Challenging experiment, but we learned a lot in the process. Here are the top 4 lessons I took away....
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First, huge kudos to lead author @lamers_erik who completed his PhD last month!
During his time @CREATEatVandy he completed a series of studies on quasi-passive wearable assistive devices spanning from foot prostheses to back-assist exosuits
Super proud of the work he did!
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Next some background: When I talk to scientists they often want to know how much exosuits reduce muscle activity, or joint torque, or metabolic rate, or about the optimal assistance levels, specific design features, etc.
And I love this technical aspect of research, but...
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The last few years I've also been spending a lot more time talking with, observing, and getting to know non-scientific stakeholders -- in this case workplace safety officers, managers & workers who are potential exosuit end-users.
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They want to know about important practical issues: Will an exo be comfortable? Will it get in their way? Or help make them less tired at the end of their shift? Or help their back feel less fatigued and sore each day? How will it affect their life on and off the job?
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These experienced have steered & broadened my interest in wanting to monitor outcomes more relevant to end-users questions/concerns.
They motivated our study of exo comfort & our interest in assessing the effect of exosuits on back muscle fatigue.
Until a few years ago our lab had not conducted muscle fatigue studies before. So we had to learn... and it was unexpectedly difficult.
Huge credit to @lamers_erik and the rest of the @CREATEatVandy team for their perseverance & diligence in developing the test protocol.
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We spent nearly a year just learning about muscle fatigue test protocols & doing pilot testing. I don't think we touched an exo for first 6 months. Just focused on how to measure back fatigue reliably using surface EMG, and validating repeatability across people and muscles.
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But once we got all of these details worked out, the cool thing is that by monitoring the median frequency (MDF) of the EMG signals we could track the rate at which each back muscle was fatiguing during a physically strenuous task (bending forward & holding a heavy weight).
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So now let's the dive into the 4 key lessons I took away from this study:
LESSON #1 Modest torque assistance leads to fairly large reductions in back muscle fatigue.
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The exosuit prototype in this study applied 12-16 Nm of torque, which is probably only ~10-15% of the total torque about the lumbar spine during the task we tested.
However, on average, we observed reductions in back fatigue on the order of 29-47% (N=6).
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This reflects a non-linear relationship between muscle loading and fatigue, which is also evidenced in the scientific literature.
Interestingly, there is also a non-linear relationship between tissue loading and microdamage (which leads to overuse injury).
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What this suggests is that we don’t need to design exos that do all the work for the user. In fact we generally don’t want to do this. Rather we can develop exos that provide partial/modest assistance & these can lead to meaningful & tangible relief for overburdened workers.
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To put this in perspective: we found that wearing the exosuit made holding a 35-lb. weight (avg weight 4-year-old child) less tiring on the back than holding a 24-lb. weight (avg weight of an 18-month-old baby) without the exosuit
As parents know -- this a huge difference!
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LESSON #2
The lat muscles act kind of like an #exosuit for your low back muscles when they get tired. This was fascinating & unexpected, since the lats are primarily used to adduct/extend the shoulder. This behavior was something we stumbled upon during pilot testing.
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We found that when a participant’s low back muscles become over-strained and fatigued, they would occasionally summon extra assistance from their lats.
When they did, the activity in the primary low back extensor muscles would noticeably decrease.
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Elastic bands in our exosuit work in a similar way: they both apply forces across the entire thoracolumbar spine, they both have a mechanical advantage vs. underlying lumbar muscles, & when engaged they both relieve back strain & fatigue, which helps users sustain endurance.
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LESSON #3
Validate. Validate. Validate. I don't care if the method was from a prior publication. Validate that you can actually measure what you care about!!
One of the most interesting observations had nothing to do w/ the exosuit but with reliably measuring back fatigue.
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Before exo test, we did measurement validation in which we had each subject hold a 24 lb mass (less tiring) vs. a 35 lb mass (more tiring) for 90 sec. This enabled us to check for each subject that EMG frequency metrics were sensitive enough to observe differences in fatigue.
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Surprisingly, only half the participants tested during this measurement validation test showed changes in EMG median frequency between the two weight conditions.
Meaning for half the subjects we could not reliably/confidently monitor muscle fatigue using conventional metric
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If we had not done this critical validation step then we would have been trying to understand exosuit effects in a population in which we could not even reliably monitor the primary outcome metric for 50% of the subjects.
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Individuals that were validated (i.e., for whom we could confidently measure differences in back muscle fatigue rate via EMG when they held diff weights) then went on to test leaning & holding a 16 kg weight with vs. without the exosuit on a separate day.
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LESSON #4
Single-subject study design was better & more appropriate for this stage of device eval (in almost every conceivable way) than traditional group comparison (e.g. t-test).
Sadly, few studies in our field seem to use this kind of study -- but probably should IMO.
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Let’s be honest: In early-stage R&D on assistive devices there is a lot we don't know. We don’t know if all users are going to adapt the same way to a device. We don’t know exactly how much training time is enough. We don’t know the precise rest time needed between trials…
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We don’t know if device will fit everyone the same way -- they usually don’t they're prototypes. We don’t know if prototype is equally comfortable for all. We don’t know if users will adopt similar muscle patterns, e.g., with back where there are so many different muscles.
