Height is an essential parameter in healthcare, influencing BMI calculations and nutritional planning for hospitalized patients. While measuring height is straightforward for standing individuals, it becomes challenging for critically ill and immobile patients. The absence of an efficient height measurement method for bedridden patients can lead to gaps in medical care.
This project aims to develop a non-invasive height measurement system for recumbent (lying) patients using computer vision techniques.
To achieve this, we propose two approaches:
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Landmark-Based Method (MediaPipe)
- Extracts body landmarks using Google's MediaPipe framework.
- Uses geometrical formulas to calculate skeletal length in 2D space.
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Bounding Box Method
- Defines a bounding box around the patient.
- Uses a pixel-to-height ratio to estimate the actual height.
- Helps improve accuracy when landmark detection fails due to poor lighting, occlusion, or complex postures.
📌 Published Paper: Height Measurement of Recumbent Individuals in 2D Space