IoT-based load monitoring system for rehabilita… — Enterprise Case Study

IOT · IoT sensors · force measurement · edge processing · rehabilitation devices · Bluetooth connectivity

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Problem context

Incorrect weight-bearing during rehabilitation after lower-limb injuries significantly increases the risk of re-injury, prolonged recovery, and additional surgical interventions. Existing rehabilitation tools rely heavily on patient self-assessment and periodic clinical supervision, providing no objective, continuous feedback during daily recovery activities. The objective was to engineer a connected edge device capable of measuring load in real time, operating reliably in uncontrolled environments, and integrating seamlessly into existing rehabilitation workflows.

Constraints

  • Accurate force measurement under dynamic, real-world loads
  • Compatibility with a wide range of existing crutch designs
  • Real-time feedback without continuous clinician supervision
  • Low-power operation suitable for daily use
  • Wireless data transmission without interrupting patient mobility
  • Minimal disruption to established rehabilitation routines

Engineering decisions

Decision: Use crutch-mounted force sensing instead of in-shoe sensors
Reason: Crutch tips provide a mechanically stable reference point and avoid the customization and variability inherent to footwear-based solutions.
Trade-off: Required development of a universal mechanical attachment mechanism.
Decision: Integrate high-precision strain gauges with edge-level processing
Reason: Local signal processing enables immediate feedback and reduces dependency on continuous connectivity.
Trade-off: Increased firmware and calibration complexity.
Decision: Implement Bluetooth-based communication for optional data synchronization
Reason: Wireless connectivity allows analytics and clinician visibility without making connectivity a single point of failure.
Trade-off: Required robust handling of intermittent connections.
Decision: Provide multi-modal feedback directly at the device level
Reason: Immediate visual feedback improves compliance without requiring constant mobile interaction.
Trade-off: Additional hardware and power management considerations.

System overview

The system consists of a sensorized crutch tip equipped with force sensors, an embedded microcontroller, and wireless communication. Load data is captured and processed locally to determine whether the patient is adhering to prescribed weight-bearing protocols. Feedback is delivered in real time via on-device indicators, while detailed analytics can be transmitted wirelessly for later review. The architecture treats the device as an autonomous IoT edge node operating reliably without cloud dependency.

Outcome

Objective, real-time measurement of weight-bearing behavior. Reduction in protocol deviations during rehabilitation. Faster recovery timelines observed in controlled testing (up to 20%). Improved patient confidence and clinician visibility. Validated prototype suitable for further scaling and production.

Engagement delivered under NDA. Details anonymized.

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