June 22, 2025 • 28 mins
America has a problem! Beyoncé called it, and the data backs her up: more than 36 million older adults fall each year, often ending up in hospitals or nursing homes. MIT mechanical-engineering PhD student Roberto Bolli joins Dope Labs to unveil E-BAR, a compact robot that glides behind you, senses a stumble, then inflates airbags in just 250 milliseconds and lifts you with padded U-shaped arms. Titi and Zakiya dig into everything from real-world interviews to load-bearing math. They show how tech like E-BAR can help seniors age in place while complementing human caregivers.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
One of my greatest fears is doing something ridiculous in
my house late at night, because you know how I
like to shuffle around and I hurt myself and no
one hears me call for help. You know, No, that
is scary, right it is. But what if instead of
laying on the ground needing life alert, there was a
robot that could catch me before I even feel I
(00:22):
love that idea.
Speaker 2 (00:23):
So today we're gonna be talking elder care engineering and
the soft, squishy future of robotic support. I'm TT and
I'm Zakiah and this is Dope Labs. Welcome to Dope Labs,
a weekly podcast that mixes hardcore science with pop culture
and a healthy dose of friendship. In today's lab, we're
(00:50):
talking about aging in America and the technology that could
help us stay safer for longer. Our guest is Roberto Bowley,
a mechanical engineering PhDc student MIT who's designing a robot
that can literally catch you when you fall. It's called Ebar.
But before we meet the robot, let's set the stage.
Speaker 1 (01:10):
What do we know? So between twenty ten and twenty twenty,
the US Census told us that the over sixty five
population saw the largest and fastest growth spurt that has
seen since to like late eighteen hundreds, and according to
the Urban Institute, by twenty forty, we're expecting one in
five Americans to be over sixty five. And what do
(01:31):
we want to know?
Speaker 2 (01:33):
Well, I want to know what kind of tech could
actually help? Like, how do you build a robot that
doesn't feel scary, you know, not like the ones that
from I robot that are going to turn on you?
Speaker 1 (01:44):
And yeah, what were they thinking? Or that's too invasive?
You know what I mean?
Speaker 2 (01:49):
Yeah, what does it take to go from a great
idea to a real life idea that's manifesting in front
of you, that is safety certified and in someone's living room.
Speaker 1 (02:01):
I think we're ready to jump right into the dissection.
Speaker 3 (02:08):
My name is Roberto Bolly. I'm a graduate student at
MIT studying mechanical engineering.
Speaker 1 (02:14):
Where do you think some of our biggest disconnects are
between people's hopes for what that kind of aging looks
like and what our current caregiving support infrastructure delivers today.
Speaker 3 (02:24):
So we actually we did a lot of interviews with
elderly people where do they need support? What kind of
support are they looking for? And we found like virtually
everybody we interviewed once to Asian place at home, Like
that's like, I feel like the goal. It's like, you
get older, you live at home, you have hobbies like
gardening or moving around the home, and you know, you
just gracefully age in place. The reality is that something
(02:49):
like thirty or forty percent of elderly people fall each year.
Oh and oftentimes when they fall it's like a debilitating injury. Like,
if you're young, you fall, it's not to make a deal.
You might get a bruise or something. But if you're
old and you fall, you can sometimes break a hip.
And so unfortunately, what we see is a lot of
people get shuttled into nursing care or long term care,
(03:11):
and they often don't like it. They want to go
back to their homes. Sometimes they get suboptimal care because
there's also a big shortage of caregivers.
Speaker 2 (03:19):
Can you clarify what age is elderly?
Speaker 1 (03:24):
Ah?
Speaker 3 (03:25):
I think in our lab we've been looking at people
over sixty five, but there's no really good definition. Because
I met someone who is seventy five and who bikes
like eight miles a day is in probably better shape
than me, but more than like an age we're looking
at like a subgroup. So we say people who have
like medium muscle strength, so they're able to hold onto
(03:47):
handlebars or do activities of daily living, but they may
lose their balance or they have a tendency to fall,
and sometimes for hard transfers like getting out of a bathtub,
they require assistance, like they need to grab onto a
handlebar or something.
Speaker 1 (04:00):
When we consider the increasing demand for care of an
aging population, you and your team are proposing robotics as
a solution or at least an enhancement. And from what
you've said, people want robotics, which I'm surprised by. I
think I would have intuitively thought that older people would
be anti robotic.
Speaker 2 (04:18):
I would have thought that too, But then I mean,
here comes Ebar, this really amazing invention of yours that's
meant to help older people in the ways that they
want to be helped.
Speaker 3 (04:29):
Yeah, for sure. So Ebar came about because we're looking
around through the literature and through what devices are available,
and we found that for robots that actually catch a fall,
pretty much all of them you have to wear a
harness or like some sort of wearable device. But like
elderly people hate to do that. The feedback we got
was that it makes them feel old and it's sometimes cumbersome. Yeah. Yeah,
(04:53):
So we're trying to develop a robot that can catch
a fall without any like having to wear any sort
of device. And then another thing we found is that
a lot of elder care robut it's only a few
that have looked at physical assistance. But typically you have
to stand within what's called the base of support of
the robot. So if you imagine all the points of
the robot that touch the floor, if you like connect
(05:14):
them with lines, as long as you stand within that area,
the robot will never tip because you're within the base
of support. But if you're outside, for some robots, they
can tip over. So we're trying to design a robot
that stable even if you're outside of that base of support,
because then it can go like over bathtuble lips, it
can go like onto a bed, it can go over
like gaps and obstacles. So we put these two together
(05:37):
and we developed what my professor calls like a mobile
forklift or robotic candlebars.
Speaker 2 (05:44):
I think that that is so fascinating and such a
leap forward in the technology for the folks that you
know they're going to be listening. They can't see us.
Hopefully they'll do their googles to be able to see ebar.
Can you just describe what ebar looks like from top
to box so that somebody can visualize it in their mind.
Speaker 3 (06:03):
Sure, yeah, I'll try to do my best. It's this
robot that can drive around. It can catch people with
airbags when they fall. It can like physically lift them
up with this sort of U shaped fork at the front,
and then it has handlebars for them to grab onto.
It's kind of just this big U that's padded with
handlebars on the front and on the back. That's the
part of the robot that you grab onto. You can
(06:24):
rest your forearms on it, or you can just grab
onto the handlebars on the side. And it has the
airbags underneath which can grab onto your waist. So that
U shaped fork is attached to a big linkage, and
then that whole thing is attached to an omnidirectional drive base.
