Written by: Carl Alano (MSc Student)
With lower back pain (LBP) being a very common disorder, affecting over 500 million people annually across the globe. Majority of these cases (up to 90%) are classified as ‘non-specific’, meaning that the pain cannot be attributed to any specific injury or pathology. However, recent research suggests a link between a person’s movement (motor control) and the associated disability with LBP. By objectively investigating the range of motor behaviours used in the control of the spinal column, it is believed that specific subgroups of dysfunction may be distinguished.
Carl Alano’s current MSc thesis research aims to use artificial intelligence to estimate movement through a video camera and understand the relationship between the movement and a person’s perceived disability, fear of movement, physical activity, and other things. To gather data, this study takes advantage of worldwide smartphone availability. We use 2D video cell-phone camera inputs and leverage open-source human pose estimation software (MediaPipeTM, Google) to analyze the movement.
This is software is a markerless solution for high quality body pose tracking. With the video data gathered from a camera, the software’s detector locates the person with the frame and predicts the location of 33 pose landmarks for every frame (Figure 1). These data are then exported as a .csv file for further post-processing in MATLAB where we differentiate motor signatures from healthy participants and those with LBP.

With this research aiming to sample a total of 1000 participants, Carl is currently focused on recruitment. Various strategies have been explored including news articles (Brock News, Toronto Star, etc..), news coverage (OMNI news), social media, posters and in-person booths.

Participating takes only 10 minutes and can be completed from anywhere using your phone!
Access the study link here, or by scanning the QR code below.

If you have any questions, please do not hesitate to reach out, my email is: ca18ei@brocku.ca