Latest / Glovisor Podcast / Her Mom Fell—So She Invented an AI Device to Change Patient Mobility | Sheila Buswell (Ep 60)

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Her Mom Fell—So She Invented an AI Device to Change Patient Mobility | Sheila Buswell (Ep 60) · Glovisor Podcast

• 0:00
  Speaker 1: Can thousands of lives change because of the hardest moments
• 0:03
  Speaker 1: you've ever faced? This is a story about resilience, innovation,
• 0:07
  Speaker 1: and purpose. Welcome to the Glowvisor podcast, where we explore
• 0:14
  Speaker 1: business growth, communication, and personal development through real conversations with
• 0:18
  Speaker 1: people that make an impact. Our guest is the CEO
• 0:21
  Speaker 1: and co-founder of Buzzwell Biomedical, the company behind Upward Mobility,
• 0:26
  Speaker 1: and AI-enabled mobility device transforming how hospitals support patient movement.
• 0:32
  Speaker 2: A U.S.
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  Speaker 1: Army veteran and engineer, she brings a passion for restoring
• 0:37
  Speaker 1: patients' independence, reducing caregiver strain, and pushing healthcare forward through innovation, entrepreneurship,
• 0:45
  Speaker 1: and resilient leadership. GloVisor welcomes Sheila Buswell.
• 0:49
  Speaker 2: Thank you, Joe. I'm happy to be here. A pleasure.
• 0:52
  Speaker 1: Looking forward to the conversation.
• 0:53
  Speaker 2: All right.
• 0:55
  Speaker 1: So, Sheila, let's begin. Please share with us a little
• 0:57
  Speaker 1: bit more about what you do.
• 0:59
  Speaker 2: Being a patient myself, but mostly when I saw my
• 1:01
  Speaker 2: mom in rehab, I wanted to empower her in a way.
• 1:07
  Speaker 2: And I wanted to empower myself and patients totally. And
• 1:10
  Speaker 2: I'm an engineer, so I look at things technically. And
• 1:13
  Speaker 2: I was like, oh, how do we solve this problem?
• 1:15
  Speaker 2: And then every day I try to solve that problem
• 1:19
  Speaker 2: and make it more obtainable for everybody in those situations.
• 1:25
  Speaker 2: And so day to day, I work to further the business.
• 1:29
  Speaker 2: And sometimes that's cleaning toilets and taking out trash. But
• 1:32
  Speaker 2: sometimes it's pitching, you know, for millions of dollars or,
• 1:36
  Speaker 2: you know, hundreds of thousands of dollars to venture capitalists
• 1:39
  Speaker 2: or angel investors.
• 1:41
  Speaker 1: Tell us a little bit more about Buswell Biomedical. What
• 1:44
  Speaker 1: are you focusing on right now?
• 1:46
  Speaker 2: We have the product Upwork Mobility, Upmo for short. And
• 1:53
  Speaker 2: I got a patent for it. where the whole business
• 1:56
  Speaker 2: is formed around that and to get input from health
• 2:00
  Speaker 2: care workers to make them safer and from people who
• 2:04
  Speaker 2: are patients or have loved ones that were patients and
• 2:06
  Speaker 2: see what we could add. And one problem that we
• 2:09
  Speaker 2: hear all the time is that when you're in a
• 2:11
  Speaker 2: hospital or rehab setting, activities of daily living, especially toileting,
• 2:15
  Speaker 2: can be cumbersome. And so to figure out how to
• 2:18
  Speaker 2: do that. and make it expeditious. And because when you
• 2:22
  Speaker 2: have to go, you have to go, you can't wait
• 2:24
  Speaker 2: hours sometimes. And that would be, that's a meaningful work.