And so the drive base, you know, like if you're
trying to parallel parker car, you can't just like slide
into a spot. You kind of have to move back
(06:45):
and forth.
Speaker 2 (06:46):
Right, Oh, Yeah.
Speaker 3 (06:50):
So this robot has four wheels. Each wheel can independently
rotate and translate, and so you can actually just go
and then move sideways instantly, so it can move in
any direction.
Speaker 1 (06:59):
That's great, That is amazing.
Speaker 3 (07:01):
I didn't put this in the paper, but I believe
it's probably the world's fastest elder care robot. So we
limit the power for safety, but it has a max
speed of around twelve feet per second. It's very powerful,
it's moved.
Speaker 2 (07:17):
I need one of those for my home.
Speaker 3 (07:20):
We limit it to like one to two feet per second.
You know, they don't want to cause any injuries.
Speaker 1 (07:25):
Yeah. I think that's a great description of the design
of how ebar looks. And I watched some of the
footage that you all share it's on YouTube, and it
looked like you had I don't know if it was
PlayStation or Xbox style, like a joystick on there, a controller.
Was that part of early testing? You know, what kind
of control system does e bar have?
Speaker 3 (07:47):
Yeah? So right now, in the original paper, it's just
manually controlled with a joystick, like similar to what you
see with mobility scooters, where there's a joystick and people
just sort of move it around. Currently, right now in
the lab, we're working on automating some of the functionality.
So we have a project where we're trying to use
the drive base to track a person automatically so it
can follow them around. And so you know, it's a
(08:11):
lot of work to do that sort of automation, so
we kind of just went for manual control first, but
we're definitely looking into it.
Speaker 1 (08:17):
That's really cool.
Speaker 2 (08:18):
My background is also engineering, and so I also have
a degree in mechanical engineering, and so I know that
part of this is about footprint, because if you're thinking
about the function of this robotis to help folks with
getting around and to keep them safe, we know that
it has to be able to take up as least
(08:38):
amount of space as possible. Can you talk about the
role that the robots footprint played in your design and
how did you make sure that it could navigate in
tight spaces inside of a home without tipping over or
interfering with other things in the house or the user.
Speaker 3 (08:56):
Yeah, for sure, for sure. So our goal was to
make the robe but as small as possible. The problem
is that you know, if it were just like six
inches wide, it would tip over immediately. So what we
did is. We set up a sort of an optimization problem,
and from a high level we said, okay, like how
(09:18):
small can we make the drive base and how heavy
can we make it so that it doesn't fall through
the floor. Because you know, if you think about a person,
a person occupies about one square foot of space if
they're standing up straight. He said, okay, you know the
average person. A floor can support a person that weighs
maybe two hundred three hundred pounds, no problem, So we'll
try to limit the robot weight to that. Then we
(09:39):
looked at like what are the maximum forces people can
apply laterally and horizontally. So it turns out the US
military has done a lot of studies like this in
the eighties and they found that, like I think it's
like one hundred and twenty Newton's horizontal force, they have
like force from any orientation. So we can quantify this
really well, like when you're standing up, how much can
you push on the robot?
Speaker 1 (10:00):
Right?
Speaker 3 (10:00):
So we put all that together and we have a
cost function. With the cost function says, okay, how can
I shrink the robot as much as possible while still
satisfying the load bearing constraints? And so putting those all together,
the actual wheels of the drive base occupy around a
ten inch square and then we have two sort of
outriggers like almost antennae, so we can get a little
(10:22):
bit more stability. And so the footprint of the robot,
I think it's around the base itself is around fifteen
inches by fifteen inches, not including the outriggers. Wow, with
the outriggers, it's a little bit bigger. I think they're
around twenty inches wide. But your average doorways are somewhere
between twenty eight to thirty six inches, so we still
got plenty of space around the door.
Speaker 1 (10:43):
That's amazing.
Speaker 2 (10:44):
And you know, I know that this is designed for
elderly folks that need help around the house, but I
can already imagine this helping a lot of people who
are differently abled from the disabled community. And did you
consider that as you were designing? Is that something that
also came into your mind as another use for ebar?
Speaker 3 (11:04):
Sort of, So we did think about using it for
Parkinson's patients because they sometimes just have a struggle maintaining
their balance, But I think absolutely it could be applied
towards different populations all be honest, we specifically designed it
for elderly persons, but I think you know, there are
certainly other people who could benefit from the robot.
Speaker 1 (11:24):
Absolutely. I think that's such a good point that TT's
talked about before in engineering and design. We've talked about
it in just inclusivity across the board in anything that
you create. You know, the more you think about who
this can help, the more people benefit from it, even
people you didn't consider. I want to know about how
you're these different types of assistance that ebar provides, because
(11:47):
it's not just that you have to fall in. Because
of the shape of it and because of how you
designed it, it seems like it can do more than
just like wait until you're at the ground and needing
to be lifted, right, like ebar can come in ahead
of time. Yeah, I'd love to hear you talk a
little bit more about the different falls you anticipate it,
or the different types of knees you anticipated, and how
you build all those things together into this system.
Speaker 3 (12:10):
Yeah. For sure. Our goal was to catch a person
before they fell, because when they're on the ground, oftentimes
they may be unconscious, they may have passed out, and
it's kind of a bad situation to be and if
the person's already on the ground, right, So you're thinking
of how to do it, and we came up with
the idea of using airbags because they're soft, you can
have like a large contact area. And the question is,
(12:34):
like is it physically possible. So a previous student in
my lab has worked on like fall prediction and she
found that you can predict a fall up to two
hundred fifty milliseconds before the person actually starts to fall down. Wow,
And that's why using like a waste mounted sensor called
an im you. So we said, okay, two fifty milliseconds,
(12:55):
that's our target inflation time. Can we like fully inflate
the airbags and catch a person right before they so then, yeah,
we tried different shapes and sizes and configurations of airbags.
I tested a lot on myself, you see, like how
how much can I inflate them before it becomes painful?
And then we looked at studies of like skin bruising
because you know, we know that elderly people's skin are
(13:16):
kind of sensitive, so we didn't want to cause them
any danger or put them in risk of bruising their skin.
And we settled with a configuration of four airbacks. There's
two big ones on the side and then two smaller
ones on the front like columns, so when they inflate,
they sort of push the person back into the robot.
