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ORIGINAL RESEARCH article

Front. Robot. AI

Sec. Biomedical Robotics

This article is part of the Research TopicMultimodal Perception and Biosignal Integration for Adaptive Healthcare RoboticsView all articles

ROS 4 Healthcare: Physiological Human Sensing for Social, Assistive, Rehabilitation, and Medical Robotics

Provisionally accepted
Ricardo Javier Manríquez-CisternaRicardo Javier Manríquez-Cisterna1*Pranjal MishraPranjal Mishra2Jorge Peña-QueraltaJorge Peña-Queralta3Mónica Perez SerranoMónica Perez Serrano2Spyridon GaryfallidisSpyridon Garyfallidis2Lucas KupperLucas Kupper2Mehdi EjtehadiMehdi Ejtehadi2Alexander BreussAlexander Breuss2Ankit A. RavankarAnkit A. Ravankar1Jose Victorio Salazar LucesJose Victorio Salazar Luces1Robert RienerRobert Riener2Yasuhisa HirataYasuhisa Hirata1Diego PaezDiego Paez2
  • 1Tohoku University, Sendai, Japan
  • 2Eidgenossische Technische Hochschule Zurich, Zürich, Switzerland
  • 3ZHAW Zurcher Hochschule fur Angewandte Wissenschaften School of Engineering, Winterthur, Switzerland

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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. This paper introduces ROS 4 Healthcare (ROS4HC), a comprehensive open-source Robot Operating System (ROS2) framework designed to standardize the integration of human sensing data into robotic systems. It provides unified message types, sensor drivers, processing libraries, and visualization tools for physiological, biological, and physical signals. We demonstrate the practical utility and real-world deployment through empirical case studies in healthcare robotics, including a Heart Rate (HR)-adaptive wheelchair velocity modulation, an autonomous robotic treadmill and a nocturnal monitoring system. Beyond healthcare, we highlight ROS4HC's generalizability for critical applications such as industrial safety, human-robot collaboration, and performance monitoring, showcasing its role in enabling safer, more adaptive, and context-aware robotic systems across diverse domains.

Keywords: biosignals, Healthcare robotics, human-robot interaction, medical robotics, open-source, rehabilitation robotics, Robot Operating System, social robotics

Received: 12 Nov 2025; Accepted: 28 Jan 2026.

Copyright: © 2026 Manríquez-Cisterna, Mishra, Peña-Queralta, Perez Serrano, Garyfallidis, Kupper, Ejtehadi, Breuss, Ravankar, Salazar Luces, Riener, Hirata and Paez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Ricardo Javier Manríquez-Cisterna

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Supplementary Material