• 2:31
  Speaker 2: But when I worked for a beer company, I didn't,
• 2:33
  Speaker 2: you know, it wasn't that meaningful. When I worked for
• 2:36
  Speaker 2: Harley Davidson, not that meaningful, but this is meaningful on
• 2:39
  Speaker 2: a level I can't explain, like to make people's lives better. Yeah,
• 2:42
  Speaker 2: that makes sense.
• 2:43
  Speaker 1: Now, does the patient have the ability to, to move
• 2:47
  Speaker 1: out of the bed using the upward mobility under OWN,
• 2:51
  Speaker 1: or does a caregiver or a nurse have to help
• 2:54
  Speaker 1: the patient?
• 2:55
  Speaker 2: The answer to that would be, it would depend on
• 2:57
  Speaker 2: the patient. The idea is to empower people where they can.
• 3:01
  Speaker 2: And so the current status of care is if you
• 3:06
  Speaker 2: have to conduct any activity of daily living and you're
• 3:08
  Speaker 2: considered a mobility concern, you call a nurse or healthcare worker.
• 3:11
  Speaker 2: The healthcare worker comes or an entourage of healthcare workers
• 3:16
  Speaker 2: when they can do the things. I mean, you're supposed
• 3:21
  Speaker 2: to lift like 50 pounds and I haven't weighed 50
• 3:25
  Speaker 2: pounds since I was under five. But like you need
• 3:28
  Speaker 2: to have a number of people. Even my mom was
• 3:32
  Speaker 2: 99 pounds. She had to have two people in theory.
• 3:36
  Speaker 2: But you would call this device, EPO, and it would
• 3:39
  Speaker 2: travel to you autonomously like a self-driving car. They have
• 3:42
  Speaker 2: wheelchairs that do this in airports. but I don't think
• 3:44
  Speaker 2: that's the best. Using lighter technology like a Roomba or
• 3:48
  Speaker 2: a self-driving car to come to you in an airport,
• 3:51
  Speaker 2: in a hospital setting. And then if you're able to,
• 3:57
  Speaker 2: this device, you'd hook your own, the lanyard to your
• 4:00
  Speaker 2: specialized harness, and then you put that harness on like
• 4:03
  Speaker 2: a jacket, and then you could go conduct any activity
• 4:05
  Speaker 2: day living by yourself. If you're able to do that.
• 4:09
  Speaker 2: If you're not, it could help people in a situation
• 4:13
  Speaker 2: if a healthcare worker needs to come because it turns
• 4:16
  Speaker 2: one healthcare worker into many because they won't have the
• 4:20
  Speaker 2: same strength. Like they're using more cognitive ability, hand-eye coordination,
• 4:28
  Speaker 2: not brute strength lifting.
• 4:30
  Speaker 1: This is really interesting. So I guess just for more clarification,
• 4:34
  Speaker 1: just because I haven't seen this in progress, but so
• 4:37
  Speaker 1: if you're in a room in a hospital, you can
• 4:40
  Speaker 1: call this device that will self-drive to your room. And
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  Speaker 1: then if I'm able to, as a patient, I can
• 4:47
  Speaker 1: just latch on and it will help me get out
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  Speaker 1: of bed. Will it bring me to the restroom or
• 4:54
  Speaker 1: will it just help me up?
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  Speaker 2: The reason you have a specialized harness is it can,
• 4:58
  Speaker 2: it knows your body. Like I walk with a lump
• 5:00
  Speaker 2: and it knows that that would be normal for me,
• 5:02
  Speaker 2: but it probably isn't normal for most people, but it
• 5:06
  Speaker 2: would compare what everybody's motion is. And that's the machine
• 5:09
  Speaker 2: learning part with your motion. and anticipate a fall. But
• 5:12
  Speaker 2: other than the way it would prevent a fall is
• 5:16
  Speaker 2: like a little kid, when he's learning how to walk,
• 5:18
  Speaker 2: you pick it up. And it's not to have somebody,
• 5:21
  Speaker 2: a patient hanging there like a pinata. It's just so
• 5:23
  Speaker 2: that you can have your feet under you, like stabilize yourself.