And then we developed a rapid like two stage inflation
(13:37):
system that can inflate them within two hundred and fifty milliseconds,
so if you're walking, you know, right now. Again, it's
all done manually, but we have done work in our
lab about like detecting falls, just haven't implemented it on
the robot yet. The idea is, if you begin to fall,
the airbags which just rapidly inflate and gravy and sort
of hold on to you, and so you're kind of
frozen in this position, but you have a chance to
(13:58):
regain your balance, or we can deflate the airbags and
you can continue normally, or we can just hold you,
you know, until someone can come to help.
Speaker 2 (14:20):
And so the next part of the engineering is to
you know, test it out on the users. I'm wondering,
you know, one, I think it'll be interesting to hear
like how you get volunteers for this or who you
recruit to test these things out, and then also what
their feedback was and how that informs like how you
move forward and any changes that you might make.
Speaker 3 (14:42):
The major thing we have to make sure before we
can roll actual elderly persons that it's completely safe because
we don't want to cause anyone any injury. So right
now we've been testing in healthy volunteers. By healthy volunteers,
I mean myself and a couple of my web mates. Okay,
but yeah, the idea is to refine the system to
(15:02):
make sure it's safe, to you know, sort of measure
the forces which we have been and so far everything's good.
Then we can apply for approval from our university and
then start enrolding elderly persons.
Speaker 1 (15:12):
Okay, this sounds really cool because you've called EBAR a
step towards aging in place. And I am thinking back
to those commercials where people were like life alert and
they were waiting until they already fail. And like you said,
after you've once you hit the ground, anything could happen.
You could be unconscious. But like I think about what
(15:33):
this could mean. Something you mentioned is how maybe stressed
our healthcare system is for aging adults. Yes, we're talking
about this in the home, but could you imagine this
type of tech in other places like care facilities or
as part of public programs. How do you imagine this tech?
You know, I know we're looking much further ahead, but
how do you imagine it scaling?
Speaker 3 (15:54):
I think for me personally, i'd say, like, I think
the gold standard is a human being. It's very difficult
for robot to replace a human, right. I think We've
seen this again and again. But the reality is that
if there is a care shortage, I think it's better
to like augment the shortage with robots than just to
not be able to do anything about it. So one
(16:14):
thing we were thinking is like in nursing homes, ebar
could sort of handle some of the easier tasks. If
a person just needs to walk, for example, to a sink,
then ebar could help them out. But very complex tasks
like lifting a person into a bathtub with a sling
like those can still be done by the caretakers, so
it can sort of free them up. That instead of
elderly persons having to wait a long time for care
(16:36):
that if for some tasks we could send the robot
and for some tasks we could send a human caretaker.
Speaker 2 (16:43):
I love that because Menzakia talk about this all the
time where a lot of solutions to the world's problems
is not an or response like this or that. It's
an and so not to say, oh, Ebar is going
to replace all caregivers, there won't be a need for
a human. It's like, no, you can have the human
(17:03):
and you can have e bar, which to supplement and
it makes it an even better experience. I'm curious about,
you know, what are the next steps with ebar. Are
there any like upgrades or advancements that you want to
add to EBAR, or what's the vision or are there
things that you want to do outside of e bar
(17:25):
to also help supplement EBAR.
Speaker 3 (17:28):
Yeah, that's a great question. Honestly, it's discussion my advisor
had with me almost immediately after I submitted the paper. Yeah.
I think certainly there's room for making the robots smaller
and more compact. I've talked with a lot of people,
even my parents are saying like, hey, you should add
something that can pick up a person's phone if it
(17:49):
falls down, like a sort of a coup holder on
the robot. I said, well, that's great. I'd love to
do that, but I don't know if I can really
put that in my thesis work. So one of the
other things our lab is looked into is handlebar optimization.
Like if you think about it, when you go into
restrooms or some public places, you see handlebars on the walls.
(18:12):
It turns out there's not really been a lot of
work that's been done on like is this the biomechanically
optimal location for handlebar? And because like you know, who knows,
it could be in front of you, it could be
like up here, it could be like down there. So
we were trying to look into, like can we make
a model of a person and then predict like where
is the optimal place for handlebar it maybe reduces the
(18:35):
muscle strength the most or provides the most support. So
that sort of stuff I think is interesting and I
think could compliment a robot like e bar because then
it helps us nowhere to position the U shaped fork
based on the posture of the person. So yeah, that's
I guess that sort of work that we've been looking
to and thinking about pursuing in the future.
Speaker 1 (18:52):
Okay, I think this is so cool.
Speaker 3 (18:55):
Things.
Speaker 1 (18:56):
You know, this is totally outside my comfort zone of science.
TT understands this kind of stuff way better than me,
which is why she has such great questions, is there
anything else here seeing in the field of robotics and
elder care? Is there anything else you're excited about this
in the research pipeline, even if it's not in your lab,
like with other labs that do great work that you see, Ye,
(19:18):
that feels promising.
Speaker 3 (19:20):
So we are collaborating with So just full disclosure. But
at Stanford, Alison O Kumurro, she did a lot of
work on these things called vine robots. They're sort of
like flexible tubes. They can inflate and they can go
under a person. And so we have this idea. It's like,
wait a second, you have an elderly person lying in
(19:40):
bed and you want to like put them in a sling,
Like right now, you've got to lift them up and
pull a slip. What if the sling just like inflated
under them, like and then you could just pick them
up that way. So that work I think we've been
doing with her. But she was the one who's been
working on vine robots. I think that's really cool. In
terms of other labs and other research, we see a
(20:03):
lot of work with humanoids. Humanoid robot seems to be
like the next big thing. There's a bunch of companies
pursuing humanoids, and so people have started looking into like
using a humanoid for sit to stand assistance, which I
think is pretty cool. My concern with it is just,
especially if the robot has two feet, it's not going
to be a stable as something that has like a heavy,
(20:23):
big drive base. You know, like if the robot and
the person fall down, then that's really bad. But I
think it's great work though. I think that that should
be explored. And I saw a couple of papers when
I was at akra Acra is a big robotics conference
that happens each year. It's sort of like v big
robotics conference, and so I saw a couple of papers
(20:43):
where people are looking at using humanoids to like provide
sit to stand assistance, and I thought that was really cool.
Speaker 2 (20:48):
Yeah, I was thinking about this the other day because
I've also been noticing a lot of the humanoid innovation
and how it's like, you know, as engineers, we try
and create things that are not just flashy but useful,
and it doesn't really seem intuitive to me to say,
(21:11):
this human is not able to form this task, so
I'm going to replace it with another human but I
think people are just so enamored by humanoids.
