Skip to main content
Back to Case Studies
Healthcare / Medical Devices
|Medical Device Manufacturer - India|
14 months
7 engineers

Smart Urinometer: Automated ICU Urine Output Monitoring System with Real-Time Analytics

Development of an FDA-compliant smart urinometer for ICU and post-surgical patients that automatically measures urine output, flow rate, and color analysis. Eliminates manual hourly measurements, reduces nursing workload by 40%, and provides early detection of acute kidney injury (AKI).

CE Marked
Class IIa Medical Device
99.5%
Measurement Accuracy
40%
Nursing Time Saved
6hr Earlier
AKI Detection
Smart Urinometer: Automated ICU Urine Output Monitoring System with Real-Time Analytics - Rapid Circuitry embedded systems case study hero image

The Challenge

A leading medical device manufacturer needed to modernize urine output monitoring in ICUs. Traditional urinometers require hourly manual readings, are prone to human error, and delay the detection of acute kidney injury - a condition that affects 50% of ICU patients.

Manual Measurement Burden

ICU nurses spend significant time on hourly urine measurements. Manual readings are often delayed, missed, or inaccurate, affecting patient care.

Impact: 12+ readings per patient/day

Delayed AKI Detection

Acute Kidney Injury develops rapidly but manual monitoring catches it 6-12 hours late. Early detection can prevent progression to kidney failure.

Impact: 50% ICU patients affected

Data Silos

Handwritten urine logs are not integrated with hospital EMR systems, making trend analysis and clinical decision support impossible.

Impact: No real-time analytics

Infection Control

Frequent manual handling of urine collection systems increases infection risk. The solution needed to be a closed system with minimal contact.

Impact: CAUTI prevention critical

Our Solution

We developed an intelligent urine monitoring system that automatically measures volume, flow rate, and urine characteristics, integrates with hospital systems, and uses AI to detect early signs of kidney dysfunction.

System Architecture

Comprehensive ICU monitoring solution with bedside device, nurse station display, and cloud-based analytics.

Bedside Device

  • Precision load cell for volume measurement
  • Optical flow sensor for real-time flow rate
  • RGB color sensor for urine analysis
  • Temperature sensor for sample integrity
  • Capacitive touch interface
  • WiFi + BLE connectivity

Nurse Station

  • Multi-patient monitoring dashboard
  • Real-time alerts and notifications
  • Trend visualization and reporting
  • Shift handoff summaries
  • Voice alert integration

Clinical Platform

  • HL7 FHIR EMR integration
  • AI-powered AKI prediction
  • Clinical decision support
  • Regulatory audit logging
  • Multi-hospital analytics

Custom Hardware Design

MCUESP32-S3 (WiFi + BLE + AI)
Load CellStrain gauge (0.1ml resolution)
Flow SensorOptical drop counter
Color SensorTCS34725 RGB sensor
Display2.4" TFT LCD with touch
PowerUSB-C with battery backup
ProtectionIPX4, IEC 60601-1 compliant

Medical-Grade Firmware Architecture

  • Real-time volume tracking with 0.1ml resolution
  • Flow rate calculation with trend analysis
  • Urine color classification (clear to dark amber)
  • Temperature monitoring for sample quality
  • Automatic hourly reporting to EMR
  • AKI risk score calculation (RIFLE criteria)
  • Alarm management with escalation logic
  • IEC 62304 Class B compliant software lifecycle

Implementation Timeline

Phase 1: Clinical Requirements & Design

10 weeks
  • ICU workflow analysis and nurse interviews
  • Clinical requirements with nephrologists
  • Risk analysis per ISO 14971
  • System architecture and design inputs

Phase 2: Hardware Development

14 weeks
  • Precision sensor selection and testing
  • PCB design with medical-grade components
  • Enclosure design for bedside mounting
  • 3 prototype iterations with clinical feedback

Phase 3: Firmware Development

16 weeks
  • IEC 62304 compliant development process
  • Sensor fusion algorithms
  • Alarm management system
  • EMR integration protocols
  • Unit testing (96% code coverage)

Phase 4: AI Model Development

12 weeks
  • Training data collection (5000+ patient records)
  • AKI prediction model development
  • Clinical validation study design
  • Edge inference optimization

Phase 5: Verification & Validation

10 weeks
  • IEC 60601-1 electrical safety testing
  • Clinical accuracy study (200 patients)
  • Usability testing with ICU nurses
  • Biocompatibility assessment

Phase 6: Regulatory Submission

8 weeks
  • Technical documentation compilation
  • CE Mark submission and review
  • FDA 510(k) preparation
  • Production transfer

Results & Impact

The Smart Urinometer has been deployed in 45 hospitals across India and Europe, significantly improving patient outcomes and reducing nursing workload in ICU settings.

Measurement Accuracy

vs 85% for manual readings

Nursing Time Saved

On urine monitoring tasks

AKI Detection

vs traditional monitoring

Documentation Compliance

vs 78% manual compliance

CAUTI Reduction

Fewer catheter infections

Hospitals Deployed

Across India & Europe

“The Smart Urinometer has transformed how we monitor critically ill patients. Early AKI detection has saved lives, and our nurses can focus on direct patient care instead of manual measurements.”

Head of Critical Care

Major Hospital Chain, India

Technologies Used

ESP32-S3Load CellsOptical SensorsTensorFlow LiteWiFiBLE 5.0HL7 FHIRReactNode.jsPostgreSQLAWS IoT

Related Case Studies

Healthcare / Medical Devices

Medical Wearable: FDA-Cleared Remote Patient Monitoring Device for Cardiac Care

Read Case Study

Ready to Build Your Success Story?

Let's discuss how our expertise can help bring your vision to life with measurable results like this project.

Start Your ProjectView More Case Studies