Cervical ROM Testing Overview
Location
Ada, Ohio
Start Date
9-12-2025 12:20 PM
End Date
9-12-2025 12:30 PM
Description
In clinical practice, there are two common methods used to assess neck range of motion, and the Cervical ROM test is the most widely recognized. This technique involves the nurse practitioner placing a goniometer on specific anatomical landmarks to measure how far the patient can move their neck in different directions. By aligning the device with these landmarks, the practitioner can obtain precise measurements that help evaluate mobility, identify movement limitations, and guide treatment decisions.
This technique raised several concerns for Dr. Ammar, which led him to pose a series of important questions. He asked how the range of motion of the neck could be measured with greater accuracy and how generative imaging might be used to improve this process. These questions became the foundation of my research and guided my first step, which was selecting the software that would support the design. The main difference in our approach is the use of an avatar that mirrors the patient’s movements instead of sending actual video footage to the clinician. This method also removes the need for physical contact with the patient, addressing another concern related to traditional assessment techniques.
When reviewing different software options, MediaPipe stood out as the most accessible choice because it is a Google product and familiar to many users. It is also easy to set up and does not require significant computing power, which makes it practical for testing and development. For data collection, MediaPipe allows simple angle measurements that can be used to determine three key ranges of motion in the neck: extension and flexion, rotation, and lateral flexion. This made it a strong fit for the goals of the project. As of now, the research is still in progress, so there are no significant findings to report. The next steps involve testing the accuracy of the collected data by comparing it to measurements from the Cervical ROM test. After that, the focus will shift toward improving the documentation process and refining the data collection methods to make them more efficient and reliable.
Looking ahead, this project has the potential to move far beyond the assessment of neck motion. The same process used to analyze cervical mobility could also be applied to shoulder movement or even adapted to evaluate the range of motion in other joints throughout the body. With further development, this approach could support the assessment, analysis, and documentation of mobility across multiple anatomical structures, creating a versatile tool for clinicians and researchers.
Overall, this project aims to improve the accuracy and accessibility of range-of-motion assessment by combining generative imaging, avatar-based modeling, and software such as MediaPipe. Although the research is still ongoing, the framework shows strong potential for providing more consistent measurements, reducing the need for physical contact, and expanding mobility analysis to multiple areas of the body. As the project continues, the focus on validation, documentation, and optimization will help refine the system into a more reliable and comprehensive clinical tool.
Recommended Citation
Murphy, Londen, "Cervical ROM Testing Overview" (2025). College of Engineering Student Research Colloquium. 2.
https://digitalcommons.onu.edu/eng_student_research_colloquium/2025/Presentations/2
Cervical ROM Testing Overview
Ada, Ohio
In clinical practice, there are two common methods used to assess neck range of motion, and the Cervical ROM test is the most widely recognized. This technique involves the nurse practitioner placing a goniometer on specific anatomical landmarks to measure how far the patient can move their neck in different directions. By aligning the device with these landmarks, the practitioner can obtain precise measurements that help evaluate mobility, identify movement limitations, and guide treatment decisions.
This technique raised several concerns for Dr. Ammar, which led him to pose a series of important questions. He asked how the range of motion of the neck could be measured with greater accuracy and how generative imaging might be used to improve this process. These questions became the foundation of my research and guided my first step, which was selecting the software that would support the design. The main difference in our approach is the use of an avatar that mirrors the patient’s movements instead of sending actual video footage to the clinician. This method also removes the need for physical contact with the patient, addressing another concern related to traditional assessment techniques.
When reviewing different software options, MediaPipe stood out as the most accessible choice because it is a Google product and familiar to many users. It is also easy to set up and does not require significant computing power, which makes it practical for testing and development. For data collection, MediaPipe allows simple angle measurements that can be used to determine three key ranges of motion in the neck: extension and flexion, rotation, and lateral flexion. This made it a strong fit for the goals of the project. As of now, the research is still in progress, so there are no significant findings to report. The next steps involve testing the accuracy of the collected data by comparing it to measurements from the Cervical ROM test. After that, the focus will shift toward improving the documentation process and refining the data collection methods to make them more efficient and reliable.
Looking ahead, this project has the potential to move far beyond the assessment of neck motion. The same process used to analyze cervical mobility could also be applied to shoulder movement or even adapted to evaluate the range of motion in other joints throughout the body. With further development, this approach could support the assessment, analysis, and documentation of mobility across multiple anatomical structures, creating a versatile tool for clinicians and researchers.
Overall, this project aims to improve the accuracy and accessibility of range-of-motion assessment by combining generative imaging, avatar-based modeling, and software such as MediaPipe. Although the research is still ongoing, the framework shows strong potential for providing more consistent measurements, reducing the need for physical contact, and expanding mobility analysis to multiple areas of the body. As the project continues, the focus on validation, documentation, and optimization will help refine the system into a more reliable and comprehensive clinical tool.