• 5:28
  Speaker 2: But you go to the bathroom. Most people fall between
• 5:32
  Speaker 2: 11 p.m. and 1 a.m. going to the bathroom. So
• 5:35
  Speaker 2: the idea is to, and when healthcare workers are going
• 5:39
  Speaker 2: to help somebody, There is usually, they had to go
• 5:43
  Speaker 2: like when you ring the button, when you ring for help, right?
• 5:45
  Speaker 2: Like you're not, sometimes they wait for hours. When you
• 5:48
  Speaker 2: go into a rehab facility, you meet with a person
• 5:51
  Speaker 2: who's like a RN or equivalent and they can assess
• 5:56
  Speaker 2: whether you're physically able or, and that the assessment needs
• 6:00
  Speaker 2: to be made at that level. And at that time,
• 6:03
  Speaker 2: they would also say, you know, if you, if you stumble,
• 6:07
  Speaker 2: you can control lower to the ground. They could pick
• 6:10
  Speaker 2: the corrective action or raise you up a little bit
• 6:15
  Speaker 2: so that you could get your feet under you, take
• 6:17
  Speaker 2: your weight off. Off-weight people, I think, is the right term.
• 6:20
  Speaker 2: And right now, this type of device is used in
• 6:24
  Speaker 2: the hakoma. It's to fit around a treadmill in physical therapy.
• 6:29
  Speaker 2: But the upward mobility would fit through a doorframe and
• 6:31
  Speaker 2: around a toilet. So... That's why it's used in hospitals
• 6:36
  Speaker 2: and rehabilitation hospitals because the door frames are standardized. In houses,
• 6:41
  Speaker 2: they're not, you know. But I think once we get
• 6:43
  Speaker 2: that motion library, we can find out where people are unstable.
• 6:47
  Speaker 2: And we know a lot of people have stabilization issues
• 6:54
  Speaker 2: in the bathroom. right? Like there's a, but there's a
• 6:57
  Speaker 2: lot going on there. They're standing up. If it's particularly,
• 7:00
  Speaker 2: you have a problem standing up or sitting down or
• 7:04
  Speaker 2: walking is a, there's a huge library on that, but
• 7:07
  Speaker 2: people who the ultimate goal is to let people stay
• 7:10
  Speaker 2: in their houses longer, but we can learn a lot
• 7:12
  Speaker 2: from the motion of when people fall the most and
• 7:15
  Speaker 2: what predictors are identify you as soon to fall. We
• 7:20
  Speaker 2: want to stop that or limit it. That travel distance
• 7:23
  Speaker 2: to six inches or, you know, not get to the
• 7:28
  Speaker 2: point where in hospitals, they say an unplanned descent to
• 7:32
  Speaker 2: the floor with and without injury. That's a whole thing.
• 7:36
  Speaker 2: But the idea that we would just be able to
• 7:40
  Speaker 2: make people safer and patients safer and healthcare workers safer,
• 7:47
  Speaker 2: because Your healthcare workers get injured a lot of the
• 7:50
  Speaker 2: time helping heavier patients or helping patients, period. You're not,
• 7:53
  Speaker 2: there's the OSHA thing of lift with your legs, not
• 7:56
  Speaker 2: your back. Well, what do you catch with in an emergency? Whatever.
• 8:00
  Speaker 1: Now, how does AI integrate with the hospital? You mentioned
• 8:04
  Speaker 1: how different patients will have different requirements. Is there an
• 8:09
  Speaker 1: integration process? where it identifies which patient can do which task?
• 8:15
  Speaker 2: I think most people, when they think of artificial intelligence,
• 8:18
  Speaker 2: they think of large language models, like my chat GPT
• 8:20
  Speaker 2: can write an email for me or Grok can tell
• 8:22
  Speaker 2: me what the best pet sitters or pet trainers are.
