An investigative interview management system and in particular a processing system, computerised system, method and computer readable medium for implementing the same are disclosed. In one aspect, the processing system is configured to receive, from an interviewer, a request to generate an interview plan; generate, based on the request, an interview plan including a plurality of topics; receive, from one or more input devices during an interview between the interviewer and interviewee, input data; associate at least some of the input data with one or more of the topics of the interview plan; analyse at least some of the input data; and output, during the interview via one or more output devices, one or more notifications based on results of the analysis.

Embodiments of the present systems and methods may provide a non-invasive system to measure and integrate behavioral and cognitive features enabling early detection and progression tracking of degenerative disease. For example, a method of detecting neurodegenerative disease may comprise measuring functioning of at least one of the motor system, cognitive function, and brain activity of a subject during everyday life and analyzing the gathered at least one motor system data, cognitive function data, and brain activity data of the subject.

The invention is a method for automatic detection of neurocognitive impairment, comprising, generating, in a segmentation and labelling step (11), a labelled segment series (26) from a speech sample (22) using a speech recognition unit (24); and generating from the labelled segment series (26), in an acoustic parameter calculation step (12), acoustic parameters (30) characterizing the speech sample (22).

The method is characterised by determining, in a probability analysis step (14), in a particular temporal division of the speech sample (22), respective probability values (38) corresponding to silent pauses, filled pauses and any types of pauses for respective temporal intervals thereof; calculating, in an additional parameter calculating step (15), a histogram by generating an additional histogram data set (42) from the determined probability values (38) by dividing a probability domain into subdomains and aggregating durations of the temporal intervals corresponding to the probability values falling into the respective subdomains; and generating, in an evaluation step (13), decision information (34) by feeding the acoustic parameters (30) and the additional histogram data set (42) into an evaluation unit (32), the evaluation unit (32) using a machine learning algorithm.

The invention is furthermore data processing system, a computer program product and a computer-readable storage medium for carrying out the method.

A method for estimating a likelihood of a stroke condition of a subject, the method comprising: acquiring clinical measurement data pertaining to said subject, said clinical measurement data including at least one of image data, sound data, movement data, and tactile data; extracting from said clinical measurement data, potential stroke features according to at least one predetermined stroke assessment criterion; comparing said potential stroke features with classified sampled data acquired from a plurality of subjects, each positively diagnosed with at least one stroke condition, defining a positive stroke dataset; and determining, according to said comparing, a probability of a type of said stroke condition, and a probability of a corresponding stroke location of said stroke condition with respect to a brain location of said subject.

Embodiments are related to a headset integrated into a healthcare platform. The headset comprises one or more sensors embedded into a frame of the headset, a controller coupled to the one or more sensors, and a transceiver coupled to the controller. The one or more sensors capture health information data for a user wearing the headset. The controller pre-processes at least a portion of the captured health information data to generate a pre-processed portion of the health information data. The transceiver communicates the health information data and the pre-processed portion of health information data to an intermediate device communicatively coupled to the headset. The intermediate device processes at least one of the health information data and the pre-processed portion of health information data to generate processed health information data for a health-related diagnostic of the user.

A method for analyzing a voice sample of a subject to determine a cardiac condition, for example, an arrhythmic condition, comprising extracting at least one voice feature from the voice sample, detecting an effect of the cardiac condition on the at least one voice feature and determining the cardiac condition based on the effect. Disclosed is also a system for determining the cardiac condition in the voice sample provided by the subject. Related apparatus and methods are also described.

A computer-implemented method for measuring cognitive load of a user creating a creative work in a creative work system, may include generating at least one verbal statement capable of provoking at least one verbal response from the user, prompting the user to vocally interact with the creative work system by vocalizing the at least one generated verbal statement to the user via an audio interface of the creative work system, and obtaining the at least one verbal response from the user via the audio interface, and determining the cognitive load of the user based on the at least one verbal response obtained from the user, wherein generating the at least one verbal statement is based on at least one predicted verbal response suitable for determining the cognitive load of the user.

A device may receive text data, audio data, and video data associated with a user, and may process the received data, with a first model, to determine a stress level of the user. The device may process the received data, with second models, to determine depression levels of the user, and may combine the depression levels to identify an overall depression level. The device may process the received data, with a third model, to determine a continuous affect prediction, and may process the received data, with a fourth model, to determine an emotion of the user. The device may process the received data, with a fifth model, to determine a response to the user, and may utilize a sixth model to determine a context for the response. The device may utilize seventh models to generate contextual conversation data, and may perform actions based on the contextual conversational data.

An apparatus includes a communication interface and a processor. The processor is configured to receive, via the communication interface, a plurality of speech samples {u.sub.m.sup.0}, m=1 . . . M, which were uttered by a subject while in a first state with respect to a disease, and using {u.sub.m.sup.0} and at least one reference discriminator, which is not specific to the subject, synthesize a subject-specific discriminator, which is specific to the subject and is configured to generate, in response to one or more test utterances uttered by the subject, an output indicating a likelihood that the subject is in a second state with respect to the disease. Other embodiments are also described.

The present invention relates to systems and methods for characterizing at least one anatomical parameter of an upper airway of a patient by analysing spectral properties of an utterance, comprising: a mechanical coupler comprising means for restricting the jaw position of the patient; means for recording an utterance; and processing means for determining at least one anatomical parameter of the upper airway from the recorded utterance and comparing the recorded utterance to a threshold value. In addition the present invention relates to the use of the above mentioned systems as a diagnostics tool for assessing obstructive sleep apnea.