Speaker 1 (21:20):
I'm not. As a non engineering person, I feel like,
give me the e bar. If I knew I was
falling back into a face, I don't think I would
like this, you know, And so I think it's interesting,
Like I feel like that humanoid component is what makes
people feel like, oh, you're trying to replace me, or
oh that's my own bias that I think. If it's
(21:42):
hard already for a person to help you, why would
I put it in something else that's person shaped to
do the same work so it can be just as
hard for it.
Speaker 2 (21:49):
Yeah, make that inflatable sling, Like, I love that idea.
Speaker 1 (21:55):
I think it's great.
Speaker 2 (22:09):
My last question is just about the process, because we
just did an episode on the research funding cuts and
stuff like that. I really would love for you to
highlight like what it takes one to get to this
point with EBAR and then to have EBAR kind of
like break into the healthcare system, if you know, because
I think that one thing that the Kia said is
(22:31):
that folks they don't think about research in the way
that they should. They think about innovation. So when the
product is there and in their hand, they're like, ah, research,
and it's like, no, that's innovation. There's a lot of
research that gets you to that point. So can you
talk about that process for yourself. I think it would
be great for people to here to understand what it
takes to do something like this.
Speaker 3 (22:52):
I took product design. It was a class at MIT
a couple of years ago. They presented us with this process.
I think it's just called like a need driven develop
and process. But the idea is you start first with
the stakeholders. You go to the elderly person, you ask
them like what sort of tasks are you trying to do?
And then oftentimes what you find is people will tell
you things, but really there's like underlying needs they're called
(23:16):
latent needs that they're not really telling you. They can't
really put into words well, but it becomes obvious as
you look into more of the of what they're doing. Like,
for example, an elderly person might say like, oh, you know,
I really have trouble getting into and out of the bathtub,
but I want is just like like a cane or
something that'll help me get in and out. And you're like, well,
(23:39):
maybe the problem is that the tub is too high.
Maybe it's the problem that, like, you just need a
little bit of support, and so it may not be
a cane that you want. It may be like a
robot or a handlebar or some other device that can
also help you. So we start with this stakeholders and
looking at the latent needs and then in our case,
we develop this sign concept for robot and we went
(24:02):
to a physical therapist that's Spaulding Rehabilitatian Hospital. We did
a presentation and they said, oh, we like these aspects
of it, but we think these aspects wouldn't work with
the patients that we work with. So then we sort
of go back and forth a couple of times, rEFInd
the design, and then from there on it's the most
fun part for me. I get to build a prototype.
Speaker 1 (24:21):
I think that's interesting because that's such a long process
and the only research you're highlighting is the new research
that you're doing. But you've already told us that even
in your prototype, to determine how much force a person
might use, you're going back to research from forty years
ago to the nineteen eighties, right, and so research that
some people may say, why does the army need to
(24:43):
do this, or why does the military need to figure
out how much force a person exerts laterally, because in
forty years, a graduate student is going to be figuring
out how to design a robot that can keep your
grandmother from falling when she reaches for something. And I
just think those are the connections between research and innovation
that we don't highlight enough. You're relying on research that
(25:06):
has already been done to help you iterate and innovate
really quickly to decide what the drive based size should be.
And I think it's just such a good demonstration of
research and innovation how closely those two rely on each other.
Speaker 3 (25:22):
For sure, for sure, And there are so many times when, like, like,
one of the critical things that we've needed was you
needed to know the friction between a person's skin and
their clothes. There's a sony in twenty thirteen that characterizes
so thank you so much. You know, it's such an
obscure piece of knowledge. You think, like, when would you
ever need that? But it turns out we need to know, like, well,
the closes slip on the skin if we can press
(25:43):
them with airbags. So this random research study ended up
being extremely useful because we can quantify now the friction.
So yeah, there's a ton of these connections between prior research,
some of it not even remotely related to elder care.
But you know, it's like we're standing on the show
of giants. Yes, all this knowledge gets built up, and
(26:03):
you may not think it's useful in the moment, but
then twenty years down the road someone needs it. It's
like the exact thing that they need exactly.
Speaker 2 (26:10):
And that's another thing that we always say is that
science never stops. And that is a really good illustration
of that, where you know, just because that part of
research ended or that paper was published, doesn't mean that
it'll never be used again. It doesn't mean that it
won't be useful. It doesn't mean that you can't build
(26:32):
off of that. And so like science never never stops,
someone will be citing your paper one hundred years from now,
I'm sure and saying, wow, look what we were able
to do based on what Roberto and his lab group
were able to do, and now we can innovate off
of that. The science never stops, and the work that
we do is really important, even if it feels obscure.
(26:54):
Sometimes I think about my graduate, my dissertation work, and
I'm like, oh, oh god, no one needs this. It
was in nano materials. And then I'll go and look
at some of my old papers. I'm like, wow, cited
eighty times. Okay, that's not bad, that's excellent.
Speaker 3 (27:12):
Yeah. No, it's cool to see you. Everything fits together,
and honestly, I think we're going to see more and
more on that.
Speaker 2 (27:19):
Congratulations on all of your success. We will be tapping
into mix to see how Ebar is evolving and your
success as your career continues to grow and change. You're
doing a great job and doing a lot of really
important work. So congratulations, Well, thank you so much.
Speaker 3 (27:36):
I'm honestly, I'm just so grateful to have the opportunity,
you know, to be a graduate student and to study
all of this. I'm you know, I'm always very grateful
for that.
Speaker 1 (27:45):
So amazing.
Speaker 3 (27:46):
Thank you, guys. I appreciate it.
Speaker 2 (27:55):
You can find us on X and Instagram at Dope
Labs podcast.
Speaker 1 (28:00):
He is on X and Instagram at d R Underscore
t Sho.
Speaker 2 (28:03):
And you can find Zakiya at z said So.
Speaker 1 (28:06):
Dope Labs is a production of Lamanada Media.
Speaker 2 (28:09):
Our senior supervising producer is Kristin Lapour. And Our Associate
producer is Issara Savez.
Speaker 1 (28:16):
Dope Labs is sound design, edited and mixed by James Barber.
Lamanada Media's Vice President of Partnerships and Production is Jackie Danziger.
