The lymphedema monitoring technology originated through research at the Georgia Institute of Technology and was further developed for market by the company LymphaTech, which also emerged from Georgia Tech. Now, a new study has benchmarked the technology, finding that it effectively detects early arm swelling associated with lymphedema in breast cancer patients.
The detection technology is intended to improve not only patients’ physical health but also their peace of mind and finances.
“The most immediate awful consequence of lymphedema is seen in mental health. Severe depression is very high,” said Brandon Dixon, who co-led the study and is an associate professor in Georgia Tech’s George W. Woodruff School of Mechanical Engineering. “If you detect it early, managing it could cost as little as $2,500 in a patient’s lifetime. If you catch it too late, the costs can rise as high as $200,000.”
“Lymphedema is under-researched, so we don’t know directly how it may lead to deadly health conditions, but there are more cases than AIDS, Parkinson’s disease, and Alzheimer’s disease combined, and it diminishes patients’ health,” Dixon said.
The researchers published the detector’s test results in the journal Physical Therapy in February 2019. Dixon and Georgia Tech graduates founded LymphaTech through the initiative TI:GER, Technology Innovation: Generating Economic Results at Georgia Tech’s Scheller College of Business. The startup received early funding from the Georgia Research Alliance.
Lymphedema can strike breast cancer survivors if surgery includes the removal of a lymph node, slowing the flow of lymph. The liquid waste can congest the arm, at first subtly but later so drastically that patients may no longer fit into their clothing.
“It makes the stigma of cancer stick out,” Dixon said. “And it is a very underappreciated disorder in medical treatment, so patients can feel stuck with it with no way out.”
A German device called a perometer accurately detects arm swelling caused by lymphedema, but perometers are seldom available in the U.S. The research team could find only one in metropolitan Atlanta to benchmark the LymphaTech system against. It was located at TurningPoint Breast Cancer Rehabilitation, a non-profit center that co-led the new study in collaboration with Dixon.
The advantages of the new technology over perometers are cost and convenience. Perimeters are bulky, costly machines, while the LymphaTech system runs on iPhone or iPad and requires only a $400 camera attachment and a paid smartphone app. Both perometers and the app technology simply determine total volume of the arm for swelling diagnosis.
The new app system performed comparably in its accuracy to the perometer in the study.
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Developing LymphaTech has faced a more challenging component – spreading lymphedema awareness – and a less challenging component – arriving at the technology to make the app measurements work.
“In the past 20 years, depth-sensor cameras have become significantly cheaper and better. Video games, self-driving cars, robotics – they have all required better depth sensors, and we took advantage of that by using a commercially available lens attachment,” Dixon said.
The camera attachment creates point clouds, 3D representations of objects, in this case of human arms, which the app uses to calculate the total arm volume. Usually, only one arm is afflicted with lymphedema, allowing clinicians to compare it with the unaffected arm for easier gauging of disease severity.
As with perometers, the LymphaTech technology avoids human error that creeps in when recording arm volume with a tape measure, a currently common method to assess lymphedema.
“The real battle has been to convince a medical market that has not much cared about lymphedema in the past or sought solutions to care,” Dixon said. “Hopefully, the high accessibility of our solution will make it easier to care.”
In a separate study involving the LymphaTech system, a research team traveled to Sri Lanka to measure lymphedema in legs, Dixon said. And in Germany, the technology is catching on with medical garment manufacturers to help them custom-fit compression sleeves to treat lymphedema.
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These researchers and clinicians co-authored the study: Jill Binkley and Lauren Bober from TurningPoint Breast Cancer Rehabilitation, and LymphaTech’s Michael Weiler and Nathan Frank, both of whom graduated from Georgia Tech. Paul Stratford from McMaster University also co-authored the study. Disclosures: B. Dixon owns equity in LymphaTech and may benefit financially from the technology. J.B. Dixon is affiliated with LymphaTech Inc and serves as a scientific advisor. Georgia Institute of Technology has licensed to LymphaTech technology that is related to this study and that is covered by patent applications for which J.B. Dixon is an inventor. In addition, J.B. Dixon is eligible to receive royalties under the license agreement for LymphaTech.
This content is a public domain news release and may also be republished without charge.