• 8:26
  Speaker 2: And I think the idea of a machine learning, and
• 8:29
  Speaker 2: that's where it goes to, it's like the understanding of
• 8:32
  Speaker 2: motion and like what's normal motion and what's, right now
• 8:36
  Speaker 2: we don't know enough about what predicts a fall. Some
• 8:40
  Speaker 2: people just fall. But there are some things that, you know,
• 8:44
  Speaker 2: they know little rugs all over your house can make
• 8:46
  Speaker 2: people trip and fall. So eliminating that and little things
• 8:51
  Speaker 2: we can learn where we help. We're going to have
• 8:53
  Speaker 2: more data. We can get more information from it. So
• 8:57
  Speaker 2: that's how it integrates. The machine learning algorithm that determines stability.
• 9:03
  Speaker 2: And then the self-driving car. I use that. like the
• 9:08
  Speaker 2: up mode driving to you, like a Roomba or a
• 9:11
  Speaker 2: self-driving car, it totally is a LIDAR technology that's artificial intelligence.
• 9:17
  Speaker 2: It can determine if there's obstructions that they need to avoid.
• 9:22
  Speaker 2: Different hospitals have, different states have different laws. Like I
• 9:25
  Speaker 2: think Texas had a hospital shooting or something. And so
• 9:32
  Speaker 2: there is doors that have to remain shut. And there's
• 9:36
  Speaker 2: limited ability to travel from one place to another. So
• 9:41
  Speaker 2: that would have to be navigated and have to use
• 9:45
  Speaker 2: artificial intelligence.
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  Speaker 1: Every successful entrepreneur has that defining moment that made them
• 9:53
  Speaker 1: make that item or come up with that idea and
• 9:57
  Speaker 1: put it to action. What inspired you to pursue this path?
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  Speaker 2: It definitely, I didn't have the entrepreneurship spirit. It was
• 10:04
  Speaker 2: one of those things where I gave myself a pep talk.
• 10:07
  Speaker 2: If not you, then who? And if not now, then when?
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  Speaker 2: And so we talked before I got it. I had
• 10:12
  Speaker 2: a scholarship when I graduated high school to the University
• 10:14
  Speaker 2: of Utah. I was tied to a high GPA that
• 10:16
  Speaker 2: I did not maintain. And after two years, I joined
• 10:18
  Speaker 2: the U.S. Army. And I was injured in Bosnia in
• 10:21
  Speaker 2: 1998 on a deployment there. And I had a generator
• 10:25
  Speaker 2: fell off a forklift and my foot was under it.
• 10:29
  Speaker 2: And I was a patient in a UN hospital called
• 10:33
  Speaker 2: the Blue Factory. I'm sure they call all the, knowing
• 10:36
  Speaker 2: the military, that's what it's called, on a peacekeeping mission
• 10:39
  Speaker 2: or any, anyway. It was a thing where I was like,
• 10:46
  Speaker 2: I had a cadre of Norwegian nurses and I had
• 10:50
  Speaker 2: no problem there, but it was like, that was the
• 10:53
  Speaker 2: hardest thing for me to get. There wasn't a shortage
• 10:55
  Speaker 2: of people. It was just that, oh man, going to
• 10:59
  Speaker 2: the bathroom when there's somebody there is just not something
• 11:01
  Speaker 2: you want to do. And after I got out of
• 11:03
  Speaker 2: the military, I got a medical discharge and I got
• 11:05
  Speaker 2: out in 2001. And then 20 years later, my mom
• 11:11
  Speaker 2: falls in Arizona and has an accident. But this time,
• 11:15
  Speaker 2: After those 20 years, I worked for a lot of
• 11:19
  Speaker 2: great companies. I ultimately obtained a master's in engineering, right?
