Foxconn taps NVIDIA to accelerate robotics for healthcare

Source: TCVGH, Foxconn, Kawasaki Heavy Industries via NVIDIA. Robot in a hospital corridor. TCVGH is conducting a field trial with Nurabot.
Source: TCVGH, Foxconn, Kawasaki Heavy Industries via NVIDIA. TCVGH is conducting a field trial with Nurabot.

Taichung Veterans General Hospital (TCVGH), Baishatun Tung Hospital – Mazu Hospital, and Cardinal Tien Hospital are some of the Taiwan-based healthcare institutions using Foxconn’s smart hospital solutions to support clinicians and advance patient care.

“Taiwan has a highly developed healthcare infrastructure with a strong push toward digital health transformation, creating the ideal environment for robotic integration,” said Shu-Fang Liu, Deputy Director of the nursing department at TCVGH, which is currently conducting a field trial with Nurabot, a collaborative nursing robot. The hospital began working with Foxconn in 2024 to codevelop the Nurabot robots as part of itssmart healthcare initiative led by Dr Shih-An Chen, Honorary Superintendent at TCVGH.

Liu added:Robots are augmenting our capabilities so we can provide more focused, meaningful care.”

Recognised as one of the world’s top 100 smart hospitals, TCVGH is developing multiple solutions to address the severe shortage of nursing personnel in Taiwan. In addition to implementing welfare policies to retain talent, the hospital is harnessing AI technology to ease the burden on frontline staff, noted Dr Yun-Ching Fu, the hospital’s Superintendent.

Foxconn’s smart hospital solution begins in the data centre, where high-performance compute is applied to develop large AI foundation models like FoxBrain, a large language model (LLM) developed using the NVIDIA NeMo framework. Trained on NVIDIA Hopper GPUs, FoxBrain is capable of text-to-speech, automatic speech recognition and natural language processing. 

Nurabot — built by Foxconn and Japanese multinational company Kawasaki Heavy Industries — uses the FoxBrain LLM, virtual training with Isaac for Healthcare and onboard compute powered by the NVIDIA Holoscan sensor processing platform running on an NVIDIA Jetson Orin device.

Foxconn is working with TCVGH, Baishatun Tung Hospital – Mazu Hospital, and Cardinal Tien Hospital to simulate healthcare facilities using NVIDIA Omniverse. With these physically-accurate simulations, the hospitals are planning out the design of new facilities, making data-driven decisions to optimise operations and building simulations to train robots.

TCVGH, for instance, built a digital twin of one of its nursing stations and wards as a training ground for Nurabot, enabling the robotic system to practice navigating through virtual hallways before testing in the real world.

Foxconn estimates that when deployed in clinical applications for delivering medication, transporting specimens and patrolling wards, Nurabot can reduce the workload of nurses by up to 30%.

“In one of our wards, we are using Nurabot to deliver wound care kits and health education materials to patient bedsides,” said Liu. 

“For nurses, having a robot assistant reduces physical fatigue, saving them multiple trips to supply rooms and allowing them to focus more on patients.”

During visiting hours, Nurabot helps guide patients and visitors through the ward, reducing the administrative workload for frontline staff. And during night shifts, when hospitals typically operate with fewer staff, it can help pick up the slack.

Liu hopes the nursing robots will be able to converse with patients in multiple languages, recognise individuals to enable personalised interactions, and help nurses move patients in future. Someone with a lung condition, for example, may need the help of two nurses to get up from their hospital bed and move to a chair for breathing exercises. With Nurabot's help, the task might be accomplished with a single nurse.

TCVGH’s field trial with Nurabot is drawing positive reactions from nurses and patients, and the hospital expects to deploy dozens of robot units to support its nursing team by the end of this year. 

Foxconn is also using its Honhai Super AI Computing Center 1, which features NVIDIA DGX systems, to develop healthcare-specific AI models. Offered through Foxconn’s CoDoctor AI platform, powered by NVIDIA AI, these models improve diagnostic accuracy and optimise clinical workflows for tasks including retinal imaging, vital sign monitoring, arrhythmia screening and cancer screening.

Foxconn is also working with medical centres to integrate the NVIDIA AI Blueprint for video search and summarisation, which can analyse real-time video data to alert healthcare workers of medical events and generate visual summaries for hospital management teams.

It will contribute CoroSegmentater, its AI model for coronary artery segmentation, to the MONAI open-source medical imaging platform pioneered by NVIDIA and leading academic medical centres. The model, powered by MONAI’s Auto3DSeg framework for 3D medical image segmentation, can be used to support diagnostics, preoperative planning and patient education.

Clinical teams can visualise these segmentations on 3D visualisations of the heart and vascular system running on NVIDIA OVX servers with NVIDIA Isaac for Healthcare, built on the NVIDIA Omniverse platform. Foxconn has also used Omniverse to develop a tool that can simulate the effects of drug treatments on the tumors of breast cancer patients.

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