Executive producer from iHeart Podcast is Katrina Norvil. Marketing lead
is Alison Kanter.
Speaker 2 (28:31):
Original music composed and produced by Taka Yasuzawa and Alex
sugi Ura, with additional music by Elijah Harvey. Dope Labs
is executive produced by us T T Show Dia and
Kia Wattley.
One of my greatest fears is doing something ridiculous in
my house late at night, because you know how I
like to shuffle around and I hurt myself and no
one hears me call for help. You know, No, that
is scary, right it is. But what if instead of
laying on the ground needing life alert, there was a
robot that could catch me before I even feel I
(00:22):
love that idea.
Speaker 2 (00:23):
So today we're gonna be talking elder care engineering and
the soft, squishy future of robotic support. I'm TT and
I'm Zakiah and this is Dope Labs. Welcome to Dope Labs,
a weekly podcast that mixes hardcore science with pop culture
and a healthy dose of friendship. In today's lab, we're
(00:50):
talking about aging in America and the technology that could
help us stay safer for longer. Our guest is Roberto Bowley,
a mechanical engineering PhDc student MIT who's designing a robot
that can literally catch you when you fall. It's called Ebar.
But before we meet the robot, let's set the stage.
Speaker 1 (01:10):
What do we know? So between twenty ten and twenty twenty,
the US Census told us that the over sixty five
population saw the largest and fastest growth spurt that has
seen since to like late eighteen hundreds, and according to
the Urban Institute, by twenty forty, we're expecting one in
five Americans to be over sixty five. And what do
(01:31):
we want to know?
Speaker 2 (01:33):
Well, I want to know what kind of tech could
actually help? Like, how do you build a robot that
doesn't feel scary, you know, not like the ones that
from I robot that are going to turn on you?
Speaker 1 (01:44):
And yeah, what were they thinking? Or that's too invasive?
You know what I mean?
Speaker 2 (01:49):
Yeah, what does it take to go from a great
idea to a real life idea that's manifesting in front
of you, that is safety certified and in someone's living room.
Speaker 1 (02:01):
I think we're ready to jump right into the dissection.
Speaker 3 (02:08):
My name is Roberto Bolly. I'm a graduate student at
MIT studying mechanical engineering.
Speaker 1 (02:14):
Where do you think some of our biggest disconnects are
between people's hopes for what that kind of aging looks
like and what our current caregiving support infrastructure delivers today.
Speaker 3 (02:24):
So we actually we did a lot of interviews with
elderly people where do they need support? What kind of
support are they looking for? And we found like virtually
everybody we interviewed once to Asian place at home, Like
that's like, I feel like the goal. It's like, you
get older, you live at home, you have hobbies like
gardening or moving around the home, and you know, you
just gracefully age in place. The reality is that something
(02:49):
like thirty or forty percent of elderly people fall each year.
Oh and oftentimes when they fall it's like a debilitating injury. Like,
if you're young, you fall, it's not to make a deal.
You might get a bruise or something. But if you're
old and you fall, you can sometimes break a hip.
And so unfortunately, what we see is a lot of
people get shuttled into nursing care or long term care,
(03:11):
and they often don't like it. They want to go
back to their homes. Sometimes they get suboptimal care because
there's also a big shortage of caregivers.
Speaker 2 (03:19):
Can you clarify what age is elderly?
Speaker 1 (03:24):
Ah?
Speaker 3 (03:25):
I think in our lab we've been looking at people
over sixty five, but there's no really good definition. Because
I met someone who is seventy five and who bikes
like eight miles a day is in probably better shape
than me, but more than like an age we're looking
at like a subgroup. So we say people who have
like medium muscle strength, so they're able to hold onto
(03:47):
handlebars or do activities of daily living, but they may
lose their balance or they have a tendency to fall,
and sometimes for hard transfers like getting out of a bathtub,
they require assistance, like they need to grab onto a
handlebar or something.
Speaker 1 (04:00):
When we consider the increasing demand for care of an
aging population, you and your team are proposing robotics as
a solution or at least an enhancement. And from what
you've said, people want robotics, which I'm surprised by. I
think I would have intuitively thought that older people would
be anti robotic.
Speaker 2 (04:18):
I would have thought that too, But then I mean,
here comes Ebar, this really amazing invention of yours that's
meant to help older people in the ways that they
want to be helped.
Speaker 3 (04:29):
Yeah, for sure. So Ebar came about because we're looking
around through the literature and through what devices are available,
and we found that for robots that actually catch a fall,
pretty much all of them you have to wear a
harness or like some sort of wearable device. But like
elderly people hate to do that. The feedback we got
was that it makes them feel old and it's sometimes cumbersome. Yeah. Yeah,
(04:53):
So we're trying to develop a robot that can catch
a fall without any like having to wear any sort
of device. And then another thing we found is that
a lot of elder care robut it's only a few
that have looked at physical assistance. But typically you have
to stand within what's called the base of support of
the robot. So if you imagine all the points of
the robot that touch the floor, if you like connect
(05:14):
them with lines, as long as you stand within that area,
the robot will never tip because you're within the base
of support. But if you're outside, for some robots, they
can tip over. So we're trying to design a robot
that stable even if you're outside of that base of support,
because then it can go like over bathtuble lips, it
can go like onto a bed, it can go over
like gaps and obstacles. So we put these two together
(05:37):
and we developed what my professor calls like a mobile
forklift or robotic candlebars.
Speaker 2 (05:44):
I think that that is so fascinating and such a
leap forward in the technology for the folks that you
know they're going to be listening. They can't see us.
Hopefully they'll do their googles to be able to see ebar.
Can you just describe what ebar looks like from top
to box so that somebody can visualize it in their mind.
Speaker 3 (06:03):
Sure, yeah, I'll try to do my best. It's this
robot that can drive around. It can catch people with
airbags when they fall. It can like physically lift them
up with this sort of U shaped fork at the front,
and then it has handlebars for them to grab onto.
It's kind of just this big U that's padded with
handlebars on the front and on the back. That's the
part of the robot that you grab onto. You can
(06:24):
rest your forearms on it, or you can just grab
onto the handlebars on the side. And it has the
airbags underneath which can grab onto your waist. So that
U shaped fork is attached to a big linkage, and
then that whole thing is attached to an omnidirectional drive base.
And so the drive base, you know, like if you're
trying to parallel parker car, you can't just like slide
into a spot. You kind of have to move back
(06:45):
and forth.
Speaker 2 (06:46):
Right, Oh, Yeah.