• 11:23
  Speaker 2: So I go out to, I'm not a caregiver. So
• 11:28
  Speaker 2: I go out there and my first impulse is to
• 11:31
  Speaker 2: be mean to the healthcare workers because my mom's, I
• 11:34
  Speaker 2: was frustrated. And I saw my mom struggle with the
• 11:38
  Speaker 2: same standard of care that I experienced 20 years prior.
• 11:41
  Speaker 2: And I knew by this time that there was a
• 11:43
  Speaker 2: better way. But it's hard when you're talking to healthcare workers.
• 11:47
  Speaker 2: They think large language model. This means more paperwork. I
• 11:51
  Speaker 2: don't want more paperwork. They don't mind helping people go
• 11:54
  Speaker 2: to the bathroom. That's something they can do. They're trained
• 11:55
  Speaker 2: for that. They're expecting that. Filling out a paperwork to
• 11:59
  Speaker 2: keep the lawyers happy is not what they want to do.
• 12:04
  Speaker 2: But I was able to identify a solution to the problem.
• 12:08
  Speaker 2: I thought at the time, I'll just go work for
• 12:09
  Speaker 2: the company that's developing a solution to this. Well, that
• 12:13
  Speaker 2: problem was there nobody was developing the solution. Like, so
• 12:19
  Speaker 2: I was like, well, I figured out how to solve
• 12:23
  Speaker 2: the problem. And I was like, well, what to do now?
• 12:25
  Speaker 2: And so I started Best Well Biomedical and obtained a
• 12:29
  Speaker 2: patent for the utmost.
• 12:32
  Speaker 1: So can you share with us a little bit about
• 12:35
  Speaker 1: how long did that process take from the moment that
• 12:37
  Speaker 1: you realized there was a need, you found that no
• 12:40
  Speaker 1: one was fulfilling it, And now you're going to step
• 12:43
  Speaker 1: up and you designed this machine, this AI mobility or Upmo,
• 12:50
  Speaker 1: as you call it, and you designed it and then
• 12:53
  Speaker 1: you put in. So how long did that process take
• 12:55
  Speaker 1: to get to the point where you're patting and ready
• 12:58
  Speaker 1: to roll?
• 12:59
  Speaker 2: What happened initially when my mom fell was like April
• 13:01
  Speaker 2: of 2019 or 2018. And then I figured out a
• 13:04
  Speaker 2: solution by June, but, and I, it took a while.
• 13:11
  Speaker 2: I would say a couple months to determine that there
• 13:13
  Speaker 2: wasn't anybody working on this. And I was just going to, oh,
• 13:16
  Speaker 2: I have this personal experience. I can go work on it.
• 13:19
  Speaker 2: And that was 2018. And now it's 2026. And then
• 13:24
  Speaker 2: closed in that timeframe. It was first, I wanted to
• 13:27
  Speaker 2: prove that my idea was feasible, right? So I went
• 13:31
  Speaker 2: and developed a short machine learning library and I got
• 13:36
  Speaker 2: a hundred specimens with four inertial measurement units and I
• 13:41
  Speaker 2: gave it to a data scientist, but it was awesome
• 13:43
  Speaker 2: because the time was like 2020 and I was going
• 13:46
  Speaker 2: around and be like all the age group, male and
• 13:49
  Speaker 2: female across the age spectrum. It was really great to
• 13:52
  Speaker 2: talk to a 20 year old man as a middle-aged
• 13:54
  Speaker 2: woman and be like, stand up and sit down for science.
• 13:57
  Speaker 2: I need to capture your emotion. It was weird. There
• 13:59
  Speaker 2: was no way to, that took a lot of the
• 14:01
  Speaker 2: military in me to be like, we're going to do this.
