Developer Team
Meet the ResQ development team. Click a card to view the official profile.
Understanding the project, its scope, and our engineering approach
CPR (Cardiopulmonary Resuscitation) is a critical life-saving skill, but traditional training on manikins has significant limitations:
Core challenge: CPR training lacks real-time, objective, scalable measurement and feedback to ensure consistent learning and competency validation.
ResQ adds intelligent sensing and live analytics to CPR manikins, transforming training into a data-driven, measurable learning experience.
A 2×2 TPU bladder array mounted under the sternum plate detects compression force and distribution. Pressure sensors quantify chest compression, while a Hall-effect sensor + magnet arrangement measures compression depth. All data flows through an ADC for precise analog-to-digital conversion.
Embedded firmware reads sensors in real-time and computes: compression count (event detection), rate in compressions per minute (cpm), depth estimate (mm), pause time, and placement drift (left/right/up/down). Data is processed locally and sent to the dashboard.
A web-based dashboard displays live graphs and performance indicators. Instructors see real-time feedback on student performance, can monitor multiple students simultaneously, and provide evidence-based coaching.
Sessions are automatically saved with performance summaries and scores. Instructors can add comments and coaching notes. Reports export to CSV/PDF for documentation, student feedback, and certification records.
Result: CPR training becomes objective, data-driven, scalable, and measurable. Students get immediate feedback for faster learning. Instructors gain insight into performance patterns and can make targeted improvements to their training programs.
Medical educators and CPR training coordinators who need to assess multiple students objectively, track performance over time, and provide evidence-based coaching.
Healthcare professionals, first responders, and anyone pursuing CPR certification. They benefit from immediate feedback and measurable progress tracking.
Hospitals, medical schools, fire departments, and certification programs seeking to improve training consistency and maintain compliance documentation.
Real-time feedback allows students to self-correct immediately, accelerating the learning curve compared to subjective feedback alone.
CPR quality measured by quantitative metrics (depth in mm, rate in cpm) eliminates bias and ensures consistent evaluation standards.
Automatic session logging and exportable reports provide auditable evidence of training and competency for certification.
Instructors can monitor multiple students simultaneously, increasing class capacity and reducing one-on-one coaching time per student.
Historical performance data reveals common error patterns and supports targeted program improvements.
Objective measurement against evidence-based standards (AHA CPR guidelines) builds confidence in learned skills.
Completed: Hardware design, firmware architecture, dashboard mockups, calibration strategy defined.
In Progress: TPU bladder array fabrication, pressure sensor integration, Hall-effect depth sensor setup, mechanical mounting.
In Progress: Sensor reading, event detection, compression calculations, and payload formatting.
Planned: Web dashboard development, real-time graph rendering, session management UI.
Planned: Calibration validation, bench testing, real manikin trials, instructor feedback incorporation.
Planned: Final demo preparation, documentation, and project handover.
Next Steps: Complete hardware mechanical integration, finalize sensor calibration strategy, and begin dashboard UI prototyping in parallel.
Meet the ResQ development team. Click a card to view the official profile.
