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Main Authors: Ajikumar, Akhil, Mayenkar, Sahil, Yoo, Steven, Reza, Sakib, Moghaddam, Mohsen
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2511.05304
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author Ajikumar, Akhil
Mayenkar, Sahil
Yoo, Steven
Reza, Sakib
Moghaddam, Mohsen
author_facet Ajikumar, Akhil
Mayenkar, Sahil
Yoo, Steven
Reza, Sakib
Moghaddam, Mohsen
contents Extended reality (XR) research increasingly relies on the ability to stream and synchronize multimodal data between headsets and immersive applications for data-driven interaction and experimentation. However, developers face a critical gap: the Platform for Situated Intelligence (psi), which excels at deterministic temporal alignment and multimodal data management, has been largely inaccessible to the dominant Unity/MRTK ecosystem used for HoloLens development. We introduce psiUnity, an open-source C# integration that bridges psi's .NET libraries with Unity 2022.3 and MRTK3 for HoloLens 2. psiUnity enables bidirectional, real-time streaming of head pose, hand tracking, gaze, IMU, audio, and depth sensor data (AHAT and long-throw) with microsecond-level temporal precision, allowing Unity applications to both consume and produce synchronized multimodal data streams. By embedding psi's native serialization, logging, and temporal coordination directly within Unity's architecture, psiUnity extends psi beyond its previous StereoKit limitations and empowers the HRI, HCI, and embodied-AI communities to develop reproducible, data-driven XR interactions and experiments within the familiar Unity environment. The integration is available at https://github.com/sailgt/psiUnity.
format Preprint
id arxiv_https___arxiv_org_abs_2511_05304
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle psiUnity: A Platform for Multimodal Data-Driven XR
Ajikumar, Akhil
Mayenkar, Sahil
Yoo, Steven
Reza, Sakib
Moghaddam, Mohsen
Human-Computer Interaction
Extended reality (XR) research increasingly relies on the ability to stream and synchronize multimodal data between headsets and immersive applications for data-driven interaction and experimentation. However, developers face a critical gap: the Platform for Situated Intelligence (psi), which excels at deterministic temporal alignment and multimodal data management, has been largely inaccessible to the dominant Unity/MRTK ecosystem used for HoloLens development. We introduce psiUnity, an open-source C# integration that bridges psi's .NET libraries with Unity 2022.3 and MRTK3 for HoloLens 2. psiUnity enables bidirectional, real-time streaming of head pose, hand tracking, gaze, IMU, audio, and depth sensor data (AHAT and long-throw) with microsecond-level temporal precision, allowing Unity applications to both consume and produce synchronized multimodal data streams. By embedding psi's native serialization, logging, and temporal coordination directly within Unity's architecture, psiUnity extends psi beyond its previous StereoKit limitations and empowers the HRI, HCI, and embodied-AI communities to develop reproducible, data-driven XR interactions and experiments within the familiar Unity environment. The integration is available at https://github.com/sailgt/psiUnity.
title psiUnity: A Platform for Multimodal Data-Driven XR
topic Human-Computer Interaction
url https://arxiv.org/abs/2511.05304