• 14:04
  Speaker 2: And it's for, for it's for the betterment of humanity,
• 14:09
  Speaker 2: but it was hard. And then to get that proven
• 14:12
  Speaker 2: and then to prove that it was feasible. And then
• 14:14
  Speaker 2: we got a mechanical prototype and tested that it could,
• 14:19
  Speaker 2: we physically made it so it could fit through a
• 14:21
  Speaker 2: doorframe and around the toilet, but then it was like
• 14:26
  Speaker 2: stable enough and it could lift enough weight. So we
• 14:28
  Speaker 2: have a mechanical prototype that can lift 500 pounds at
• 14:32
  Speaker 2: a Like having the idea, I thought we had an
• 14:40
  Speaker 2: idea and it was needed and there was a need
• 14:43
  Speaker 2: for it. But it's almost like you don't realize you
• 14:48
  Speaker 2: have a problem or people don't realize they're going to
• 14:50
  Speaker 2: be old. And it's really hard to sell somebody who's
• 14:53
  Speaker 2: in their 30s that they're going to be in a
• 14:54
  Speaker 2: nursing home or you're going to have problems with your knees.
• 14:59
  Speaker 2: And that's a difficult sell, but it's easier. To talk
• 15:02
  Speaker 2: to people about their loved ones. For myself, when I
• 15:04
  Speaker 2: was 20 years old, I was like, yeah, this is terrible.
• 15:06
  Speaker 2: But it was more mentally taxing and pulled at my
• 15:11
  Speaker 2: heartstrings more when I saw my little mama waiting to go,
• 15:14
  Speaker 2: you know, for any of the activities of daily living
• 15:16
  Speaker 2: and to solve those problems. It's something that's going to
• 15:19
  Speaker 2: affect everybody. And it's important to work. Like I keep saying,
• 15:23
  Speaker 2: bringing this back to it. I feel like this work
• 15:26
  Speaker 2: is meaningful and it's going to impact a lot of
• 15:29
  Speaker 2: lives in the future.
• 15:30
  Speaker 1: You have a prototype. What is the next step after this?
• 15:35
  Speaker 2: Well, we absolutely need FDA clearance. But to get to
• 15:39
  Speaker 2: FDA clearance, we have to figure out that this is
• 15:42
  Speaker 2: safe and applicable and we have to be able to
• 15:44
  Speaker 2: prove that. And then, so there's a lot of testing involved.
• 15:50
  Speaker 2: And I don't, Joe, it's really expensive to get testing
• 15:52
  Speaker 2: and to develop a machine learning algorithm, but that's the
• 15:56
  Speaker 2: next steps.
• 15:57
  Speaker 1: So who should be contacting you right now?
• 15:59
  Speaker 2: So venture capitalists or angel investors would be great. But
• 16:01
  Speaker 2: I'd love to hear from people who have been patients,
• 16:04
  Speaker 2: have loved ones of patients or healthcare workers to just
• 16:06
  Speaker 2: give me your input, what problems we could solve. That
• 16:08
  Speaker 2: would be great. What problems have you faced that you
• 16:11
  Speaker 2: think we could help with? So that's helpful, right?
• 16:14
  Speaker 1: To listen to some feedback and then integrating. And I
• 16:18
  Speaker 1: guess that would be version two, version three. As you
• 16:21
  Speaker 1: move along, these models just continue improving like every other product.
• 16:25
  Speaker 2: Well, and I think when more people, we get more
• 16:27
  Speaker 2: people using it, we're going to get more input. We
• 16:29
  Speaker 2: get more people. I am a total believer in that
• 16:34
  Speaker 2: the more people use it, that's feedback you get. But
• 16:38
  Speaker 2: you have to ask the right questions. You have to
• 16:40
  Speaker 2: get it. Doing things in a vacuum, I've learned so much,
• 16:44
  Speaker 2: mostly around what I didn't know before. But healthcare workers specifically,
• 16:47
  Speaker 2: they fight those battles daily. So what could we do
• 16:51
  Speaker 2: to help make your life easier?
• 16:53
  Speaker 1: If one of our listeners is an angel investor and
• 16:55
  Speaker 1: contacts you today and just gives you endless amount of money,
• 17:01
  Speaker 1: how long before you think you can get to market?
