Capstone internship at the Agribiosystems machinery and Power Engineering Division (AMPED) with a mini-project on : prototyping a height measurement tool using machine vision systems
Date
3-2026
Adviser
Ynni E. Barredo
Co-adviser
Elisa SJ. Onal
Principal
Buela, Mabel S.
Abstract
Accurate height measurement is an essential variable in various healthcare settings, especially in monitoring and assessing growth patterns and nutritional status of children. However, access to these assessments is often limited in resource-constrained and rural areas, which also makes it difficult for Rural Health Workers (RHWs) to transport and efficiently use traditional stadiometers due to its bulk and weight. This study addresses the need for a more portable and intuitive alternative to help deliver basic health services to rural communities. An internship was conducted at the Agribiosystems Machinery and Power Engineering Division (AMPED), which aimed to enhance the researchers’ technical competencies in computer vision, programming, and hardware fabrication through the development of a machine-vision-based height-measuring prototype. The developed software utilized Python and OpenCV to process the captured images and estimate human height using a reference object. Its components consist of several detachable components, mainly a camera, tripods, a meter stick, and a device that can run the program. The prototype’s performance was evaluated by comparing its calculated measurements with those obtained from a traditional stadiometer across 37 participants. The statistical analysis was performed using a paired samples t-test at a level of significance (), α = 0.05along with error metrics such as Mean Absolute Error and Root Mean Square Error (RMSE). The prototype achieved a 100% detection rate and yielded low error values with an MAE of 1.60 cm and an RMSE of 1.61 cm. Results from the paired samples t-test indicated no significant difference between the two methods (). 𝑝=0.997Furthermore, the prototype achieved a significantly shorter processing time of 12.41 s compared to the stadiometer’s 15.80 s (p <0.001). These findings validate the effectiveness and accuracy of the developed prototype as a portable and reliable alternative to traditional stadiometers and demonstrate a strong potential for its use in healthcare settings.
Language
English
Location
UP Rural High School
Recommended Citation
Barros, Nicos G.; Saavedra, Evangeline V.; and Verang, Althea Dennise D., "Capstone internship at the Agribiosystems machinery and Power Engineering Division (AMPED) with a mini-project on : prototyping a height measurement tool using machine vision systems" (2026). Capstones. 214.
https://www.ukdr.uplb.edu.ph/etd-capstone/214
Document Type
Capstone