Speaker 3 (06:50):
So this robot has four wheels. Each wheel can independently
rotate and translate, and so you can actually just go
and then move sideways instantly, so it can move in
any direction.
Speaker 1 (06:59):
That's great, That is amazing.
Speaker 3 (07:01):
I didn't put this in the paper, but I believe
it's probably the world's fastest elder care robot. So we
limit the power for safety, but it has a max
speed of around twelve feet per second. It's very powerful,
it's moved.
Speaker 2 (07:17):
I need one of those for my home.
Speaker 3 (07:20):
We limit it to like one to two feet per second.
You know, they don't want to cause any injuries.
Speaker 1 (07:25):
Yeah. I think that's a great description of the design
of how ebar looks. And I watched some of the
footage that you all share it's on YouTube, and it
looked like you had I don't know if it was
PlayStation or Xbox style, like a joystick on there, a controller.
Was that part of early testing? You know, what kind
of control system does e bar have?
Speaker 3 (07:47):
Yeah? So right now, in the original paper, it's just
manually controlled with a joystick, like similar to what you
see with mobility scooters, where there's a joystick and people
just sort of move it around. Currently, right now in
the lab, we're working on automating some of the functionality.
So we have a project where we're trying to use
the drive base to track a person automatically so it
can follow them around. And so you know, it's a
(08:11):
lot of work to do that sort of automation, so
we kind of just went for manual control first, but
we're definitely looking into it.
Speaker 1 (08:17):
That's really cool.
Speaker 2 (08:18):
My background is also engineering, and so I also have
a degree in mechanical engineering, and so I know that
part of this is about footprint, because if you're thinking
about the function of this robotis to help folks with
getting around and to keep them safe, we know that
it has to be able to take up as least
(08:38):
amount of space as possible. Can you talk about the
role that the robots footprint played in your design and
how did you make sure that it could navigate in
tight spaces inside of a home without tipping over or
interfering with other things in the house or the user.
Speaker 3 (08:56):
Yeah, for sure, for sure. So our goal was to
make the robe but as small as possible. The problem
is that you know, if it were just like six
inches wide, it would tip over immediately. So what we
did is. We set up a sort of an optimization problem,
and from a high level we said, okay, like how
(09:18):
small can we make the drive base and how heavy
can we make it so that it doesn't fall through
the floor. Because you know, if you think about a person,
a person occupies about one square foot of space if
they're standing up straight. He said, okay, you know the
average person. A floor can support a person that weighs
maybe two hundred three hundred pounds, no problem, So we'll
try to limit the robot weight to that. Then we
(09:39):
looked at like what are the maximum forces people can
apply laterally and horizontally. So it turns out the US
military has done a lot of studies like this in
the eighties and they found that, like I think it's
like one hundred and twenty Newton's horizontal force, they have
like force from any orientation. So we can quantify this
really well, like when you're standing up, how much can
you push on the robot?
Speaker 1 (10:00):
Right?
Speaker 3 (10:00):
So we put all that together and we have a
cost function. With the cost function says, okay, how can
I shrink the robot as much as possible while still
satisfying the load bearing constraints? And so putting those all together,
the actual wheels of the drive base occupy around a
ten inch square and then we have two sort of
outriggers like almost antennae, so we can get a little
(10:22):
bit more stability. And so the footprint of the robot,
I think it's around the base itself is around fifteen
inches by fifteen inches, not including the outriggers. Wow, with
the outriggers, it's a little bit bigger. I think they're
around twenty inches wide. But your average doorways are somewhere
between twenty eight to thirty six inches, so we still
got plenty of space around the door.
Speaker 1 (10:43):
That's amazing.
Speaker 2 (10:44):
And you know, I know that this is designed for
elderly folks that need help around the house, but I
can already imagine this helping a lot of people who
are differently abled from the disabled community. And did you
consider that as you were designing? Is that something that
also came into your mind as another use for ebar?
Speaker 3 (11:04):
Sort of, So we did think about using it for
Parkinson's patients because they sometimes just have a struggle maintaining
their balance, But I think absolutely it could be applied
towards different populations all be honest, we specifically designed it
for elderly persons, but I think you know, there are
certainly other people who could benefit from the robot.
Speaker 1 (11:24):
Absolutely. I think that's such a good point that TT's
talked about before in engineering and design. We've talked about
it in just inclusivity across the board in anything that
you create. You know, the more you think about who
this can help, the more people benefit from it, even
people you didn't consider. I want to know about how
you're these different types of assistance that ebar provides, because
(11:47):
it's not just that you have to fall in. Because
of the shape of it and because of how you
designed it, it seems like it can do more than
just like wait until you're at the ground and needing
to be lifted, right, like ebar can come in ahead
of time. Yeah, I'd love to hear you talk a
little bit more about the different falls you anticipate it,
or the different types of knees you anticipated, and how
you build all those things together into this system.
Speaker 3 (12:10):
Yeah. For sure. Our goal was to catch a person
before they fell, because when they're on the ground, oftentimes
they may be unconscious, they may have passed out, and
it's kind of a bad situation to be and if
the person's already on the ground, right, So you're thinking
of how to do it, and we came up with
the idea of using airbags because they're soft, you can
have like a large contact area. And the question is,
(12:34):
like is it physically possible. So a previous student in
my lab has worked on like fall prediction and she
found that you can predict a fall up to two
hundred fifty milliseconds before the person actually starts to fall down. Wow,
And that's why using like a waste mounted sensor called
an im you. So we said, okay, two fifty milliseconds,
(12:55):
that's our target inflation time. Can we like fully inflate
the airbags and catch a person right before they so then, yeah,
we tried different shapes and sizes and configurations of airbags.
I tested a lot on myself, you see, like how
how much can I inflate them before it becomes painful?
And then we looked at studies of like skin bruising
because you know, we know that elderly people's skin are
(13:16):
kind of sensitive, so we didn't want to cause them
any danger or put them in risk of bruising their skin.
And we settled with a configuration of four airbacks. There's
two big ones on the side and then two smaller
ones on the front like columns, so when they inflate,
they sort of push the person back into the robot.
And then we developed a rapid like two stage inflation
(13:37):
system that can inflate them within two hundred and fifty milliseconds,
so if you're walking, you know, right now. Again, it's
all done manually, but we have done work in our
lab about like detecting falls, just haven't implemented it on
the robot yet. The idea is, if you begin to fall,
the airbags which just rapidly inflate and gravy and sort
of hold on to you, and so you're kind of
frozen in this position, but you have a chance to
(13:58):
regain your balance, or we can deflate the airbags and
you can continue normally, or we can just hold you,
you know, until someone can come to help.