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Given all these unknowns in early stage device R&D, usually our first experiments aren't trying to establish broad generalizability across all users & scenarios.
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So to me -- often group comparison study designs seem misaligned with the actual (realistic) goals of this early stage research (e.g., to assess feasibility, or gain deeper understanding of how different individuals use a device, or range of effects observed).
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Single-subject study designs (e.g. A-B-A) often seem better suited for answering questions we have in early stage R&D given the numerous unknowns.
These allow individuals to serve as their own controls, & allow researchers hone in on effects of an intervention on each user.
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These involve testing a baseline condition, then introducing an intervention, then removing the intervention to ensure outcome metric returns back to baseline.
I’ve found these studies insightful & I've been more confident in my interpretations for early-stage device tests
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We were fortunate to use this ABA study design here b/c we found inter-subject variability in the number of muscles that benefited, which specific muscles benefited, & the degree to which each muscle benefited (percentage reduction in fatigue rate) from wearing the exosuit.
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For instance, subject 2 and subject 6 each benefited from the exosuit yet showed reductions in fatigue for a different (non-overlapping) subset of lumbar muscles.
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Diff people use exos in diff ways to relieve diff muscles. Just like any other tool.
We should keep this in mind in the development of industrial standards, & when trying to compare across different studies (which tested different users); until sample sizes are much larger
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I'll end by saying that I appreciate how this study pushed me/us to learn new methods, and really think deeply about applied/translational research -- to identify metrics that connected our #biomechanical science with outcomes that were of importance to end users.
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The interdisciplinary & translational parts of research & engineering, & continual learning are part of what I love about this job.
I was appreciative to have engineering as well as clinical collaborators involved -- shout out to @AaronYangMD & undergrads who contributed.
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I’ll note this muscle fatigue study was completed in 2018 & helped motivate us to found HeroWear.
You can follow @HeroWearExo to learn more about field tests & Apex #exosuit that came out from this research.
Excited to learn more from real workers using these #exosuits.
Nice article posted to the Associated Builders & Contractors of Wisconsin website & co-written by Prof. Zhenhua Zhu from UW-Madison & Mariya Sorenson, a construction manager with M.A. Mortenson.
They highlight 3 potential broad impacts of exos:
1. Improving worker safety & fostering a better safety culture in the construction industry.
Exoskeletons can reduce fatigue, muscle strain & wear-and-tear injuries, which could lead to substantial cost savings.
2. Alleviating the shortage of skilled construction workers.
Exoskeletons could help extend careers & attract candidates who might otherwise be deterred by physically demanding jobs.
🚀 5 years ago, I stumbled—somewhat unexpectedly—into the world of tech translation, commercialization & startups. It's been a wild & enriching adventure!
👨🏾🔬 As a scientist-turned-entrepreneur, this journey opened my eyes to the business world.
But...
😡 Amidst all the positive learning & growth, there's one thing that truly gets under my skin: misleading marketing & unsubstantiated claims.
😬 Brace yourself: The wearable & assistive tech industry (think #exoskeletons, #prosthetics, sensors) is still plagued by this problem! Whether it's in clinical, occupational, sport, or recreational applications, we need to address it head-on.
I used to source all of mine from academic literature & conferences, or from my own research.
But these can become echo chambers that limit thinking & creativity.
🔥 Here are 4 overlooked places to find impactful research problems:
1️⃣ Your own life
• This is why I started studying low back #biomechanics
• I was a parent to young kids & experiencing back pain
• I was curious if we could create more practical exoskeletons that'd fit into my own life
It started as an undergrad project then grew into more:
2️⃣ Spending time w/ users
• In academia we often talk about this
• But we tend to involve users too late in R&D
• And I'm not convinced we spend enough time doing it
Hearing pain points directly from #prosthetics users is what prompted the daily activities we now study:
Science is the foundation, but user feedback is the north star:
• to know what to prioritize
• to learn where to improve
• to remember why you sweat all the science details
This is a vital lesson for those doing applied research whose feedback is mostly from other scientists
The combination of #biomechanics science and user-centric design is beginning to have the real-world impact the occupational #exoskeleton field long hypothesized it would.
End-users explain this best:
“When you show you care about people, that retains people,” one warehouse worker who piloted a back exosuit said. “Everybody in here, we’re all sore. We’re all hurting. But for the first time in a long time I won’t be hurting walking out of this building [because of the exosuit]”
Early career researchers often stress out when they talk to more senior faculty about how many grant proposals they submit.
Don't compare. Focus on your writing process. Outcomes will follow.
Here are 5 proven tricks senior faculty use to submit more high-quality proposals:🧵
1. Resubmitting
• Revise/resubmit an unfunded proposal
• This takes much less time than writing a new application
This is easier to do (and comes naturally) as you get further into your career.
2. Repurposing
• Take a similar core idea and apply it to a new population or context
• Or you can sometimes submit the same proposal to multiple agencies (check w/ program officers first; you just can't accept two grants for the same work)