ArticleFrontiers in robotics and AI2026
ROS 4 healthcare: a framework for physiological human sensing for social, assistive, rehabilitation, and medical robotics.
Article in Frontiers in robotics and AI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Erratum issued
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The pervasive integration of robots into daily life necessitates advanced human-robot interaction (HRI) capabilities, particularly the accurate understanding of human physiological and cognitive states. The current state of the widely used Robot Operating System (ROS2) lacks standardized mechanisms for representing and communicating human states. This paper introduces ROS 4 Healthcare (ROS4HC), a comprehensive open-source framework designed to standardize the acquisition, representation, and integration of human sensing data into robotic systems. ROS4HC provides unified message types, modular sensor drivers, signal processing libraries, and visualization tools for physiological, biological, and physical signals. This framework is validated through empirical case studies in healthcare robotics, including a heart rate (HR)-adaptive wheelchair velocity modulation, an autonomous treadmill system integrating physiological feedback, and a nocturnal monitoring system based on a robotic rocking bed. These case studies demonstrate that the framework enables modular component reuse, standardized communication, and interoperability for better human-robot integration. Beyond healthcare, we highlight ROS4HC's generalizability for critical applications such as industrial safety, human-robot collaboration, and performance monitoring, establishing a standardized infrastructure for safer, more adaptive, and context-aware robotic systems across diverse domains.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.