Speaker 2 (14:20):
And so the next part of the engineering is to
you know, test it out on the users. I'm wondering,
you know, one, I think it'll be interesting to hear
like how you get volunteers for this or who you
recruit to test these things out, and then also what
their feedback was and how that informs like how you
move forward and any changes that you might make.
Speaker 3 (14:42):
The major thing we have to make sure before we
can roll actual elderly persons that it's completely safe because
we don't want to cause anyone any injury. So right
now we've been testing in healthy volunteers. By healthy volunteers,
I mean myself and a couple of my web mates. Okay,
but yeah, the idea is to refine the system to
(15:02):
make sure it's safe, to you know, sort of measure
the forces which we have been and so far everything's good.
Then we can apply for approval from our university and
then start enrolding elderly persons.
Speaker 1 (15:12):
Okay, this sounds really cool because you've called EBAR a
step towards aging in place. And I am thinking back
to those commercials where people were like life alert and
they were waiting until they already fail. And like you said,
after you've once you hit the ground, anything could happen.
You could be unconscious. But like I think about what
(15:33):
this could mean. Something you mentioned is how maybe stressed
our healthcare system is for aging adults. Yes, we're talking
about this in the home, but could you imagine this
type of tech in other places like care facilities or
as part of public programs. How do you imagine this tech?
You know, I know we're looking much further ahead, but
how do you imagine it scaling?
Speaker 3 (15:54):
I think for me personally, i'd say, like, I think
the gold standard is a human being. It's very difficult
for robot to replace a human, right. I think We've
seen this again and again. But the reality is that
if there is a care shortage, I think it's better
to like augment the shortage with robots than just to
not be able to do anything about it. So one
(16:14):
thing we were thinking is like in nursing homes, ebar
could sort of handle some of the easier tasks. If
a person just needs to walk, for example, to a sink,
then ebar could help them out. But very complex tasks
like lifting a person into a bathtub with a sling
like those can still be done by the caretakers, so
it can sort of free them up. That instead of
elderly persons having to wait a long time for care
(16:36):
that if for some tasks we could send the robot
and for some tasks we could send a human caretaker.
Speaker 2 (16:43):
I love that because Menzakia talk about this all the
time where a lot of solutions to the world's problems
is not an or response like this or that. It's
an and so not to say, oh, Ebar is going
to replace all caregivers, there won't be a need for
a human. It's like, no, you can have the human
(17:03):
and you can have e bar, which to supplement and
it makes it an even better experience. I'm curious about,
you know, what are the next steps with ebar. Are
there any like upgrades or advancements that you want to
add to EBAR, or what's the vision or are there
things that you want to do outside of e bar
(17:25):
to also help supplement EBAR.
Speaker 3 (17:28):
Yeah, that's a great question. Honestly, it's discussion my advisor
had with me almost immediately after I submitted the paper. Yeah.
I think certainly there's room for making the robots smaller
and more compact. I've talked with a lot of people,
even my parents are saying like, hey, you should add
something that can pick up a person's phone if it
(17:49):
falls down, like a sort of a coup holder on
the robot. I said, well, that's great. I'd love to
do that, but I don't know if I can really
put that in my thesis work. So one of the
other things our lab is looked into is handlebar optimization.
Like if you think about it, when you go into
restrooms or some public places, you see handlebars on the walls.
(18:12):
It turns out there's not really been a lot of
work that's been done on like is this the biomechanically
optimal location for handlebar? And because like you know, who knows,
it could be in front of you, it could be
like up here, it could be like down there. So
we were trying to look into, like can we make
a model of a person and then predict like where
is the optimal place for handlebar it maybe reduces the
(18:35):
muscle strength the most or provides the most support. So
that sort of stuff I think is interesting and I
think could compliment a robot like e bar because then
it helps us nowhere to position the U shaped fork
based on the posture of the person. So yeah, that's
I guess that sort of work that we've been looking
to and thinking about pursuing in the future.
Speaker 1 (18:52):
Okay, I think this is so cool.
Speaker 3 (18:55):
Things.
Speaker 1 (18:56):
You know, this is totally outside my comfort zone of science.
TT understands this kind of stuff way better than me,
which is why she has such great questions, is there
anything else here seeing in the field of robotics and
elder care? Is there anything else you're excited about this
in the research pipeline, even if it's not in your lab,
like with other labs that do great work that you see, Ye,
(19:18):
that feels promising.
Speaker 3 (19:20):
So we are collaborating with So just full disclosure. But
at Stanford, Alison O Kumurro, she did a lot of
work on these things called vine robots. They're sort of
like flexible tubes. They can inflate and they can go
under a person. And so we have this idea. It's like,
wait a second, you have an elderly person lying in
(19:40):
bed and you want to like put them in a sling,
Like right now, you've got to lift them up and
pull a slip. What if the sling just like inflated
under them, like and then you could just pick them
up that way. So that work I think we've been
doing with her. But she was the one who's been
working on vine robots. I think that's really cool. In
terms of other labs and other research, we see a
(20:03):
lot of work with humanoids. Humanoid robot seems to be
like the next big thing. There's a bunch of companies
pursuing humanoids, and so people have started looking into like
using a humanoid for sit to stand assistance, which I
think is pretty cool. My concern with it is just,
especially if the robot has two feet, it's not going
to be a stable as something that has like a heavy,
(20:23):
big drive base. You know, like if the robot and
the person fall down, then that's really bad. But I
think it's great work though. I think that that should
be explored. And I saw a couple of papers when
I was at akra Acra is a big robotics conference
that happens each year. It's sort of like v big
robotics conference, and so I saw a couple of papers
(20:43):
where people are looking at using humanoids to like provide
sit to stand assistance, and I thought that was really cool.
Speaker 2 (20:48):
Yeah, I was thinking about this the other day because
I've also been noticing a lot of the humanoid innovation
and how it's like, you know, as engineers, we try
and create things that are not just flashy but useful,
and it doesn't really seem intuitive to me to say,
(21:11):
this human is not able to form this task, so
I'm going to replace it with another human but I
think people are just so enamored by humanoids.
