Muscle, Skin or Brain Based Authentication and Identification

Smart overview of the Invention

The patent application introduces an innovative device designed for authentication and identification using unique recognition vectors derived from muscle, skin, or brain activity. This device employs sensors to generate electrical signals responsive to these activities, which are then converted into spectral images. A machine learning mechanism processes these images to create a recognition vector associated with the user. This system offers a novel approach to user authentication, particularly suitable for emerging portable wearable devices with varied form factors.

Traditional biometric authentication methods like fingerprints, facial recognition, and eye scans often require conscious user interaction and are not compatible with new device forms such as AR/VR headsets, smart jewelry, and oral appliances. These conventional methods may also lack continuous security verification, posing risks in scenarios where unauthorized use could occur unnoticed. The proposed device addresses these limitations by providing a seamless and continuous authentication method suitable for diverse applications, including industrial equipment operation and wearable health devices.

In addition to personal use cases, the technology can be applied in commercial farming to accurately identify animals using biometric data rather than easily transferable RF tags. This ensures a more secure and reliable identification process that minimizes errors and fraud. The device's ability to monitor optical variations through infrared light interactions further enhances its versatility across different biological systems and industries requiring precise biometric data.

The device can be integrated into various wearable technologies such as CPAP machines and eyewear, ensuring compliance and accurate user identification. For instance, it can replace traditional temperature sensors in oral appliances for sleep apnea treatment, providing not only usage compliance but also confirming the identity of the user. Similarly, eyewear equipped with this technology can utilize eye biometrics like blinking patterns and pupil dilation for secure authentication.

Overall, the described technology provides a robust solution for modern authentication needs across multiple domains. By leveraging advanced sensor technologies and machine learning algorithms, it facilitates secure and user-friendly authentication processes that align with the evolving landscape of portable and wearable devices. This approach not only enhances security but also broadens the scope of biometric applications beyond current limitations.