A computer-aided learning method and apparatus for a learning user to learn materials inexpensively. Not only does the apparatus provide the user the freedom as to where and when to learn, and the guidance as to what to learn, the apparatus also reduces a significant hurdle to learning—money. The apparatus retrieves a user identifier entered by the user, and determines whether the user is a learning user or an institute user. If the user is a learning user, the apparatus allows the user to access information regarding learning materials. If the user is an institute user, the apparatus permits the user to access information regarding at least one learning user. The institute user might be interested to use the apparatus to recruit employees to fill job openings. A learning user pays significantly less than an institute user to access information, so as to encourage the learning user to work on learning materials. The apparatus can also track and update information regarding the users.

Apparatuses, systems, methods, and computer program products are disclosed for adaptive machine learning. An apparatus includes a monitoring module that continuously monitors one or more interactions of a user while the user performs one or more simulated tasks digitally presented to the user that are associated with a learning path. The apparatus includes a metadata module that tracks data describing the user's interactions during the user's performance of one or more simulated tasks. The apparatus includes a machine learning module that, dynamically and in real-time, optimizes the user's learning path by simulating multiple different learning paths using one or more machine learning processes and tracked data. The apparatus includes a recommendation module that presents one or more recommendations to the user for optimizing the user's learning path. One or more recommendations may be generated as a function of the optimized learning path.

Apparatuses, systems, methods, and computer program products are disclosed for adaptive machine learning. An apparatus includes a monitoring module that continuously monitors one or more interactions of a user while the user performs one or more simulated tasks digitally presented to the user that are associated with a learning path. The apparatus includes a metadata module that tracks data describing the user's interactions during the user's performance of one or more simulated tasks. The apparatus includes a machine learning module that, dynamically and in real-time, optimizes the user's learning path by simulating multiple different learning paths using one or more machine learning processes and tracked data. The apparatus includes a recommendation module that presents one or more recommendations to the user for optimizing the user's learning path. One or more recommendations may be generated as a function of the optimized learning path.

The schematic flow chart diagrams included herein are generally set forth as logical flow chart diagrams. As such, the depicted order and labeled steps are indicative of one embodiment of the presented method. Other steps and methods may be conceived that are equivalent in function, logic, or effect to one or more steps, or portions thereof, of the illustrated method. Additionally, the format and symbols employed are provided to explain the logical steps of the method and are understood not to limit the scope of the method. Although various arrow types and line types may be employed in the flow chart diagrams, and they are understood not to limit the scope of the corresponding method.

Systems and methods for using multi-view learning to leverage highly informative, high-cost, psychophysiological data collected in a laboratory setting, to improve post-traumatic stress disorder (PTSD) screening in the field, where only less-informative, low-cost, speech data are available. Partial least squares (PLS) methods can be used to learn a bilinear factor model, which projects speech and EEG responses onto latent spaces, where the covariance between the projections is maximized. The systems and methods use a speech representation based on a combination of audio and language descriptors extracted from spoken responses to open-ended questions.

Systems and methods for using multi-view learning to leverage highly informative, high-cost, psychophysiological data collected in a laboratory setting, to improve post-traumatic stress disorder (PTSD) screening in the field, where only less-informative, low-cost, speech data are available. Partial least squares (PLS) methods can be used to learn a bilinear factor model, which projects speech and EEG responses onto latent spaces, where the covariance between the projections is maximized. The systems and methods use a speech representation based on a combination of audio and language descriptors extracted from spoken responses to open-ended questions.

A device (100) for the treatment of depression, anxiety and pain, the device comprising: a plurality of adjacent dots (11) or other shapes, each comprising means for providing a signal being sensible by a touch sense, the signal comprising mechanical signal and/or electrical signal and/or temperature signal and/or magnetic signal; and a controller (32) for executing each of the means independently, for providing pre-programmed shapes (30, 40, 40A, 40B, 42, 46, 48, 50, 52, 54) being sensible by the touch sense, thereby allowing treating the depression, anxiety and pain by generating to the brain, signals resembling the pre-programmed shapes (30, 40, 40A, 40B, 42, 46, 48, 50, 52, 54) through the signals being sensible by the touch sense.

A system for monitoring behaviour comprising a portable display device (12) provided for an individual whose behaviour is to be monitored and a portable communication device (14) provided to a supervising adult. The portable display device (12) displays a value being an indication of a number of good behaviour events and a value modifier on the portable communication device (14) is operated to increase the value displayed on the portable display device (12) of the individual.

A system for monitoring behaviour comprising a portable display device (12) provided for an individual whose behaviour is to be monitored and a portable communication device (14) provided to a supervising adult. The portable display device (12) displays a value being an indication of a number of good behaviour events and a value modifier on the portable communication device (14) is operated to increase the value displayed on the portable display device (12) of the individual.

A speech improvement system includes a memory, an audio input device, and a signal processing device. A baseline spoken audio signal is pre-recorded and stored in the memory. A real-time spoken audio signal is captured using the audio input device. The signal processing device is configured to compare the real-time spoken audio signal to the baseline spoken audio signal and generate a user alert, such as a haptic alert, an audible alert, and/or a visual alert, if the real-time spoken audio signal deviates from the baseline spoken audio signal by a preset threshold amount.