The Nielsen Comapny (us), LLC

Brainguard Technologies, Inc.

Nielsen Consumer LLC

University of California

The Nielson Company (us), LLC

The Neilsen Company (us), LLC

Braingaurd Technologies, Inc.

Robert T Knight

Ramachandran Gurumoorthy

Anantha K Pradeep

A K Pradeep

Yakob Badower

Alexander Pavlovich Topchy

Padmanabhan Soundararajan

Ratnakar Dev

Avery Audrey Kwan

Dev Ratnakar

Brian Pasley

Ramchandran Gurumoorthy

Ak Pradeep

Ram Gurumoorthy

Example devices are disclosed herein that include a first elongated band coupled to a first housing to be located on a first side of a head of a subject and a second housing to be located near a second side of the head of the subject, the first elongated band comprising a first set of electrodes. The example device also includes a second elongated band coupled to the first housing and to the second housing, the second elongated band comprising a second set of electrodes. In addition, the device includes a third elongated band coupled to the first housing and to the second housing, the third elongated band comprising a third set of electrodes.

Systems and methods to gather and analyze electroencephalographic data

An example system includes an analyzer to identify a degree of amplitude synchrony between a first pattern in a first frequency band in first neuro-response data and a second pattern in a second frequency band in the first neuro-response data, the first neuro-response data gathered via a first modality of collection from a subject while the subject is exposed to media, and modify the degree of amplitude synchrony in response to activity in second neuro-response data, the second neuro-response data gathered via a second modality of collection from the subject while the subject is exposed to the media, the activity corresponding in time to at least a portion of the first pattern or the second pattern. The example system includes an estimator to determine an effectiveness of the media based on the modified degree of amplitude synchrony.

Analysis of marketing and entertainment effectiveness using central nervous system, autonomic nervous system, and effector data

An example system includes an analyzer to identify first activity in first neuro-response data, the first activity generated in response to exposure of a subject to a first stimulus prior to exposure to an advertisement or entertainment; identify second activity in second neuro-response data, the second activity generated in response to re-exposure of the subject to the first stimulus after to exposure to the advertisement or entertainment; calculate a differential event related potential measurement; and calculate a differential event related power spectral perturbation. The example system includes a resonance estimator to determine a subject resonance measurement to the advertisement or the entertainment based on the differential event related potential measurement and adjust at least one of the subject resonance measurement or the differential event related potential measurement based on the differential event related power spectral perturbation to generate an adjusted subject resonance measurement.

Neuro-response stimulus and stimulus attribute resonance estimator

A neurological profile associated with introversion/extroversion levels, simultaneous visual element processing capability, and/or dynamism processing capability, etc., is determined to select market categories and stimulus material targeted to the particular neurological profile. The neurological profile is determined using information such as user input, user activity, social and environmental factors, genetic and developmental factors, and/or neuro-response data. The neurological profile can be matched with corresponding neurological profile templates to select market categories and stimulus material.

Neurological profiles for market matching and stimulus presentation

An example system disclosed herein includes an analyzer to determine a first priming characteristic of media at a first location based on first neuro-response data and determine a second priming characteristic of the media at the second location based on second neuro-response data. The example system includes a selector to select a third location in the media after the first location or a fourth location in the media after the second location as a candidate location for introduction of advertising material based on the first priming characteristic and the second priming characteristic. The selector is to select the third location when the first priming characteristic indicates increased receptivity to the advertising material at the first location relative to the second priming characteristic and select the fourth location when the second priming characteristic indicates increased receptivity to the advertising material at the second location relative to the first priming characteristic.

Analysis of controlled and automatic attention for introduction of stimulus material

An example system to identify an advertisement to include in source material to increase an effectiveness of the advertisement includes an analyzer to determine one or more priming characteristics for a plurality of locations of a source material based on neuro-response data collected from a first subject exposed to the source material and a selector to identify an attribute of the advertisement, identify at least one of a temporal attribute or a spatial attribute for the plurality of locations, perform a comparison of the attribute of the advertisement to the at least one of the temporal attribute or the spatial attribute for the plurality of locations, select a first location of the plurality of locations for insertion of the advertisement based on the comparison and the priming characteristics, and transform the source material to include the advertisement at the first location.

Content based selection and meta tagging of advertisement breaks

An example system disclosed herein includes an analyzer to analyze first neuro-response data and second neuro-response data and a selector to identify a candidate location in source material for introduction of an advertisement or entertainment based on first neuro-response data and second neuro-response data. The analyzer is to detect a first pattern of oscillation in a first frequency band of third neuro-response data; detect a second pattern of oscillation in a second frequency band of the third neuro-response data; determine a degree of phase synchrony or amplitude synchrony based on the first pattern of oscillation and the second pattern of oscillation; and determine an effectiveness of the advertisement or entertainment based on the degree of phase synchrony or amplitude synchrony.

Stimulus placement system using subject neuro-response measurements

An example system disclosed herein for transforming neuro-response data into media ratings includes a data collector to obtain first neuro-response from a first subject exposed to a first media and second neuro-response data from a second subject exposed to a second media. The first media broadcast is before a time of the second media. The example system includes an analyzer to integrate the first neuro-response data with ratings data for the first media to generate a first rating for the first media. The ratings data is based on set-top box data associated with a media presentation device presenting the first media. The analyzer is to transform the second neuro-response data into a second rating for the second media based on the first rating.

Generating ratings predictions using neuro-response data

Methods and apparatus to identify an emotion evoked by media are disclosed. An example apparatus includes a synthesizer to generate a first synthesized sample based on a pre-verbal utterance associated with a first emotion. A feature extractor is to identify a first value of a first feature of the first synthesized sample. The feature extractor to identify a second value of the first feature of first media evoking an unknown emotion. A classification engine is to create a model based on the first feature. The model is to establish a relationship between the first value of the first feature and the first emotion. The classification engine is to identify the first media as evoking the first emotion when the model indicates that the second value corresponds to the first value.

Methods and apparatus to identify a mood of media

Analysis of marketing and entertainment effectiveness using central nervous system, autonomic nervous sytem, and effector data

An example system includes an analyzer to determine a first distance between (1) a first peak in a first frequency band of first neuro-response data gathered from a subject while exposed to media and (2) a second peak in the first frequency band; determine a second distance between (1) a third peak in the first frequency band and either (2) the second peak in the first frequency band or (3) a fourth peak in the first frequency band and determine a first difference between the first distance and the second distance. The example system includes a selector to determine a modification for the media based on the first difference and a modifier to implement the modification for presentation of the media.

Neuro-physiology and neuro-behavioral based stimulus targeting system

An electroencephalography (EEG) system includes a dry electrode design having a jagged, angular, comb, etc. shaped support housing. Each dry electrode housing includes multiple electrodes where each electrode has multiple contacts for scalp placement with minimal interference from hair. Signals from individual contacts may be disregarded and each housing may provide one or more aggregated signals for data analysis. Each electrode may be placed in close proximity with neighboring electrodes as no conductive gel is required and may be attached to the scalp using straps, elastic cap, spring-type materials, tape, etc. The dry electrode design effectively measures bio-signals including neurological activity.

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Berkeley, CA, United States of America

Robert T Knight