BIBIBOP

What inspired usWe were inspired by the common struggle of people like "Adi," who are dealing with hair loss and using standard red light therapy caps. We saw a critical flaw in these devices: they're "dumb." They deliver a static, one-size-fits-all dosage that completely ignores the unique contours of a user's head. This results in an inefficient treatment, where some areas get too much light and others get far too little. We knew we could build a "smart" device that solves this problem.How we built itOur project, BIBIBOP, is the first adaptive photobiomodulation device. To achieve this, we moved beyond a simple "on/off" switch and built a sophisticated feedback system:Sensor Integration: We integrated a matrix of reflective IR sensors throughout the cap's interior.Scalp Mapping: When the user puts the cap on, these sensors create a real-time topographical map of their scalp by measuring the precise distance to the skin at hundreds of points.Dynamic Control: This map data is fed into our custom control algorithm, which instantly and dynamically modulates the intensity of each individual LED.This ensures that every single follicle, regardless of its position on the scalp's curves, receives the precise, clinically-optimized light dosage.What we learnedWe learned that personalization isn't just a feature; it's essential for efficacy. The biological goal of red light therapy is to maximize mitochondrial activation and boost ATP (Adenosine Triphosphate) synthesis within the cells. Our work confirmed that a generic, one-size-fits-all approach is a significant bottleneck. By delivering an adaptive, precise dosage to all target follicles, we can achieve a far more efficient and powerful treatment, leading to better and faster results.Challenges we facedOur main challenge was developing the closed-loop control system. This involved several hurdles:Sensor Noise: Getting clean, reliable distance data from the IR sensor matrix in a complex environment (around hair) was difficult and required significant filtering.Algorithm Development: Creating the control algorithm to translate the topographical map data into thousands of simultaneous, real-time intensity adjustments for each LED was computationally complex.Calibration: Determining the "clinically-optimized" light dosage (the target $fluence$) and then calibrating the algorithm to deliver it accurately across varying distances was the most critical and time-consuming part of the project.

Built With

• ir
• lasers
• red
• resistors
• sensors
• wires