying sensory inputs affecting working memory load of an individual is provided. The method comprises monitoring (S101) working memory load of the individual using a sensor device, detecting (S102) an increase in the working memory load of the individual, and identifying (S103), in response to the detected increase, at least one sensory input affecting the working memory load of the individual.

A portable work capacities testing apparatus comprising a portable computer, a hub releaseably interconnected with the portable computer, a dynamic strength and lifting device releaseably interconnected with the hub, a hand grip strength device releaseably interconnected with the hub, a finger pinch strength device releaseably interconnected with the hub, a forearm/wrist strength device releaseably interconnected with the hub, a handling/proprioception device releaseably interconnected with the hub, a finger flexion device releaseably interconnected with the hub, a whole body coordination device releaseably interconnected with the hub, and a strength push/pull/lift device releaseably interconnected with the hub.

Apparatus having corresponding methods and computer-readable media comprise a controller configured to i) determine a desired respiratory rate of a person, and ii) generate an audio signal having a periodic component, wherein a rate of the periodic component is based on the desired respiratory rate; and a speaker configured to produce sound based on the audio signal.

A method for using an Internet of Workplace Things (IoWT) to enhance productivity in a workplace includes obtaining real-time data for a plurality of core modules via an environmental sensory system which is operatively connected to one or more core computational linguistics technologies of a workplace interface in the workplace. The method further includes analyzing the real-time data and monitoring trends by comparing the real-time data with predetermined baselines for each of the plurality of core modules. The method further includes generating a corrective real-time bio-feedback loop by providing backend solutions and commands for each core module with alerts and flags. The method further includes reporting a decision-making matrix for the backend solutions and commands. The decision-making matrix is based on the plurality of core modules as aligned with a plurality of human-machine interfaces.

A computer-implemented method includes: receiving, by a computing device, information identifying a user's activity; determining, by the computing device, the user's tasks based on the information identifying the user's activity; determining, by the computing device, the user's context switches based on the user's tasks; receiving, by the computing device, biometrics data associated with the user via an application programming interface (API); determining, by the computing device, the user's stress levels at various times based on the biometrics data; storing, by the computing device, information linking the user's stress level with the user's context switches; and outputting, by the computing device, the information linking the user's stress level with the user's context switches.

A method for predicting an arousal level used by a computer of an arousal level prediction apparatus that predicts an arousal level of a user includes obtaining current biological information regarding the user detected by a first sensor, calculating a current arousal level of the user on the basis of the current biological information, obtaining current environment information indicating a current environment around the user detected by a second sensor, predicting a future arousal level, which is an arousal level a certain period of time later, on the basis of the current arousal level and the current environment information, and (i) issuing a notification to the user or (ii) controlling another device, on the basis of the future arousal level.

Systems and methods are provided for detecting mental fatigue by a user of an Information Handling System (IHS). Upon the user initiating operation of the IHS, activity by the user and physiological parameters of the user are monitored using capabilities of the IHS and, in some cases by wearable devices. Estimates of the user's mental fatigue during the session are generated based on the monitoring. Embodiments identify when the user takes a break from operating the IHS and also identify when the user resumes use of the IHS. Upon the user resuming the session, the user is prompted for their level of mental fatigue prior to taking the break, thus providing a reliable source of feedback data that is utilized in updating and improving machine learning models that are used to generate the estimates of the user's mental fatigue based on observed physiological parameters and activity by the user.

The present invention relates to a medical image acquisition unit assistance apparatus (10), the apparatus comprising:at least one sensor (20); anda processing unit (30); wherein one or more sensors of the at least one sensor is configured to acquire sensor data of a person observing a patient undergoing a medical scan by a medical image acquisition unit; wherein the one or more sensors is configured to provide the acquired sensor data of the person observing the patient undergoing the medical scan to the processing unit; wherein the processing unit is configured to determine a state of the person observing the patient undergoing the medical scan comprising utilization of the acquired sensor data of the person observing the patient undergoing the medical scan; wherein the processing unit is configured to determine an overall state of the patient comprising utilization of the determined state of the person.