Speaker 1 (21:20):
I'm not. As a non engineering person, I feel like,
give me the e bar. If I knew I was
falling back into a face, I don't think I would
like this, you know, And so I think it's interesting,
Like I feel like that humanoid component is what makes
people feel like, oh, you're trying to replace me, or
oh that's my own bias that I think. If it's
(21:42):
hard already for a person to help you, why would
I put it in something else that's person shaped to
do the same work so it can be just as
hard for it.
Speaker 2 (21:49):
Yeah, make that inflatable sling, Like, I love that idea.
Speaker 1 (21:55):
I think it's great.
Speaker 2 (22:09):
My last question is just about the process, because we
just did an episode on the research funding cuts and
stuff like that. I really would love for you to
highlight like what it takes one to get to this
point with EBAR and then to have EBAR kind of
like break into the healthcare system, if you know, because
I think that one thing that the Kia said is
(22:31):
that folks they don't think about research in the way
that they should. They think about innovation. So when the
product is there and in their hand, they're like, ah, research,
and it's like, no, that's innovation. There's a lot of
research that gets you to that point. So can you
talk about that process for yourself. I think it would
be great for people to here to understand what it
takes to do something like this.
Speaker 3 (22:52):
I took product design. It was a class at MIT
a couple of years ago. They presented us with this process.
I think it's just called like a need driven develop
and process. But the idea is you start first with
the stakeholders. You go to the elderly person, you ask
them like what sort of tasks are you trying to do?
And then oftentimes what you find is people will tell
you things, but really there's like underlying needs they're called
(23:16):
latent needs that they're not really telling you. They can't
really put into words well, but it becomes obvious as
you look into more of the of what they're doing. Like,
for example, an elderly person might say like, oh, you know,
I really have trouble getting into and out of the bathtub,
but I want is just like like a cane or
something that'll help me get in and out. And you're like, well,
(23:39):
maybe the problem is that the tub is too high.
Maybe it's the problem that, like, you just need a
little bit of support, and so it may not be
a cane that you want. It may be like a
robot or a handlebar or some other device that can
also help you. So we start with this stakeholders and
looking at the latent needs and then in our case,
we develop this sign concept for robot and we went
(24:02):
to a physical therapist that's Spaulding Rehabilitatian Hospital. We did
a presentation and they said, oh, we like these aspects
of it, but we think these aspects wouldn't work with
the patients that we work with. So then we sort
of go back and forth a couple of times, rEFInd
the design, and then from there on it's the most
fun part for me. I get to build a prototype.
Speaker 1 (24:21):
I think that's interesting because that's such a long process
and the only research you're highlighting is the new research
that you're doing. But you've already told us that even
in your prototype, to determine how much force a person
might use, you're going back to research from forty years
ago to the nineteen eighties, right, and so research that
some people may say, why does the army need to
(24:43):
do this, or why does the military need to figure
out how much force a person exerts laterally, because in
forty years, a graduate student is going to be figuring
out how to design a robot that can keep your
grandmother from falling when she reaches for something. And I
just think those are the connections between research and innovation
that we don't highlight enough. You're relying on research that
(25:06):
has already been done to help you iterate and innovate
really quickly to decide what the drive based size should be.
And I think it's just such a good demonstration of
research and innovation how closely those two rely on each other.
Speaker 3 (25:22):
For sure, for sure, And there are so many times when, like, like,
one of the critical things that we've needed was you
needed to know the friction between a person's skin and
their clothes. There's a sony in twenty thirteen that characterizes
so thank you so much. You know, it's such an
obscure piece of knowledge. You think, like, when would you
ever need that? But it turns out we need to know, like, well,
the closes slip on the skin if we can press
(25:43):
them with airbags. So this random research study ended up
being extremely useful because we can quantify now the friction.
So yeah, there's a ton of these connections between prior research,
some of it not even remotely related to elder care.
But you know, it's like we're standing on the show
of giants. Yes, all this knowledge gets built up, and
(26:03):
you may not think it's useful in the moment, but
then twenty years down the road someone needs it. It's
like the exact thing that they need exactly.
Speaker 2 (26:10):
And that's another thing that we always say is that
science never stops. And that is a really good illustration
of that, where you know, just because that part of
research ended or that paper was published, doesn't mean that
it'll never be used again. It doesn't mean that it
won't be useful. It doesn't mean that you can't build
(26:32):
off of that. And so like science never never stops,
someone will be citing your paper one hundred years from now,
I'm sure and saying, wow, look what we were able
to do based on what Roberto and his lab group
were able to do, and now we can innovate off
of that. The science never stops, and the work that
we do is really important, even if it feels obscure.
(26:54):
Sometimes I think about my graduate, my dissertation work, and
I'm like, oh, oh god, no one needs this. It
was in nano materials. And then I'll go and look
at some of my old papers. I'm like, wow, cited
eighty times. Okay, that's not bad, that's excellent.
Speaker 3 (27:12):
Yeah. No, it's cool to see you. Everything fits together,
and honestly, I think we're going to see more and
more on that.
Speaker 2 (27:19):
Congratulations on all of your success. We will be tapping
into mix to see how Ebar is evolving and your
success as your career continues to grow and change. You're
doing a great job and doing a lot of really
important work. So congratulations, Well, thank you so much.
Speaker 3 (27:36):
I'm honestly, I'm just so grateful to have the opportunity,
you know, to be a graduate student and to study
all of this. I'm you know, I'm always very grateful
for that.
Speaker 1 (27:45):
So amazing.
Speaker 3 (27:46):
Thank you, guys. I appreciate it.
Speaker 2 (27:55):
You can find us on X and Instagram at Dope
Labs podcast.
Speaker 1 (28:00):
He is on X and Instagram at d R Underscore
t Sho.
Speaker 2 (28:03):
And you can find Zakiya at z said So.
Speaker 1 (28:06):
Dope Labs is a production of Lamanada Media.
Speaker 2 (28:09):
Our senior supervising producer is Kristin Lapour. And Our Associate
producer is Issara Savez.
Speaker 1 (28:16):
Dope Labs is sound design, edited and mixed by James Barber.
Lamanada Media's Vice President of Partnerships and Production is Jackie Danziger.
Executive producer from iHeart Podcast is Katrina Norvil. Marketing lead
is Alison Kanter.
Speaker 2 (28:31):
Original music composed and produced by Taka Yasuzawa and Alex
sugi Ura, with additional music by Elijah Harvey. Dope Labs
is executive produced by us T T Show Dia and
Kia Wattley.
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