Writer & Media Representative: Ben Brumfield (404-272-2780), email: ben.brumfield@comm.gatech.edu
Georgia Institute of Technology
]]>But he’s not like any performer you’ve ever seen. He’s not even human.
Shimon, the marimba-playing robot, has learned some new skills: He sings, he dances a little, he writes lyrics, he can even compose some melodies. Now he’s taking them on the road in a concert tour to support a new album — just like any other musician.
The new album will have eight to 10 songs Shimon wrote with his creator, Georgia Tech Professor Gil Weinberg. It will drop on Spotify later this spring.
“Shimon has been reborn as a singer-songwriter,” Weinberg said. “Now we collaborate between humans and robots to make songs together.”
[Listen to Shimon's first single, "Into Your Mind]
Weinberg will start with a theme — say, space — and Shimon will write lyrics around the theme. Weinberg puts them together and composes melodies to fit them. Shimon can also generate some melodies for Weinberg to use as he puts together a song. Then, with a band of human musicians, Shimon will play the songs and sing.
“I always wanted to write songs, but I just can’t write lyrics. I'm a jazz player,” Weinberg said. “This is the first time that I actually wrote a song, because I had inspiration: I had Shimon writing lyrics for me.”
Weinberg and his students have trained Shimon on datasets of 50,000 lyrics from jazz, prog rock, and hip-hop. Then Shimon uses deep learning, a class of machine learning algorithms, to generate his own words.
“There are lots of systems that use deep learning, but lyrics are different,” said Richard Savery, a third-year Ph.D. student who has been working with Shimon over the past year on his songwriting. “The way semantic meaning moves through lyrics is different. Also, rhyme and rhythm are obviously super important for lyrics, but that isn't as present in other text generators. So, we use deep learning to generate lyrics, but it's also combined with semantic knowledge.”
Savery offered this example of how it might work: “You'll get a word like ‘storm,’ and then it'll generate a whole bunch of related words, like ‘rain.’ It creates a loop of generating lots of material, deciding what's good, and then generating more based on that.”
When Shimon sings these songs, he really does sing, with a unique voice created by collaborators at Pompeu Fabra University in Barcelona. They used machine learning to develop the voice and trained it on hundreds of songs.
Along with his new skills — all developed in Weinberg’s lab — Shimon has some new hardware, too, that changes how he plays and moves on stage. To be clear, he’s still mostly stationary, but he has a mouth, new eyebrows, and new head movements designed to help convey emotion and interact with his bandmates. He also has new “hands,” that have totally changed how he plays the marimba.
“Shimon plays much faster — about 25 to 30 hertz at the maximum — and also much more expressively, playing from a soft dynamic range to a strong dynamic range,” said Ph.D. student Ning Yang, who designed all-new motors and hardware for Shimon. “That also allows [Shimon] to do choreography during the music being played.”
For example, Shimon can count in at the beginning of songs to cue the band, and sometimes he’ll wave his mallets around in time to the music. New brushless DC motors mean he has a much greater range of motion and control of that motion. Yang accomplished that by bringing his engineering knowledge and musical background together to create human-inspired gestures.
“It's actually a very, very good example at Georgia Tech that we can actually combine tech and arts together to create something that's brand new,” Yang said.
He worked closely with fellow Ph.D. student Lisa Zahray, who created a new suite of gestures for the robot — including how he uses those new eyebrows.
“We have to think about his role at each time during the song and what he should be doing,” Zahray said. “We also want to make sure he's interacting with the other musicians around him to give that feel that he's performing with people.”
That partnership with people is key for Weinberg. Teaching Shimon new skills isn’t about replacing musicians, he said.
“We will need musicians, and there will be more musicians that will be able to do more and new music because robots will help them, will generate ideas, will help them broaden the way they think about music and play music,” Weinberg said.
Shimon, Weinberg, and the entire band are building a touring schedule now with the goal of taking their unique blend of robot- and human-created music to more people. Weinberg said he hopes those shows will prove to be more than a novelty act.
“I think we have reached a level where I expect the audience to just enjoy the music for music’s sake,” Weinberg said. “This is music that humans, by themselves, wouldn't have written. I want the audience to think, ‘There's something unique about this song, and I want to go back and listen to it, even if I don't look at the robot.’”
Shimon was originally developed with support from the National Science Foundation Cyber-Human Systems program, grants No. 0713269, and 1017169.
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