Category Archives: Assistive Technology

3-D Printed Models Help Shorten Surgery Time for Common Hip Disorder in Children


3d-printer-hip-surgery-children-cerebral-palsyA team of engineers and pediatric orthopedic surgeons are using 3D printing to help train surgeons and shorten surgeries for the most common hip disorder found in children ages 9 to 16. In a recent study, researchers showed that allowing surgeons to prep on a 3D-printed model of the patient’s hip joint cut by about 25 percent the amount of time needed for surgery when compared to a control group.

The team, which includes bioengineers from the University of California San Diego and physicians from Rady Children’s Hospital, detailed their findings in a recent issue of the Journal of Children’s Orthopedics.

“Being able to practice on these 3D-models is crucial,” said Dr. Vidyadhar Upasani, pediatric orthopedic surgeon at Rady Children’s and UC San Diego and the paper’s senior author.

In this study, Upasani operated on a total of 10 patients. For five of the patients, he planned the surgeries using 3D-printed models. He didn’t use models to plan the other five. In addition, two other surgeons operated on a different group of five patients without using models. In the group where Upasani used 3D-printed models, surgeries were 38-45 minutes shorter compared with the two control groups. These time savings would translate into at least $2700 in savings per surgery, researchers said. By contrast, after the one-time cost of buying a 3D printer for about $2200, physicians can make a model for each surgery for about $10.

The results of the study were so positive that Rady Children’s orthopedics department has acquired its own 3D printer, Upasani said. “I’ve seen how beneficial 3D models are,” he said. “It’s now hard to plan surgeries without them.”

Slipped capital femoral epiphysis is a condition that affects about 11 in 100,000 children in the United States every year.

In this condition, the head of the patient’s femur slips along the bone’s growth plate, deforming it. The main goal of the surgery is to sculpt the femur back into its normal shape and restore hip function. This is difficult because during the surgery, the bone and its growth plate are not directly visible. So the surgeons can’t visualize in 3D how the growth plate is deformed. The condition is associated with obesity and hormonal dysfunction and has become more common as obesity increases among young people.

Traditionally, before the surgery, physicians study X-rays of the surgery site taken from different angles, which they use to plan the bone cuts. During surgery, an X-ray fluoroscopy beam also shines periodically on the surgery site to help guide the physician. These methods are time consuming and expose the child to radiation. In addition, physicians don’t have a physical model to educate patients or practice the surgery beforehand.

How the 3D Printed Models were made

In this study, two UC San Diego students, Jason Caffrey, pursuing a Ph.D. in bioengineering, and Lillia Cherkasskiy, pursuing an M.D. and conducting her Independent Studies Project, teamed up with Upasani, bioengineering professor Robert Sah, and their colleagues. They used commercially available software to process CT scans of the patients’ pelvis and create a computerized model of bone and growth plate for 3D printing. The models allowed surgeons to practice and visualize the surgery before they operated in the real world.

One of the biggest obstacles was getting the right texture for the 3D prints, so that they mimic bone. If the texture was too thick, the model would melt under the surgeon’s tools; if too thin, it would break. The engineers finally settled on a honeycomb-like structure to mimic bones for their models. The printing process itself took four to 10 hours for each print.

The 3D printing effort was led by Caffrey, in the lab of professor Sah at the Jacobs School of Engineering at UC San Diego. The inspiration and foundations for the study came from BENG 1, a hands-on engineering class that Sah, a world leader in tissue engineering and cartilage repair, co-taught in 2015 and Caffrey helped set up. Students 3D printed models of complex ankle bone fractures from CT scans of UC San Diego patients. BENG 1 continues to be a part of the “Experience Engineering” initiative introduced by Albert P. Pisano, dean of the Jacobs School of Engineering at UC San Diego.

Caffrey is now working on his medical degree at the UC San Diego School of Medicine. He is still collaborating with Upasani at Rady Children’s to use 3D printed models to evaluate the best way to surgically correct hip dysplasia, a developmental deformation or misalignment of the hip joint found in infants.

Predicting Epileptic Seizures, Just Like the Weather

Via: Science & Technology Research News

Every morning you wake up and check the weather app on your smartphone, to see if it will rain. If the forecast probability is high enough, let’s say 80 per cent, you decide to bring an umbrella to work.

Now, imagine waking up and not knowing if you will have a seizure that day. You might not be able to go to work at all. This is the uncertainty faced by people with epilepsy every day. An app providing a daily seizure forecast would be life changing – and that is exactly what our team of neuro-engineering researchers at the University of Melbourne is developing.

Led by Professor Mark Cook, our team has recently published a powerful new framework for seizure forecasting. Published in Brain Journal of Neurology, it is the longest forecasting study (where data is used to make reliable predictions about the future) undertaken in humans.

The framework paves the way for us to develop a daily seizure forecast app. We envisage users will be able to enter information about their seizure activity, medication and other lifestyle factors that can be combined with environmental data and brain recordings. This information will then be aggregated to tell the user how likely they are to have a seizure that day.

