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- Experimental data proved that it can help loaded walking by reducing metabolic costs.
- This suit applies force to lower limb joints by a cable through cables driven by the actuators on the backpack.
Challenge
As it is a new approach the Exosuit tries to assist human gait with deformable structure, there are many challenges in developing the exosuit. The challenges are
- It is difficult to analyze the effectivness effectiveness of the suit
- It is difficult to find the optimal input force for actuators to reduce the metabolic cost
- It is difficult to identify the effect of change of design parameters
The reasons for the challenges are
- The Exosuit suit is deformable and closely attached to a body
- We can not predicet predict how external actuation assists muscles during loaded walking as human body is highly redundant
- Experimental data is inconsistent case by case
Goals
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- Evaluate the effectiveness of wearing active actuator actuators on metabolic cost reduction during loaded walking.
- Explain how Exosuit can help loaded gait
- Verify the impact of changes of design parameters.
- Find optimal control inputs for exosuit actuators.Evaluate the effectiveness of Biarticular actuatoractive actuators
Strategy
Experimental data
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- The subject didn't wear a suit and walked freely.
- walking speeds are were identical in for both cases
- Mass of the load for loaded walking was 38kg.
Modeling
To simulate the movement of exosuit wearer, the first thing to do is to create a model which can replicate a real subject as possible as we can. Before I created our the simulation model with active actuator actuators on it, I had the generic gait model in opensim to go through the basic steps of modeling procedure in OpenSim. By doing so, I could make my model dynamically consistent to the experimental data. And then, I added actuators and metabolic cost probes to the model.
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Here are the figures of sample simulation models. I created several different types of models by modifying RRA-adjusted model for both loaded gait and unloaded gaitto compare them for their evaluation.
Loaded gait model
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The path actuator supporting plantar flexion is attached to heel and tibia, and the path actuator supporting hip extension is attached to backpack and femur. For Simplicity, Loaded mass was added to torso for simplicity.
Unloaded gait model
Same types of models were created for unloaded gait simulation. The main difference between loaded gait model and unloaded gait model is the mass of torso, and transparancy of backpack.
Optimization methodology
The idea to optimize the control input force for the actuators is to take advantage of CMC tool. The main reason we use CMC in OpenSim is to find a most suitable excitations for muscles to create body movement while minimizing activationmuscle activations. To see how it works, read
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- Now, if we diminish the influnece of Xactuator on J, and run CMC, the optimizer tries to find X_actuator in a manner of minimizing muscle activationactivations.
- We know that minimizing muscle activation correponds to minimizing metabolic cost, so we can come up with the conclusion conclude that the actuator input force resulted from CMC after diminishing if we diminish the influence of Xactuator is to objective function J is the optimal actuator input for most efficient metabolic cost reduction.
- Muscle force is constructed from the equation Factuator = Factuatormax * Xactuator. if we assign large value of maximum force to each actuator, actuator control Xactuator decreases, so that the influence of actuator to J is decreases.
- Using this methodologyidea, I could find an optimal input for each actuator, and also found the metabolic cost reduction after running CMC with a model where active actuators are added.
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I investigated how much metabolic cost is reduced when optimal input force is applied to a model by active actuators. I did simulation for both loaded and unloaded walking cases, and I compared the influence of hip actuator and ankle actuator to metabolic cost reduction. I assigned 10,000N to maximum active actuator force( Factuatormax) for this simulation.
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- Ankle actuator: 10.62%
- Hip actuator: 1.04%
- Things to notice
- The metabolic cost is much lower during unloaded walking than loaded walking. Loaded walking costs only 75% of metabolic energy compared to spent during loaded walking.
- Ankle actuator works better to reduce metabolic cost than hip actuator when we can apply optimal input force.
- Hip actuator is not assistive to unloaded gait.
Therefore, we can say that ankle actuator helps metabolic cost reduction better than hip actuator if we have an optimal actuator ideal actuators which has no maximum force limitation.
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- Actuation is started right after the toe-off of a foot on the opposite side, and the peak force occurs 7.12% of gait cycle before toe offhappens between the heal-strike of a foot on the opposite side and the toe off of a foot on the same side, and ends at the toe-off of a foot on the same side
- This Same actuation scheme strategy is valid for both loaded gait and unloaded gait
- The force signal is clear and easy to implement in real world
- However, the maximum actuation force is about 2500 N, which is too high to achieve in reality
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I could explain how the optimal actuation input for ankle actuator could help helps loaded gait by investigating the change of plantar flexor muscle forces
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- The gastrocnemius muscle forces are barely changed.
- Other plantarflexor muscle forces, including Soleus muscle forces, are significantly decreased.
- If we draw the sum of baseline uniarticular forces and active actuator input force together, we can see that the active actuator force follows the sum of baseline uniarticular muscle forces.
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- From the previous results, we found that the optimal input force for hip actuator is small enough to be achieved by real actuator, while the optimal input force for ankle actuator is not realistic. (>2000N). Therefore, I tried different types of input forces for ankle actuators up to 400N, and compare the results to optimal control input case.
- My initial guess was to saturate the optimal input force that I found earlier at 400N. I generated an new input force which is identical to optimal input force up to 400N, and saturated once optimal input force exceeds 400N. And then, I run CMC after setting the actuator input forces as a control constraints for each case.
- The second input force I tried is a new result from different CMC procedure. The new CMC result was acquired after assigning 4000N to maximum actuation force and bounding control input between 0 and 0.1.
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According to the formula Factuator = Factuatormax * Xactuator, the new CMC results also has maximum force of 400N. As Xactuator is bounded between 0 and 0.1 and Xmuscle has a range of is chosen between 0 and 1, the influence of Xactuator to objective function of CMC procedure is relatively lower than that of Xmuscle , so we can use this idea to create optimal input for active actuator when the maximum actuation force is limited.
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Now that we know both ankle actuator and hip actuator can reduce metabolic cost during loaded walking, the natural procedure is to test the actuators which can affect both ankle plantar flexor and hip extensor. In order to reduce the number of actuator, I added biarticular actuator actuators of 1 DOF affecting ankle plantar flexion and hip extension to each leglegs on both side, and see how much it reduces metabolic cost.
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The main idea to create biarticular actuator is to let the path actuator go through the axis of ankle joint rotation. I chose the attachment points of ankle actuator and hip actuator as the via points and end points of biarticular actuator line, and also set the origin of ankle joint rotation as one of the via points. By doing so, I create a biarticular actuator as a combination of which combines ankle actuator and hip actuator synchronized in series.
Simulation result
I run CMC on loaded gait model with biarticular actuator. I set the maximum force of biarticular actuator to be 10,000N, in order to see the optimal input force and best metabolic cost reduction.
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- Active actuators offer greater assist for loaded walking than unloaded walking when we can apply sufficient amount of force
- Optimal input of ankle actuator is consistent with gait cycle and muscle forces data, while that of hip actuator or biarticular actuator is not.
- The optimal input force for ankle actuator when it’s maximum force is bounded is similar to the general optimal input force saturated at maximum force
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You can find the model that I created for the project in SimTK website. You can reproduce the result using the model on the website. Please visit httpvisit https://www.simtk.org/home/~~~ exosuit.