View source for 18294420. ADAPTATION OF SENSES DATASTREAMS IN VIRTUAL REALITY AND AUGMENTED REALITY ENVIRONMENTS simplified abstract (Telefonaktiebolaget LM Ericsson (publ))

=ADAPTATION OF SENSES DATASTREAMS IN VIRTUAL REALITY AND AUGMENTED REALITY ENVIRONMENTS=


==Organization Name==

[[:Category:Telefonaktiebolaget LM Ericsson (publ)|Telefonaktiebolaget LM Ericsson (publ)]]


[[Category:Telefonaktiebolaget LM Ericsson (publ)]]

==Inventor(s)==

[[:Category:Athanasios Karapantelakis of SOLNA (SE)|Athanasios Karapantelakis of SOLNA (SE)]][[Category:Athanasios Karapantelakis of SOLNA (SE)]]

[[:Category:Divya Sachdeva of NEW DELHI (IN)|Divya Sachdeva of NEW DELHI (IN)]][[Category:Divya Sachdeva of NEW DELHI (IN)]]

[[:Category:Lackis Eleftheriadis of Valbo (SE)|Lackis Eleftheriadis of Valbo (SE)]][[Category:Lackis Eleftheriadis of Valbo (SE)]]

[[:Category:Maxim Teslenko of SOLLENTUNA (SE)|Maxim Teslenko of SOLLENTUNA (SE)]][[Category:Maxim Teslenko of SOLLENTUNA (SE)]]

[[:Category:Konstantinos Vandikas of Solna (SE)|Konstantinos Vandikas of Solna (SE)]][[Category:Konstantinos Vandikas of Solna (SE)]]

[[:Category:Alexandros Nikou of Danderyd (SE)|Alexandros Nikou of Danderyd (SE)]][[Category:Alexandros Nikou of Danderyd (SE)]]

[[:Category:Alessandro Previti of STOCKHOLM (SE)|Alessandro Previti of STOCKHOLM (SE)]][[Category:Alessandro Previti of STOCKHOLM (SE)]]

[[:Category:Kristijonas Cyras of San Jose CA (US)|Kristijonas Cyras of San Jose CA (US)]][[Category:Kristijonas Cyras of San Jose CA (US)]]

==ADAPTATION OF SENSES DATASTREAMS IN VIRTUAL REALITY AND AUGMENTED REALITY ENVIRONMENTS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18294420 titled 'ADAPTATION OF SENSES DATASTREAMS IN VIRTUAL REALITY AND AUGMENTED REALITY ENVIRONMENTS

The abstract describes a computer-implemented method for adapting a sensory datastream, involving obtaining raw sensory data from a source, state information about the user, predicting the user's desired state using a machine learning model, determining an action to adapt the datastream, and providing the processed datastream to the user's device.

* Obtaining raw sensory datastream from a source
* Obtaining state information about the user
* Predicting the user's desired state using a machine learning model
* Determining an action to adapt the raw sensory datastream
* Providing the processed sensory datastream to the user's device

Potential Applications:
- Personalized user experiences in wearable technology
- Adaptive assistive devices for individuals with disabilities
- Enhanced virtual reality and augmented reality applications

Problems Solved:
- Lack of personalized user experiences in sensory devices
- Inefficient adaptation of sensory data based on user state
- Limited user control over sensory input in devices

Benefits:
- Improved user comfort and satisfaction
- Enhanced user-device interaction
- Increased efficiency in adapting sensory datastreams

Commercial Applications:
Title: Personalized Sensory Adaptation Technology for Wearable Devices
This technology can be utilized in the development of personalized wearable devices for various industries such as healthcare, entertainment, and gaming. The market implications include increased demand for customized sensory experiences in consumer electronics.

Questions about Personalized Sensory Adaptation Technology:
1. How does this technology improve user-device interaction?
- This technology enhances user-device interaction by adapting sensory datastreams based on the user's desired state, providing a more personalized and comfortable experience.
2. What are the potential applications of this technology beyond wearable devices?
- This technology can also be applied in virtual reality systems, smart home devices, and assistive technologies for individuals with disabilities.


==Original Abstract Submitted==

In one aspect, a computer-implemented method of adapting a sensory datastream is provided. The method includes obtaining a raw sensory datastream from a source, wherein the raw sensory datastream comprises input for a sensory actuator of a user device. The method includes obtaining state information, wherein the state information comprises information indicating a first state of a user. The method includes predicting, using a machine learning model, a desired second state of the user based on the obtained state information. The method includes determining an action to adapt the raw sensory datastream based on the desired second state of the user. The method includes adapting the raw sensory datastream in accordance with the determined action and the first state of the user to create a processed sensory datastream. The method includes providing the processed sensory datastream to the sensory actuator of the user device.



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