Depending on personal preference and the acuity of the forecasting model, seizure likelihood can be presented as five risk levels, corresponding to 20 per cent increments of increasing seizure likelihood. After long-term monitoring the forecasts can be personalised, in response to individual seizure patterns.

Providing patients with probabilities, rather than certainties, is a more realistic way to forecast seizures. People with epilepsy can then tailor their lifestyles to minimise their risk. For instance, only exercising when their seizure forecast drops below 20 per cent, or taking additional protective measures once the forecast climbs above 80 per cent.

Previous attempts to develop prediction systems for epilepsy patients have almost always failed due to low volumes of data. To combat this problem, long-term analysis was critical, and so we used the world’s longest continuous database of brain recordings as our dataset. This data were recorded from the surface over the brain during a previous trial for an implantable seizure warning device, which ran three years and involved fifteen patients with drug resistant epilepsy.

The results from this study showed that seizure prediction was feasible; however, the performance was not successful for all patients. We have now used the same data to show seizureforecasting is viable for more people. The framework we applied provides better predictive performance than any other method previously trialled.

Our results come at an exciting time for epilepsy patients. Colleagues have recentlydeveloped an implantable device that can continuously monitor the electrical activity of the brain. Unlike our previous device trial, this new implant records from outside the skull, meaning it is less invasive and can be offered to many more patients. Together, these two studies represent the hardware and software components required to make seizure forecasting a reality for people with epilepsy.

To date, much of the work in the field of seizure prediction has focused on answering a definitive question – will someone have a seizure, or not? But this ignores the subtleties of brain dynamics. For instance, we know that the brain can enter an excited state, where a seizure is more likely, but not certain. Forcing a forecast to take on only two possible outcomes means that these highly excitable states are misdiagnosed, making it difficult to refine or improve predictions.

To reflect the brain’s changing state a more useful question to ask is: “What is the probability a person will have a seizure in the next hour?” Treating seizure likelihood as a continuum, rather than a duality (you will/will not have a seizure), makes forecasts more flexible. Many factors affect the excitability of the brain and, as a result, someone’s risk of seizure changes throughout the day.

This work builds on a study from 2016, published in Brain Journal of Neurology, where we proved that some people have seizures far more often at certain times of the day. We expected seizures to cluster at certain times of day, but were surprised by just how distinctive patterns were between patients. Our next question was: “How can these patterns be used to improve prediction strategies?”

Our latest results show patterns of seizure occurrence can be combined with existing models to provide patients with more useful, flexible forecasts. The hope is that these forecasts will become seamlessly integrated into the lives of people with epilepsy.

Just as the hourly weather report guides decisions and daily activities, a regular seizure forecast will enable people with epilepsy to regain independence.

Electronic Devices Help Non-Verbal Kids Find Their Voice

by Pam Adams, Journal Star/TNS


cerebral palsy non-verbalSelah isn’t ready to work yet.

Carrie Kerr asks, “Do you want a drink?”

Selah grabs a bright pink iPad programmed with more than 3,000 words and matching pictures, including a skunk for a fun kid word like “fart.” Pronouns in yellow-colored boxes, adjectives in blue, nouns in white, verbs in green with different shades for past tense and other conjugations.

Selah Oelschlager is 6 years old and learning to talk.

“It’s hard for her to find the words verbally, but easy for her to find them here,” says Kerr, a speech pathologist, referring to the electronic device she calls Selah’s “talker.”

Once Selah finds the matching symbols and words on her talker, Kerr adds, “it’s easier for her to learn them verbally.”

The scene isn’t quite the breakthrough moment of Helen Keller’s discovery of the sign-language meaning of water from the movie, “The Miracle Worker.” It is a child who is nonverbal and has autism stalling the start of a therapy session, the way young children find excuses to put off bedtime.

They are at Child’s Nature, Kerr’s new pediatric therapy center. The scene may not be high drama, but it is a picture of the higher technology of alternative communication systems. Until about a year ago, Kerr and Selah’s mother, Tiffanie Oelschlager, say the exchange might have ended on less agreeable terms.

“The breakthrough was when she didn’t have to use behavior to communicate,” Kerr says. “Before, she would have gotten up and brought the water to us, or bolted, or screamed because we had no idea what she wanted. Now, she can tell us.”

In private life, Kerr worries about the widespread attachment to electronic devices. “It drives me insane.” Her professional life is just the opposite.

“I want that child so invested in their device that it’s not seen as work,” she says of her therapy sessions for children with alternative communication devices. “It’s where their power is. It should be about their freedom, their ideas, their wants and needs. It’s simply their voice.”

She wants the children she works with to use their devices at home, school, the grocery story, at the park or during meals. They do. For instance, varying types of assisted communication technology are evident at many schools, including Peoria Public Schools, where Selah is in a life skills class at Kellar Primary School.



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