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In order to develop an under-suit that doesn’t interrupt wearer’s free movement, researchers are trying to make it soft and deformable, but still capable of applying force to body joints. Among several different projects in the Warrior Web program, I focused on Harvard exosuitHarvard exosuit is the example of new approach to create under-suit in a soft and deformable manner.
- Harvard Biodesign group, one of a project groups in this program, is trying to make their warrior web suit soft and light, and they call their suit harvard exosuit.
- Experimental data proved that it can help loaded walking by reducing metabolic costs.
- This suit applies force to lower limb joints by a cable driven by the actuators on the backpack.
Challenge
As it is a new approach to assist human gait with deformable structure, there are many challenges while in developing the exosuit. The examples of the challenges are
- It is difficult to analyze the effectivness of exist.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 under-suit may be soft and deformable Hard to identify
- Exosuit is deformable
- We can not predicet how external actuation assists muscles during loaded gait.walking
- Experimental metabolic cost data is inconsistent case by case
Goals
Through this project, I tried to resolve the challenges in developing exosuit with Opensim simulationOpenSim. Simulation can help developing soft wearable exosuit as it can gives give an intuition on how exosuit help muscles, and what are the key features that one should take care about of when developing the suit.
I hope this project will construct a systematic way of analyzing and designing soft wearable device. The goal that I set as a starting point initial goals of this project are
- Evaluate the effectiveness of wearing active actuator on metabolic cost reduction during loaded walking.
- Explain how exosuit Exosuit can help loaded gait.
- Verify the impact of changes in of design parameters.
- Find optimal control inputs for exosuit actuators.
- Evaluate the effectiveness of Biarticular actuator
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- One gait cycle of loaded walking (From left toe off to next left toe off)
- One gait cycle of unloaded walking (From left toe off to next left toe off)
For both data, walking speed is identical, and mass The subject didn't wear a suit and walked freely. Also, walking speeds are identical in both cases. Mass of the load for loaded walking was 38kg.
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- mass: 61.3kg
- Sex: male
Modeling
To simulate an the movement of exosuit wearer, it is most important the first thing to do is to create a model which can replicate a real subject as possible as we can. In this project, as the experimental data was acquired from a subject walking freely, it is not possible to make a realistic exosuit wearer. However, to Before I created our model with active actuator 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, my model was gone through the basic steps of modeling procedure in Opensim, and then . And then, I added actuators and metabolic cost probes to the model.
How to model a subject wearing active actuator
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The diagram describes what procedure my the generic gait model had gone through.
- The first three steps are basic modeling procedure in Opensim to make a model dynamically and kinematically consistent to the experimental data. For more information, refer toread
- After RRA is done to the modelstep 3 is complete, probes for calculating metabolic cost were added to the model. . For more information about how to add the probes, refer toread
Simulation-Based Design to Reduce Metabolic Cost
- And thenFinally, I added active actuators to the model. Here, I used PathActuator class to simulate active actuators of exosuit, as they are cable driven actuator. If you are interested in how PathActuator works, refer toread
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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 gait.
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The path actuator supporting plantar flexion is attached to heel and tibia, and the pathactuator path actuator supporting hip extension is attached to backpack and femur. Loaded mass was added to torso for simplicity.
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The idea to optimize the control input force for the actuator 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 activation. To see how it works, refer toread
In this project, I make use of different use of the objective function optimization process in CMC in order to find optimal optimize the control input force for active actuators.
- CMC procedure contains is static optimization process, and it tries to minimize minimizes the cost function J which can be represented as
- When we add active actuators on OpenSim Model, the activation term in cost function becomes
Where X
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muscle is muscle control and X
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actuator is actuator control. As X
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actuator is part of activation
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states,
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it is also adjusted after the optimization process.
- Now, if we diminish the influnece of X_actuator on on J, and run CMC, the optimizer tries to find X_actuator in order to minimize a manner of minimizing muscle activation.
- We know that minimizing muscle activation correponds to minimizing metabolic cost, so we can we can say come up with the conclusion that the actuator input force resulted resulted from CMC after diminishing the influence of X_actuator is is the optimal actuator input for most efficient metabolic reduction.
- Muscle force is constructed by from the equation
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- Factuator = Factuatormax * Xactuator. if we assign large value of maximum force to each actuator,
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- actuator control
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- Xactuator
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- decreases, so that the influence of actuator to J is decreases.
- Using this methodology, I could find an optimal input for each actuator, and also see found the metabolic cost reduction after running CMC with a model where active actuators are added to a model.
Result & Discussion
Metabolic cost change when active actuators are added to model
I investigated how much metabolic cost is reduced when active actuators are added to a model, and optimal input force is applied to a model by 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 I assigned 10,000N to maximum active actuator force in order to find optimal control input force through CMC( Factuatormax) for this simulation.
| Loaded walking | Unloaded walking | ||||||||
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- Metabolic cost reduction when active actuators are added to loaded gait model
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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% metabolic energy compared to 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 which has no maximum force limitation.
Optimal actuator input force
| Loaded walking | Unloaded walking | |
|---|---|---|
| Ankle actuator |  |  |
| Hip actuator |  |  |
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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 off, and ends at the toe-off of a foot on the same side.
- This actuation scheme is valid for both loaded gait and unloaded gait.
- This 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
Optimal input force for Hip actuator
- Hip actuator can reduce the metabolic cost with lower maximum force than ankle actuator.
- However, it is hard to identify how the actuator assists walking.
- Also, it is difficult to implement the optimal control input for hip actuator in real world
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How ankle actuator assists loaded gait
I could explain how the optimal actuation input for ankle actuator could help loaded gait by investigating the change of plantar flexor muscle forces
- 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 baseline uniarticular muscle forces.
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According to the formula Factuator = Factuatormax * Xactuator, the new CMC results also has maximum force of 400N
, and it gives better result in terms of metabolic cost reduction than a result of CMC which was acquired with an actuator with 400N actuation and conventional control input.
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. As Xactuator is bounded between 0 and 0.1 and Xmuscle has a range of 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.
It we compare the saturated optimal input and the result from new type of CMC procedure, we can find a similarity between the saturated optimal input and a results of new CMC procedure. Now, let's compare the metabolic cost reduction when each control input is applied to ankle actuators.
Metabolic cost reduction
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- The result from new CMC procedure reduces metabolic cost more efficiently.
- However, the reduction is not significant, and it is much lower than the optimal case.
- The interesting thing is that the realistic actuation input force works better in unloaded walking case than loaded walking case. It makes sense because we requires lower force to assist unloaded walking than to assist loaded walking.
Biarticular actuator
Now that we know both ankle actuator hip actuator works well to can reduce metabolic cost during loaded walking, the natural progress procedure is to create biarticular actuator test the actuators which can affect both ankle plantar flexion flexor and hip extensionextensor. In order to reduce the number of actuator, I created added biarticular actuator with 1 DOFof 1 DOF affecting ankle plantar flexion and hip extension to each leg, and see how much it reduces metabolic cost, and what it’s optimal input force is.
Modeling
The main idea to create biarticular actuator is to let the path actuator go through the axis of ankle joint rotation.
Simulation result
| Optimal input | Metabolic cost reduction |
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