What it does
MEDI X offers a patient monitoring service (web/app), the IVY camera, and the Alerter device. Using FaceTech-based nonverbal signal detection, it enables real-time insight into patient changes, helping nurses focus more on care than data analysis.
Your inspiration
Through surveys and interviews with nurses, the following pain points were identified: Judgments based on numerical data can miss deeper changes or potential risks, forcing nurses to rely on experience and intuition. There is no system for real-time detection of emergencies, such as self-removal of oxygen therapy devices, making round-the-clock monitoring difficult and delaying response. They also have many side tasks, making it difficult to focus on patient care. Therefore, there is a need to reduce the burden on nurses and provide a real-time patient monitoring experience through FaceTech-based nonverbal signal detection.
How it works
IVY is a smart bedside monitoring device using FaceTech AI to analyze and record nonverbal patient cues—facial expressions, movement, and temperature—in real time. The central CAMBAR houses three cameras: an AI facial camera, a motion-tracking camera, and an infrared camera. These are hidden behind the LED display via UPC (Ultra Privacy Cover) to protect patient privacy. The display shows status through color: blue (stable), yellow (caution), red (critical). CAMBAR adjusts vertically and horizontally with a slide bar and ball joint, and AI auto-tracking keeps the face centered. IVY comes in stand and ceiling-mounted models to suit various hospital environments. The Allerter alerts nurses to emergencies via vibration and red LED. Pressing its button stops the alert and sends a response log to the system. It runs on replaceable batteries and supports wireless wear for flexible use.
Design process
We identified user needs and defined the project direction through an online survey of around 100 nurses and interviews with 8 actual nurses. We analyzed stakeholders involved in nurses’ monitoring tasks and added doctors as key stakeholders to define user needs for both nurses and doctors. After designing the overall user flow for both software and hardware, we conducted Brain-writing with AI to develop specific functions and visual elements. Based on this, we created behavioral, form, and engineering sketches, using AI as a visual and concept assistant to exchange feedback and refine ideas. For the software, we created an information architecture and revised the user flow accordingly, then built a prototype using Figma. Using this prototype, we conducted eye-tracking tests with real nurses. Results showed that differences between the existing EMR mental model and MEDIX’s structure made it hard to find key info. Integrated visibility and accessibility of the user flow emerged as critical. We then restructured the information hierarchy and revised the output based on real ICU workflows and systems nurses face in practice.
How it is different
While many medical devices are designed for patients or doctors, few focus on nurses—those who provide direct, continuous care. This system centers on nurses, aiming to reduce the burden of patient assessment and allow greater focus on caregiving. It offers 24/7 real-time detection of patient abnormalities, helping to cover blind spots in nurse surveillance. For less experienced nurses, FaceTech and on-device AI assist in interpreting subtle, nonverbal patient signals that may be difficult to assess. Unlike traditional devices, it is built on the familiar form of an IV stand, making it easy to integrate into ICU environments. As features were added and refined, the device maintained a space-conscious design suited for real clinical settings. From patient status detection to emergency alert history, the system is fully automated, enabling hands-free monitoring. By minimizing manual intervention, it reduces nurse workload and enhances patient care focus.
Future plans
Based on feedback from nurses during UI design, we adopted a familiar documentation format to ensure ease of use. However, we aim to move beyond the current EMR-focused interface by developing a new visual system that supports intuitive use, even in emergencies. We are also building a hardware prototype that considers real-world clinical constraints. Step-by-step testing will verify its applicability, installation, and operation in medical settings. Our goal is to ensure not only technological implementation but also clinical effectiveness and real usability.
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