Lower back pain affects more than 500 million people worldwide and is the leading cause of disability, above reported data of cancers and heart diseases.
But receiving a back pain diagnosis can take time, with patients often facing barriers that may delay the process.
Brock University Master of Science in Kinesiology student Carl Alano (BSc ’22) is determined to help patients receive their diagnosis faster — all with the help of artificial intelligence (AI).
Through his research, “Automated Movement Screen: Developing a data-driven scoring tool to assess spine motor dysfunction,” Alano is working to develop a telehealth screening tool for clinicians.
“Back pain is typically hard to diagnose without using a movement assessment test in clinic,” Alano says. “Identifying movement patterns with the naked eye can be difficult, and for those without access to an allied health team because they may be living in rural settings or suffering from limited access due to the COVID-19 pandemic, proper care is further challenged.”
Using AI software called MediaPipe, Alano inputs images and videos of common tasks requiring movement of the lower back into software for analysis. The data are aligned with patient-reported outcomes to understand the relationship between how someone moves and how they reportedly feel.
“The aim of our work is to automate movement analysis and to help alleviate the need for in-person appointments,” Alano says. “Particularly, since many cases of low back pain are classified as ‘non-specific,’ meaning the pain cannot be attributed to any specific injury or cause.”
To accomplish this, research participants aged 18 to 65 years complete an online survey and are asked to submit video of themselves performing three different movement tasks: picking up a pen or pencil, completing a single body weight squatting motion and doing a maximum spine flexion, which is when an individual rounds their spine as much as they can comfortably.
The data derived from the survey then allows the team to build an algorithm that scores someone’s movement using a web camera or smartphone and predicts levels of disability.
“The research takes a data-driven approach to uncover hidden patterns that are aligned with clinically meaningful outcomes,” Alano says. “To get a good idea of how one individual compares to others, we need a large number of participants with a wide range of ages, activity levels and low back-related disability.”
The idea for this research emerged during Alano’s fourth-year undergraduate thesis, which looked at back pain in rowers. Even though COVID-19 restrictions were easing, athletes were hesitant to come to campus or had scheduling conflicts, which made it difficult to recruit participants.
“I started looking at ways AI could help in the collection and analysis of data because it can be done from anywhere with an internet connection,” Alano says. “I want my research to have an impact and to do this we need a lot of data. Historically, we have suffered from small sample sizes; this is where AI can help.”
Growing up in the Philippines, Alano observed the hardships faced by individuals with socio-economic challenges as well as those who had to travel long distances for medical care. This experience motivated him to make a difference by pursuing a career in the medical field.
“As an undergraduate Medical Sciences student at Brock, and a patient with a torn anterior cruciate ligament, I often thought about how in-person appointments can take two to three hours,” says Alano, who completed his bachelor’s degree at Brock last year. “This motivates me to find new ways to streamline diagnostic workflow, benefitting patients though expedited assessments, creating access to underserved demographics and freeing up valuable clinician time.”
A video demonstrating the assessment process is available on YouTube.