Lower Limb Biomechanical Analysis of Healthy Participants

Biomechanical analysis techniques are useful in the study of human movement. This technique can be used for leveling biomechanical assessment in healthy participants using commercially available systems. In biomechanical analysis, it’s useful to have specific test of function like gait analysis combined with tests looking at muscular performance.

Understanding the relationship between muscle strength and the ability to perform functional tasks such as walking is needed in the future design of research studies and rehabilitation protocols. Demonstrating our protocol today is Francesco Ferraro, trial manager in our team. Before beginning the analysis, confirm that the participant is wearing tight non-reflective clothing such as cycling shorts or leggings and use double-sided adhesive tape to attach 25 passive reflective markers onto the participant according to the lower body configuration of the human body model as illustrated.

Use a joint ruler to take measurements of the required knee and ankle widths for the model and secure the participant to a safety harness that is fastened to an overhead frame. Start a new session in the database and make sure the session is active. Under the Subject tab, click the Labeling Skeleton button and navigate to the Lower Limb HBM N2 VST file to create a new participant.

Enter the name of the participant and click OK.The name of the participant will appear in the subjects window. In the tools windows, open the Subject Preparation tab. Click to zero level the force plates and ask the participant to stand in the middle of the treadmill while walking at a comfortable speed for five minutes immediately following the acclimatization and click Start Recording in the software to begin recording the gait data.

Stop the recording after acquiring the desired amount of data. To remove the high-frequency noise in the data, open the processing software, select a low-pass filter for the marker data, and determine the individual strides from the vertical force data using the foot markers to ascertain the gain events. Export the data as a CSV file.

The gait parameters such as the kinematic, kinetic, and spatial temporal data can then be analyzed. To measure the participant’s muscle strength based on the maximum voluntary isometric contraction, first attach the tool pad number 701 to the dynamometer exercise head and have the participant sit on the chair with a back rest. To test the knee isometric muscle strength, use the up/down switch to align the dynamometer axis with the anatomical axis of rotation of the knee and place the pad of the tool centrally at the lower part of the shin of the tibia.

Have the participant position the knee at a 90 degree flexion with the hip in neutral rotation and abduction and the foot in plantar flexion. Then have the participant place their hands on their abdomen and stabilize the trunk, hips, and mid thigh on the chair with Velcro straps. To familiarize the participant with the testing maneuver, have the participant extend their knee before flexing to exert a maximum contraction on the command go for three seconds while providing verbal prompts and encouragement.

When the participant is comfortable with the procedure, ensure the participant that they can stop the test immediately if they experience any unusual pain or discomfort and allow the participant for rest for two minutes. Then repeat the trial three times for the left leg and three times for the right leg as just demonstrated recording and exporting the data in Newtons. Here, the mean and standard deviation of the spatial temporal, kinematics, and kinetic gait parameters of 30 participants from a representative analysis are shown.

As observed in this table summarizing the mean and standard deviation of the maximum voluntary isometric contraction for the knee joints of the participants, on average, the right knee demonstrated a slightly more robust extension and flexion in the assessed participants. In this offline analysis of the gait assessment of one participant, the spatial temporal data and kinematic and kinetic gait cycle for the left side of the participant can be observed. These data were similarly reproduced when the spatial temporal data and kinematic and kinetic gait cycle for the right side of the participant were assessed.

Clinical research has identified clear links between human biomechanics characteristics and different medical conditions. This protocol can be used for the accurate and comprehensive testing of combined gait analysis and muscle strength in a way that has not been previously described. Future research in orthopedic surgery will require accurate and repeatable techniques to measure gait.

The data collected through the technique described is consistent with international reference data for gait analysis and isometric muscle strength testing.