Hi,
I aim to compare the muscle states with MOCO using two musculoskeletal models: Hamner2010 and LaiArnold2017. Nevertheless, even though I am using the same static trial, marker position, and scaling setup between models, I have "slightly" different results. For instance, after scaling there is a 3 deg difference between models and this is even more visible when I run IK: Both models give similar patterns but not exactly the same (+/- 4 deg difference in each joint). As you can see in the following figures:
After scaling:
At IK:
Thus, I would like to know if there is something that I should do in order to have the same calibration (e.g. same IK) between these models. I am aware that the knee definition between models is different (thus ankle, knee, and the hip joint would be different), but I am not sure if this is the main issue (this would not explain why there is a difference in pelvis tilt which would affect hip flexion/extension).
I attach the static trial, marker position, and scaling setup for both models.
Israel
Comparing model hamner 2010 and laiArnold 2017 - Scale issue
- Israel Luis
- Posts: 11
- Joined: Thu Oct 24, 2019 3:21 am
Comparing model hamner 2010 and laiArnold 2017 - Scale issue
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- Ayman Habib
- Posts: 2248
- Joined: Fri Apr 01, 2005 12:24 pm
Re: Comparing model hamner 2010 and laiArnold 2017 - Scale issue
Hello,
Since the two models are different, the problem solved is different and the configurations that are taken by the models will likely be different as well. This a global problem over the whole model (sum of squares of marker errors) so I'm not sure why you're surprised that the answers are different. It's not an indication of anything wrong. You can change weights to affect the solution but having identical solutions is highly unlikely (based on your high level description of the issue). I also don't expect the differences to be localized though you can play with the weights to affect that.
Hope this helps,
-Ayman
Since the two models are different, the problem solved is different and the configurations that are taken by the models will likely be different as well. This a global problem over the whole model (sum of squares of marker errors) so I'm not sure why you're surprised that the answers are different. It's not an indication of anything wrong. You can change weights to affect the solution but having identical solutions is highly unlikely (based on your high level description of the issue). I also don't expect the differences to be localized though you can play with the weights to affect that.
Hope this helps,
-Ayman