Purpose

    This activity is a lab module that aims to help students:

1. Experience a motion analysis scenario that represents a simplified real-world biomechanical engineering situation and make insightful connections to basic biomechanical principles (EM principle: Making connections).
2. To develop natural perceptive and curiosity about ranges of motions, velocity, and accelerations of their own body segment motions (EM principle: Curiosity).
3. To reduce the need for expensive motion analysis setups or equipment (EM principle: Creating value in our lab setting).
4. Be able to use the gained skills to measure the motion speed of different body parts and apply this knowledge in many applications, such as: sports, medical diagnosis, robotics, and many other.

Background

Delivery of a hands-on laboratory experience is a real challenge in a remote learning environment. Many instructors tend to acquire and record experimental data, and then instruct their students to analyze such data to produce results and lab reports in an online course mode. Such a process considerably diminishes students’ motivation, engagement, and eagerness to explore further knowledge, as students appreciate more the experimental data that they gather themselves, which in turn activates the sense of curiosity. Such drawbacks are even more profound in a practical field such as biomechanics, where students need to feel the sense of kinematic and kinetic data as measured using their own body motions and muscle forces to make the proper connections between theory and practice.   

Detailed Description of Activity

In this module, students first capture their selected body motion (of their own choice) with a webcam at home. They are provided a video tracking algorithm that calculates spatial locations of the body segment in motion. Students then perform calculations to estimate further kinematic and kinetic data, plot them, and comment on their own estimated muscle forces.

The motion experiment starts with placing two markers (such as white labels) on the two ends of the body part in motion (e.g. forearm motion). A webcam captures a short video (about 20-40 seconds) while the body part is in motion, so that all spatial positions of the body part would be captured. Video capturing was initiated using a small MATLAB script (MATLAB R2022b, MathWorks, Inc., Natick, MA, USA) which is provided to students by the author/instructor. This script starts the capturing process and saves the video file on the computer’s drive. The recorded video is then fed (by browsing the video file location) to a video tracking software module implemented by the author/instructor. The tracking module has been implemented with a custom MATLAB script, using the computer vision toolbox utilizing the Kanade-Lucas-Tomasi point tracking algorithm. The script generates two arrays of the estimated points displacements (in x and y coordinates) corresponding to the two ends of the body part in motion.

Since the tracking module provides point coordinates in pixel units, students are required to develop their own MATLAB scripts to perform the necessary coordinate translations and trigonometric transformations to calculate motion displacements in the units of degrees rather than pixels, with respect to the non-moving joint end (the assumed origin of new coordinates). Students are then asked to apply their prior DSP knowledge to implement signal filtering and smoothing techniques (typically Gaussian filters) in order to prepare the data for the differentiation step that follows (EM: making connections). The smoothed signal consecutive differentiations provide estimates of the final kinematic data (from angular joint displacements to velocities and accelerations) which in turn are used to calculate kinetic data (muscle forces and moments) by solving biomechanical equilibrium equations. These tasks allow students to use their previous understanding of trigonometric transformations, DSP techniques, mechanical equilibrium analysis to solve the problem in hand and estimate many motion parameters (EM: making connections). Students would plot the results and comment on their own estimated body motion parameters and how such results correlate with their own muscle forces (EM: enhance curiosity).

The attached presentation shows the complete process with sample student results (including graphs). Additionally, a complete sample students report is attached to this card that includes their reflections. It was quite interesting to see how student go creative and managed to implement the active marker bonus task using available components in their household (thermometer batteries!).