Head-Based Wearable Sight-Vector Control for Specific AR Objects
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Solution Overview
Problem
Existing brain-computer interface (BCI) systems face challenges in accurately identifying user intent to interact with specific objects in augmented reality environments, particularly due to dynamic brain wave patterns and external electrical interference, limiting their ability to control devices beyond directional movements and leading to unreliable thought-to-speech or thought-to-command modalities.
Innovation Solution
A head-based wearable device collects bio-signals and spatial data to determine user engagement with physical objects using a sight-vector object matrix, enabling non-tactile interaction through a processing unit that identifies and executes commands based on user engagement states with objects in the vicinity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional EEG-based BCI systems are used to read brain waves for command recognition, then directional movement control is achieved, but accurate identification of user intent for specific object interaction is not possible
Solution Approach 1:
The patent combines multiple data sources (brain wave patterns, gaze direction, head orientation, and spatial object data) into a unified engagement assessment. The processing unit integrates these diverse data types to determine user engagement with specific objects, enabling accurate intent identification while maintaining ease of operation through automatic multi-parameter analysis.
Solution Approach 2:
The head-based wearable device performs multiple functions: collecting bio-signals, determining head orientation, identifying objects in the field of view, and assessing user engagement. This multi-functional approach allows the system to accurately identify user intent for various object interactions without requiring separate specialized systems for each function.
2Productivity
If brain wave patterns are read in real-time for thought-to-speech conversion, then communication capability is achieved, but accuracy is reduced due to dynamic brain wave nature and external electrical interference
Solution Approach 1:
The system merges brain wave data with complementary data from gaze tracking, head orientation sensors, and spatial object databases. By combining these data streams, the system compensates for the dynamic and interference-prone nature of brain waves alone, maintaining real-time operation while improving reliability through cross-validation of multiple data sources.
Solution Approach 2:
The patent introduces intermediary data layers (gaze direction, head orientation, spatial object information) that mediate between raw brain wave signals and final command interpretation. These intermediary parameters help filter out noise and external electrical interference from the brain wave readings, improving accuracy without sacrificing real-time processing.
3Ease of operation
If existing thought-to-command modalities are used, then device control is achieved, but the system cannot reliably identify which specific object the user intends to interact with among multiple objects
Solution Approach 1:
The patent adds spatial and contextual dimensions to the control system by incorporating gaze direction, head orientation, and object location data. This dimensional expansion allows the system to distinguish between multiple objects in the environment based on where the user is looking and oriented, enabling specific object identification while preserving ease of operation through automatic spatial awareness.
Solution Approach 2:
The system creates a virtual representation of the physical environment with objects and their spatial relationships. By copying the real-world scene into a digital model that can be processed along with bio-signal data, the system accurately determines which object the user intends to interact with without requiring direct touch or speech, maintaining ease of operation while eliminating object identification ambiguity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances user interaction with real-world objects by accurately determining engagement and executing commands or providing audio feedback, allowing reliable control of devices and access to informational content without requiring touch or speech input.
Implementation Method 1
In an electroencephalography (EEG)-based BCI, the messages are encoded in EEG activity. A BCI measures electrophysiological signals from a user's brain
Data Source
AI summary
Systems and methods are provided for interacting with a physical object. Techniques include receiving data parameters associated with a user via a head-based wearable device; receiving data parameters associated with the object via the head-based wearable device; determining that the user is in vicinity of the object; transmitting the user data parameters and object data parameters to a processor, wherein the processor is configured to: identify at least one sight-vector object definition with the object based on the object data parameters; identify at least one sight-vector object matrix with the user; determine a user-engagement state with the object; set an execution value based on the user-engagement state; and transmit the execution value to an output server.