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SYSTEMS AND TECHNIQUES FOR IDENTIFYING AND EXPLOITING RELATIONSHIPS BETWEEN MEDIA CONSUMPTION AND HEALTH

Номер патента: US20200012959A1. Автор: Karanam Ketki, KOPIKIS Alexis, Krishnan Vikram, Kuchekar Nilesh N., Marsh Abby B., Martucci W. Edward, Sian Steven A.. Владелец: Bose Corporation. Дата публикации: 09-01-2020.
A system for inducing a physical state in a user. The system includes a sensor associated with the user, an audio output device, and a computer. The computer obtains, from a database, an identification of a type of music associated with a first phase of sleep, and determines, based on data from the sensor, that a user is in a second phase of sleep. Music of the type associated with the first phase of sleep is selected, and the selected music is output to the user through the audio output device. 1. A system for inducing a physical state in a user , comprising:a sensor associated with the user;an audio output device; anda computer configured to:obtain, from a database, an identification of a type of music associated with a first phase of sleep;determine, based on data from the sensor, that a user is in a second phase of sleep;select music of the type associated with the first phase of sleep; andoutput the selected music to the user through the audio output device.2. The method of claim 1 , further comprising:obtaining, from a sensor associated with the user, updated health condition data, the health condition data indicating the user's progress towards the first phase of sleep;based on the updated health condition data, modifying the selected music; andoutputting the modified music to the user.3. The method of claim 2 , wherein obtaining the updated health condition data comprises monitoring the user's respiration rate.4. The method of wherein the identification of a type of music associated with a first phase of sleep comprises a genre of music.5. The method of wherein the identification of a type of music associated with the first phase of sleep comprises data describing acoustic attributes of music.6. The method of wherein the acoustic attributes of music comprise one or more of beat claim 5 , tempo claim 5 , and pitch.7. The method of wherein modifying the selected music comprises reducing the tempo of the music.8. The method of wherein determining that the user ...

SYSTEMS AND TECHNIQUES FOR IDENTIFYING AND EXPLOITING RELATIONSHIPS BETWEEN MEDIA CONSUMPTION AND HEALTH

Номер патента: US20160055420A1. Автор: Karanam Ketki, KOPIKIS Alexis, Krishnan Vikram, Kuchekar Nilesh N., Marsh Abby B., Martucci W. Edward, Sian Steven A., Zohar Daphne. Владелец: . Дата публикации: 25-02-2016.
A predictive method may include determining the strength of a relationship between a user's health state and the user's consumption of media content having one or more features, based on health data and media consumption data corresponding to user consumption of media content items having the feature(s), and predicting an effect of consuming a media content item on the user's health. The prediction may be based on a determination that the strength of the relationship between the health state and the consumption of media content having the one or more features exceeds a threshold strength. A diagnostic method may include determining whether a media consumption signature associated with a health condition matches media consumption data for a population, and diagnosing the population with the health condition based on a determination that the media consumption signature associated with the health condition matches the media consumption data for the population. 1. A predictive method comprising: obtaining media consumption data regarding media content consumed by a user during one or more time periods, wherein the media content includes a plurality of media content items having one or more same features;', 'obtaining health data, wherein at least a portion of the health data relates to health states of the user during the one or more time periods;', 'synchronizing the media consumption data and the health data;', 'determining a strength of a relationship between a health state of the user and consumption by the user of media content having the one or more features, based at least in part on portions of the media consumption data corresponding to user consumption of the plurality of media content items having the one or more features and on the synchronized health data; and', "predicting an effect of consuming a media content item on the user's health, wherein the prediction is based at least in part on a determination that the strength of the relationship between the ...

USER INTERFACE AND METHOD BASED ON SLIDING-SCALE CLUSTER GROUPS FOR PRECISE LOOK-ALIKE MODELING

Номер патента: US20190156529A1. Автор: Kuchekar Nilesh, PATEL Bhupendra Mohanlal, Patel Tushar. Владелец: Cadreon LLC. Дата публикации: 23-05-2019.
A graphical user interface showing relevant sliding scale cluster groups having a processor generating a ranking of Top N1 features of the seed dataset in order of frequency of their occurrence. The processor generates another ranking of Top N2 features of the seed dataset in order of frequency of their occurrence in correlation with their equivalent percentage in total dataset. The Top M co-related features is identified for each of the Top N (N1+N2) features that are present for the seed dataset. The processor, for each one in M×N set, generates a sliding scale cluster via permutation of Top M features. The processor sorts each permutation based on closest occurrence match. The Seed Group Meta Bitmap Index is generated for the seed audience segment. For each cluster, the processor calculates the available amplification count from the Total Audience Bitmap Index, until the desired amplification is achieved. 1: A computerized method for generating dynamic look-alike data points of seed dataset on a graphical user interface (GUI) comprising:defining a seed dataset from a collection of data, said collection of data comprising features associated with data;generating a first ranking of a first set of top features of the seed dataset;generating a second ranking of a second set of top features of the seed dataset;identifying a M set of co-related features for each of a combined set N from the first set and the second set that are present for the seed dataset;for each one in M×N set, generating a sliding scale cluster via permutation of the M set of co-related features to be displayed on the GUI;generating a seed group meta bitmap index for the seed audience segment;generating a total audience bitmap index based on the generated seed group meta index; andfor each cluster, generating an available amplification count from the total audience bitmap index for display on the GUI in response to a user instructions received from the GUI until a desired amplification in the ...

Systems and techniques for identifying and exploiting relationships between media consumption and health

Номер патента: US20180240027A1. Автор: Abby B. Marsh, Alexis Kopikis, Daphne Zohar, Ketki Karanam, Nilesh N. Kuchekar, Steven A. Sian, Vikram Krishnan, W. Edward Martucci. Владелец: Bose Corp. Дата публикации: 23-08-2018.
A predictive method may include determining the strength of a relationship between a user's health state and the user's consumption of media content having one or more features, based on health data and media consumption data corresponding to user consumption of media content items having the feature(s), and predicting an effect of consuming a media content item on the user's health. The prediction may be based on a determination that the strength of the relationship between the health state and the consumption of media content having the one or more features exceeds a threshold strength. A diagnostic method may include determining whether a media consumption signature associated with a health condition matches media consumption data for a population, and diagnosing the population with the health condition based on a determination that the media consumption signature associated with the health condition matches the media consumption data for the population.

System and method based on sliding-scale cluster groups for precise look-alike modeling

Номер патента: US10417798B2. Автор: Bhupendra Mohanlal PATEL, Nilesh Kuchekar, Tushar Patel. Владелец: Cadreon LLC. Дата публикации: 17-09-2019.
A graphical user interface showing relevant sliding scale cluster groups having a processor generating a ranking of Top N1 features of the seed dataset in order of frequency of their occurrence. The processor generates another ranking of Top N2 features of the seed dataset in order of frequency of their occurrence in correlation with their equivalent percentage in total dataset. The Top M co-related features is identified for each of the Top N (N1+N2) features that are present for the seed dataset. The processor, for each one in M×N set, generates a sliding scale cluster via permutation of Top M features. The processor sorts each permutation based on closest occurrence match. The Seed Group Meta Bitmap Index is generated for the seed audience segment. For each cluster, the processor calculates the available amplification count from the Total Audience Bitmap Index, until the desired amplification is achieved.
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