Sensor Node with Position Validation Towards Camptocormia Measurement at Home

This paper presents an optical sensor position validation system for wearable sensors, especially inertia sensors for camptocormia assessment at home. The system combines motion data analysis with a histogram-based marker detection algorithm. A hardware implementation is presented that includes an optical sensor, IMU sensor, microcontroller, and Bluetooth LE module. A computationally low-cost algorithm is proposed to analyzes histograms of raw image data to establish an absolute reference and detect sensor displacement. Measurements on different skin tones demonstrate the extraction of position features (positioned on top of marked skin, unmarked skin, on the boundary, or lifted off). The proposed system has the potential to ensure data acquisition continuity in camptocormia angle tracking, addressing sensor displacement challenges in home assessments.