Vital Sign Harmonic Authentication for Extended Reality (XR)

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Technology harnesses harmonics of vital sign vibrations to realize effortless (does not require any explicit user actions) and inbuilt (uses motion sensors available on all XR headsets) XR user authentication

Invention Summary:

As extended reality (XR) experiences become more immersive, traditional authentication methods like passwords, PINs, and gaze-based verification are no longer sufficient. They interrupt the user journey and fail to protect against mid-session impersonation once access is granted. Our solution delivers seamless, continuous authentication that works entirely in the background eliminating friction while ensuring users remain securely verified at all times. The result is a smoother, safer XR experience with zero disruption.

Rutgers researchers developed this technology which enables continuous and robust user authentication in extended reality environments by capturing and analyzing low-frequency mechanical vibrations generated by users' vital signs such as breathing and heartbeat. These vibrations cause the skull to produce harmonic signals that carry unique biometric information, which is captured through built-in motion sensors in XR headsets. Using adaptive filters and attention-based deep learning models, the system processes these signals to reliably authenticate users without requiring any additional hardware. The work was presented in November in Taipei, Taiwan, at the ACM Conference on Computer and Communications Security, a major annual meeting of the Association for Computing Machinery’s Special Interest Group on Security, Audit and Control, and was recognized with a Distinguished Paper Award. Read more here!  

Market Applications:

• User authentication for virtual and augmented reality headsets.
• Access control and personalized experiences in gaming and entertainment XR platforms.
• Secure authentication for remote work and virtual collaboration environments.
• Healthcare and fitness XR applications requiring identity verification.
• Enhanced security in XR training and simulation systems.

Advantages:

• No need for additional hardware; utilizes existing XR headset motion sensors.
• Non-volatile biometric features extracted from harmonic frequency ratios, ensuring stable authentication despite fluctuations in vital signs.
• Adaptive filtering mitigates distortion from body motion during XR interactions.
• Attention-based deep learning ensures continuous and robust authentication over long periods.
• High accuracy with a true positive rate over 95% and unauthorized user rejection over 98%.

Publication:

• Tianfang Zhang, Qiufan Ji, Md Mojibur Rahman Redoy Akanda, Zhengkun Ye, Ahmed Tanvir Mahdad, Cong Shi, Yan Wang, Nitesh Saxena, and Yingying Chen. 2025. Harnessing Vital Sign Vibration Harmonics for Effortless and Inbuilt XR User Authentication. In Proceedings of the 2025 ACM SIGSAC Conference on Computer and Communications Security (CCS '25). Association for Computing Machinery, New York, NY, USA, 3520–3534. https://doi.org/10.1145/3719027.3765060  

Intellectual Property & Development Status: Provisional patent application filed. Patent pending. Available for licensing and/or research collaboration. For any business development and other collaborative partnerships, contact:  marketingbd@research.rutgers.edu