Early Breast Cancer Detection Device
An innovative IoT-enabled smart bra designed for early breast cancer detection using advanced sensors and medical electronics. This wearable medical device leverages my background in medical electronics and sensor technology to create a non-invasive, continuous monitoring solution for women's health.
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Multiple medical-grade sensors for detecting tissue changes, temperature variations, and other early cancer indicators.
24/7 passive monitoring that collects data during normal daily activities without user intervention.
AI algorithms trained to identify patterns and anomalies that may indicate early-stage breast cancer development.
Secure, encrypted transmission of health data to healthcare providers and mobile applications.
Ergonomic design that can be worn comfortably throughout the day while maintaining sensor accuracy.
Designed with medical device standards and regulations in mind for potential clinical use.
Functional prototype with integrated sensor array
Real-time sensor data analysis and pattern recognition
Mobile application for data visualization and health insights
Developing sensors sensitive enough to detect early-stage changes while avoiding false positives in a wearable form factor.
Implemented multi-modal sensing approach combining temperature, pressure, and bioimpedance sensors with advanced signal processing algorithms to improve detection accuracy.
Creating a device that can operate continuously for extended periods while maintaining a comfortable, lightweight design.
Developed ultra-low-power sensor circuits and implemented intelligent duty cycling to extend battery life to several days between charges.
Navigating complex medical device regulations and ensuring the device meets safety and efficacy standards for health monitoring.
Collaborated with medical professionals and regulatory experts to ensure design compliance with medical device standards and established pathways for clinical validation.
Extensive research into breast cancer detection methods and sensor technologies.
Developed and tested various sensor configurations for optimal detection capabilities.
Built functional prototype with integrated sensors, processing unit, and wireless communication.
Developed machine learning algorithms for pattern recognition and anomaly detection.
Looking back, I would focus more on user testing early in the development process, implement better error handling from day one, and spend more time on the initial architecture planning. These learnings have shaped how I approach new projects today.