A Day of Testing: The Rundown

Apathetic and Absorbed Readers, 

As some of you may know from my last blogpost, I finally went to a day of testing. And when I say "a day of testing" I mean, quite literally, an entire day of data collection. The team originally planned to do both agility and metabolic testing this past Monday, but didn't even finish agility testing before the subject grew tired around 5pm. This is not to say we didn't have a successful venture, in fact, some graphs the team quickly developed indicated fantastic results. One of my favorite moments during testing was when I saw multiple members of the team really interact as a team--not just engineers, undergrads and biologists--but a group people giddy with results from hours of testing. In this post, I'm going to give you a rundown of how the five hours of testing played out, in detail. 

Around 12:30 PM, Anthony (one of my advisors) and I, went to find a place to set up for the T-Test. In case you don't remember, a T-Test is set up as a T that has a 10 meter stick and 10 meter dash. We ended up in a hallway just around the Bio room we typically work from. Here, we also set up a laptop that receives data from the BiOM through a Wi-Fi signal. This is important for data collection and programming--because, remember, the BiOM works by reading a code, like a computer. While Anthony and I set up the testing area and cleared dozens of vials from the hall space (because, obviously, a Bio building can't go without being littered by vials), one of the engineering students on the project, Eric, helped the subject get fitted with the BiOM. This subject has vacuum pump attachment for the device to link up (this is the same subject I referenced in an earlier post). Anyway, we started testing with the WFH rather than the stock BiOM program, which we tested later. Initially, even after walking around on the BiOM, the subject wasn't performing at his best. After 10 solid tests, but 16 recorded (we sometimes can't use a test when there's a glitch in the run, this happened 6 times) we had multiple data points to consider. We had time, laptop counted tests (16), our counted tests (10) and the number of steps taken by the subject for each path. Path A was walking forwards to the intersection of the T's dash and stick, Path B was the sidestep 5 meters to the left, Path C was sidestepping 10 meters to the right, Path D was sidestepping 5 meters to the left back to the intersection of the dash and stick, and finally, Path E was the backward walk to the end of the stick. So, forward, side, side, side, backward. My job (at first) was counting and recording the steps taken in each path. Now, this may not seem so difficult, but it is an incredibly tricky maneuver, trust me. After we finished the trials for the WFH, we did trials for the stock BiOM. Trials for the stock BiOM were performed in the exact same way they were for the WFH. Except, this time, we had less glitches. So, laptop count was 12 trials and our count was 10 trials--(two problematic runs). After completing BiOM stock trials, we noticed that the times were significantly shorter than with the WFH. This was problematic because we didn't know if the time difference was due to more practice with the prosthesis by the time we had tested the stock BiOM or because the WFH was just less effective. Luckily, there was a simple yet time consuming solution: Re-test the WFH. After another hour of testing, we finished recording new data for the WFH. During this time, I switched roles to controlling the laptop. This was a much simpler job but it was also super cool to see the code provided to the BiOM. Also, please remember it takes about 30 minutes to switch from WFH to stock BiOM. From the new data, we discovered that times were much closer than before--good news! Typically, our times were about 30 seconds per T, but it's nearly impossible to compare those times to any previously results from other studies because the T-Test is usually used with athletes sprinting. But, from some simple calculations we can create a bubble number to compare the 30 seconds to. By knowing that the average walking speed of someone is 3.1 miles/hour, we can convert that to 1.39 meters/second (our units). We can then do a simple proportion to find how many seconds it would take the average human to walk 20 meters, which turns out to be around 15 seconds. But, because there is side stepping and backwards walking, we must add some time to make up for the differences in gait. So, we can safely say the average time of an able bodied human performing to the T-Test is roughly 15-20 seconds. This is great news because it means that while using a prostheses, our subject's time values are hardly off. After data collection of the WFH, the stock BiOM and the WFH again, the subject grew weary, which we could see through trends in the data. So, we were unable to test the passive device in fear of having inaccurate data. But, my advisor, Anthony, created a graph that showed five different steps having nearly the same torques with the WFH. This is fantastic because it shows consistency and proves that the WFH is effective. Additionally, the graph shows proper negative/positive torques when the foot is moving or is in plantar flexion/dorsiflexion. This is all so exciting. 

Well, that was my first day of testing and I cannot wait for the many more to come!

Thank you for reading, 

Pooja 

Got Data?

Readers,

I have had such an eventful week. My project has been incredibly exciting for the past seven days and I am so glad to finally update you all. After this post, I will explain everything about my first day of testing and include some incredibly promising results. Get excited!

First, I realize I haven't yet explained what a step is. Simply, a step is from heel strike to heel strike. "What's heel strike?" you may wonder, allow me to explain. One entire step moves like this: from a start position of your feet next to each other, your left food moves forward, touching the heel to the ground (heel strike) before the entire foot lands flat, then your right foot mocks this movement, and finally the left foot moves forward once more, again completing heel strike. The movement from left foot heel strike to left foot heel strike is one entire step. 

To analyze data, the team interpolates the data. Interpolation means to "estimate the value of something given certain data." (vocabulary.com). So, for example, if you're given the amount of children buying chocolate ice cream on April 1st and April 20th, you must interpolate the amount of children buying chocolate ice cream on April 10th. In context of this study, an example of interpolation is when given the time to complete the first agility test and the time to complete third agility test, you interpolate the time for completion of the second agility test. Additionally, we compare our data to averages, which is a qualitative analysis. Except for the comparison to averages, this is all data analysis in terms of how the subject is able to move--whether the WFH/BiOM/ERS are able to compare to an able-body's gait. But, there are other ways to compare a prosthesis and human ankle-foot system. Specifically, agility and metabolism.

