Aegis Medtech

Aegis is a smart cushion that stops pressure ulcers before they start. It uses a built-in sensor grid to find high-pressure spots and automatically shifts air to protect the user's skin.

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Inspiration

It has been estimated that the total cost of treating pressure ulcers in the UK alone is £1.4 to £2.1 billion annually. When evaluating current solutions, we discovered a massive Innovation Gap. The standard of care relies on passive cushions and the labor-intensive manual method of repositioning patients. We wanted to give independence back to wheelchair users by creating an autonomous, AI-driven tissue preservation system.

What it does

Aegis Medtech is a smart, autonomous wheelchair cushion designed to shift from reactive wound management to predictive injury prevention. Predictive AI: Our machine learning model predicts high-risk tissue inflammation days before an ulcer forms. Microclimate Control: The cushion detects moisture buildup to maintain an optimal moisture balance and prevent skin damage. Discreet Biofeedback: Provides simple, discreet alerts to the user to encourage weight shifting.

How we built it

We engineered a hybrid sensor stack using advanced nanocomposite materials. To measure the exact "dose" of pressure the skin has absorbed over time, we implemented a continuous integration algorithm to calculate the localized Pressure-Time Integral ($PTI$):$$PTI=\int_{0}^{t}P(t)dt$$When the calculated $PTI$ exceeds safe physiological thresholds, our AI triggers the active off-loading mechanism. Here is a simplified code snippet showing our logic: def calculate_pti(pressure_data, time_delta): # Calculate cumulative pressure over time pti = sum(p * time_delta for p in pressure_data)

# Trigger active redistribution if threshold is exceeded
if pti > SAFETY_THRESHOLD:
    trigger_active_redistribution()

return pti

Challenges we ran into

Achieving true "Autonomous Operation" was difficult. Bridging this gap meant designing a system that could automatically redistribute pressure based on real-time data while remaining highly energy-efficient.

Accomplishments that we're proud of

We successfully translated 18 distinct clinical and user needs into a cohesive, functional system. We are incredibly proud of shifting the technology from a "dumb" passive surface to an intelligent, data-driven medical device. By integrating deep tech, IoT, and AI, we built a solution that perfectly aligns with the innovation standards championed by the START Summit.

What we learned

We learned that building successful medical technology requires balancing the rigorous, objective needs of the healthcare system (like precise data logging and sensitivity) with the deeply personal needs of the end-user (like comfort, breathability, and social discretion). A clinical device only works if the patient actually wants to use it in their daily life.

What's next for Aegis Medtech

Our next steps involve refining the active redistribution actuators and optimizing our machine learning algorithms for real-time edge computing. We also want to work on clinical validations.

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