• 17:05
  Speaker 2: After we get the FDA clearance, I think it would
• 17:07
  Speaker 2: be about six months.
• 17:08
  Speaker 1: Yeah, because I can see this model being very interesting
• 17:11
  Speaker 1: to hospitals today, but I think ultimately... Other variations, it
• 17:15
  Speaker 1: may be a little smaller. They can be used in
• 17:17
  Speaker 1: the home. Some people may be interested if it can fit.
• 17:20
  Speaker 2: Well, that's the biggest thing about it. I think our
• 17:22
  Speaker 2: ultimate goal is when we learn more about motion. But
• 17:25
  Speaker 2: we can't make something any smaller. Door frames in houses
• 17:29
  Speaker 2: are variable. Like our house in the city, when we
• 17:32
  Speaker 2: lived near St. Louis City, it was a 100-year-old house.
• 17:35
  Speaker 2: And it had one door frame that was 28 inches.
• 17:39
  Speaker 2: So there's people these days that are bigger than 28
• 17:41
  Speaker 2: inches across. So it's very hard to make something, if
• 17:46
  Speaker 2: not impossible, structurally sound to prevent a fall and be mobile.
• 17:52
  Speaker 2: But if we know that you have these moments of
• 17:55
  Speaker 2: instability when you stand, where we could place stuff that
• 17:58
  Speaker 2: doesn't have to move so that you can stay in
• 18:00
  Speaker 2: your house longer.
• 18:01
  Speaker 1: Now, if listeners remember only one thing from today's conversation,
• 18:06
  Speaker 1: what do you hope that message is?
• 18:08
  Speaker 2: I think when I was young and it would still
• 18:10
  Speaker 2: serve me, it still serves me today is to just
• 18:13
  Speaker 2: trust my gut more than I do other people. And
• 18:17
  Speaker 2: because that's your intuition. And I think that a lot
• 18:21
  Speaker 2: of people think we're only going to be able to
• 18:24
  Speaker 2: do this or that. It's not ill-intentioned. It's just they're
• 18:28
  Speaker 2: limited by their experiences and their education and I think
• 18:33
  Speaker 2: that's what led me down this path of entrepreneurship and
• 18:36
  Speaker 2: is just being open to that and just being like, okay,
• 18:39
  Speaker 2: we are offering something and people think exoskeleton, people think
• 18:43
  Speaker 2: they're robotics in a different way. Like they think a
• 18:46
  Speaker 2: robot is gonna be like the humanoid robot that can
• 18:50
  Speaker 2: run faster than Hussein Bolt. Well, it might be a
• 18:52
  Speaker 2: robot that folds your laundry or does your dishes or
• 18:56
  Speaker 2: at Harley-Davidson, we had packaging robots that were awesome to watch,
• 18:59
  Speaker 2: but they did not look like a humanoid. And I
• 19:02
  Speaker 2: think to really think outside the box, you need to
• 19:06
  Speaker 2: feel and to solve problems, you need to be able
• 19:09
  Speaker 2: to trust your gut.
• 19:11
  Speaker 1: Now, where can our audience connect with you? Find out
• 19:14
  Speaker 1: more about your work and continue this conversation.
• 19:17
  Speaker 2: BuswellBiomedical.com.
• 19:19
  Speaker 1: Nice and easy. Sheila, thank you so much for spending
• 19:22
  Speaker 1: time with us today and sharing your story and your invention.
• 19:28
  Speaker 1: I'm looking forward to seeing it in person.
• 19:30
  Speaker 2: Thank you. Thanks, Joe.
• 19:32
  Speaker 1: Thanks, everyone, for listening. If this episode inspired you, share
• 19:35
  Speaker 1: it with someone who needs it. And don't forget to
• 19:37
  Speaker 1: follow the Globalizer podcast for more conversations to make an impact.
• 19:41
  Speaker 1: Till the next time.