In addition to performing tests for backward walking, forward walking and varied terrain walking, we perform metabolic testing. In metabolic analysis, we consider the subject's breathing rate and oxygen consumption. For example, a subject finds that passive device is more exhausting to wear because there's no powered plantar flexion. Meaning the subject has to put in more work and energy in order to move the device, whereas with the BiOM requires less of the subject. Furthermore, when someone is missing a limb, there is consequently less oxygen consumption. This is obvious considering there's less mass overall. But, this also means there's more oxygen consumption when wearing a prosthetic device. It's impossible to create a massless device, so it needs to have its own power source (which the BiOM does from the battery) but it's also important to note that a device with too much power, would alter the subject's gait. Looking at breathing rates is a great indicator of a subject's energy efficiency, rather than just comparing numbers. Because, remember, this all comes down to how the subject feels in order maintain a high quality of life.

On Monday, I went to NAU for five hours testing one subject's agility with the WFH and the stock BiOM. Agility testing is the last type of testing we perform. Like I mentioned in a previous post, agility testing is crucial for determining a patent's quality of life. The analysis for this is already showing wonderful results but I'll wait to include those details until my next post.

Pooja :)

Testing Parameters

Enduring and Capricious Readers alike,

I've been holding off on explaining the testing parameters for my project until I felt like I'd provided enough background information. But, in case I'm missing anything, I'll try to supplement my information with... more information. If what I say is still unclear, please comment. I love responding to any comments, especially if it helps develop your understanding of my project. 

The forward walking parameters: The subject tested at four different speeds: a self-selected speed, a slow speed of 1m/s, an average speed of 1.25m/s and a fast speed of 1.5m/s. The self-selected speed was the same for both the Winding Filament Hypothesis (WFH) and for the stock BiOM, but different for the passive device. Each test had a 5-meter fly zone--a space where the subject can catch up to speed before data recordings occur at a certain rate. After the fly zone is the recording zone--a 20 meter distance for recording data at specific speeds. Additionally, we allowed for +/- .05% error. So, when walking at 1m/s, the error would be 21 seconds or 19 seconds for the 20 meter distance. Additionally, 50 trials were performed at each speed, and each trial is one step (remember one step is from heel strike to heel strike). So, 50 trials is equal to 50 steps, in other words, 200 steps total for each device at all speeds. This is quite impressive considering how efficient the group had to be. The stock BiOM registers a lot of the data we need to see if the device meets physical standards. For example, ankle torque, ankle angle, battery life and current from the motor. 

The backward walking parameters: There was a lot less testing done for backward walking because the end of the day was nearing, meaning there was a ton of wear on the subject (who, I should remind you, is not nearly as accustomed to the BiOM as he is the passive device for reasons I brought up in previous posts, but I will reiterate: no PT/OT with the BiOM and very little practice time with the device). With BW the self selected speed was typically the same, except with the BiOM where the self-selected speed was slower than with FW, and the slow, average and fast speeds were the same for all controls. The group performed tests over a 20 meter distance and have at least 20 BW steps. 

That was a lot of information that took me a long time to process and fully understand, so if you have any questions (which I totally expect), ask away! Next time, we will cover data analysis. 

Pooja 

Backward Walking

Lovely Readers,

So, it looks like I'll be finally working with subjects this Saturday and the following Monday. I can't express how excited I am to see the concepts I've been working in action. Today, I think we should cover a little more about backward walking and the implications surrounding it. 

First, we should talk about physical and occupational therapy. Physical therapy (PT) is "the treatment of a disease or an injury of the muscles or joints with massage, exercises, heat, etc" whereas occupational therapy (OT) is the "treatment that helps people who have physical or mental problems learn to do the activities of daily life". When someone suffers from the loss of a limb, they go through physical and occupational therapy to become accustomed to their new prosthetic limb. But, even with passive devices, backward walking isn't typically covered during treatment, so it's extremely unlikely that the BiOM would be covered either. 

This all links to a concept called Proprioception, which is "the ability to sense stimuli arising within the body regarding position, motion, and equilibrium." As you can imagine, this becomes much harder for someone who has no neurological connections to a part of their body--i.e. the prosthesis. Simply, these patients don't know where in space their foot is. Hopefully, when BiOM becomes more commercially available and affordable, they will include backward walking as part of both physical and occupational therapy, which will, by extent, help a patient's Proprioception. 

This is a hopeful and necessary goal especially in concerns related to testing. When a subject is more comfortable and aware of how the device moves, testing will be much more realistic. This is because a subject typically has countless hours with the prosthesis, but significantly less time with BiOM, they're simply more used to the prosthesis, making it easier and more adjustable to them. Thankfully, this hasn't had a large or noticeable effect on our tests. Problematically, before the device can be used in backward walking PT/OT, the device needs to have a solid and reliable history with backwards walking. Meaning, the device needs to be reliable before PT/OT but also usable enough to undergo more testing (I'm sorry that was so confusing. This is an unbelievably tricky medium researchers have to find). 

So, with that, let's talk about how the patients felt about the Winding Filament Hypothesis (WFH) (our algorithm, not the passive) and the BiOM in general. There is some good news. Some. The subject found the BiOM was consistently wrong, so he'd lose control, but consistently. Meaning, he could react appropriately because the BiOM would respond in the same way with every step, though responding incorrectly. Whereas the WFH was less consistent in its movements, so it sometimes reacted correctly and sometimes incorrectly, making it significantly less predictable. So, the subject had a harder time keeping up with it. 

*My definitions for physical therapy and occupational therapy came from Merriam-Webster and my definition for Proprioception came from MedicineNet.com. 

Thanks for reading!
Pooja