# Human I/O: Towards a Unified Approach to Detecting Situational Impairments

arXiv: https://arxiv.org/abs/2403.04008 · HTML: https://mlsanity.com/paper/2403.04008/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Mar 2024.

## Built on by (most cited first, 5 of 5)

- [Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review](https://mlsanity.com/paper/2501.12557/) (2025)
- [OmniQuery: Contextually Augmenting Captured Multimodal Memory to Enable Personal Question Answering](https://mlsanity.com/paper/2409.08250/) (2024)
- [PARSE-Ego4D: Personal Action Recommendation Suggestions for Egocentric Videos](https://mlsanity.com/paper/2407.09503/) (2024)
- [XR Blocks: Accelerating Human-centered AI + XR Innovation](https://mlsanity.com/paper/2509.25504/) (2025)
- [Generative Tutorial: Towards Live Contextualized Visual Instructions for Physical Tasks](https://mlsanity.com/paper/2609.24955/) (2026)

## Abstract (arXiv)

Situationally Induced Impairments and Disabilities (SIIDs) can significantly hinder user experience in contexts such as poor lighting, noise, and multi-tasking. While prior research has introduced algorithms and systems to address these impairments, they predominantly cater to specific tasks or environments and fail to accommodate the diverse and dynamic nature of SIIDs. We introduce Human I/O, a unified approach to detecting a wide range of SIIDs by gauging the availability of human input/output channels. Leveraging egocentric vision, multimodal sensing and reasoning with large language models, Human I/O achieves a 0.22 mean absolute error and a 82% accuracy in availability prediction across 60 in-the-wild egocentric video recordings in 32 different scenarios. Furthermore, while the core focus of our work is on the detection of SIIDs rather than the creation of adaptive user interfaces, we showcase the efficacy of our prototype via a user study with 10 participants. Findings suggest that Human I/O significantly reduces effort and improves user experience in the presence of SIIDs, paving the way for more adaptive and accessible interactive systems in the future.