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Detecting patients’ pain levels via their brain signals
The system could help with diagnosing and treating patients that cannot communicate.
Researchers from MIT and elsewhere have developed a system that measures a patient's pain level by analyzing brain activity from a portable neuroimaging device.
The system could help doctors diagnose and treat pain in unconscious and noncommunicative patients, which could reduce the risk of chronic pain that can occur after surgery.
Pain management is a surprisingly challenging, complex balancing act. Overtreating pain, for example, runs the risk of addicting patients to pain medication. Undertreating pain, on the other hand, may lead to long-term chronic pain and other complications. Today, doctors generally gauge pain levels according to their patients' own reports of how they're feeling. But what about patients who can't communicate how they're feeling effectively — or at all — such as children, elderly patients with dementia, or those undergoing surgery?
In a paper presented at the International Conference on Affective Computing and Intelligent Interaction, the researchers describe a method to quantify pain in patients. To do so, they leverage an emerging neuroimaging technique called functional near infrared spectroscopy (fNIRS), in which sensors placed around the head measure oxygenated hemoglobin concentrations that indicate neuron activity.
For their work, the researchers use only a few fNIRS sensors on a patient's forehead to measure activity in the prefrontal cortex, which plays a major role in pain processing. Using the measured brain signals, the researchers developed personalized machine-learning models to detect patterns of oxygenated hemoglobin levels associated with pain responses. When the sensors are in place, the models can detect whether a patient is experiencing pain with around 87 percent accuracy.
"The way we measure pain hasn't changed over the years," says Daniel Lopez-Martinez, a PhD student in the Harvard-MIT Program in Health Sciences and Technology and a researcher at the MIT Media Lab. "If we don't have metrics for how much pain someone experiences, treating pain and running clinical trials becomes challenging. The motivation is to quantify pain in an objective manner that doesn't require the cooperation of the patient, such as when a patient is unconscious during surgery."
Traditionally, surgery patients receive anesthesia and medication based on their age, weight, previous diseases, and other factors. If they don't move and their heart rate remains stable, they're considered fine. But the brain may still be processing pain signals while they're unconscious, which can lead to increased postoperative pain and long-term chronic pain. The researchers' system could provide surgeons with real-time information about an unconscious patient's pain levels, so they can adjust anesthesia and medication dosages accordingly to stop those pain signals.
Joining Lopez-Martinez on the paper are: Ke Peng of Harvard Medical School, Boston Children's Hospital, and the CHUM Research Centre in Montreal; Arielle Lee and David Borsook, both of Harvard Medical School, Boston Children's Hospital, and Massachusetts General Hospital; and Rosalind Picard, a professor of media arts and sciences and director of affective computing research in the Media Lab.
Focusing on the forehead
In their work, the researchers adapted the fNIRS system and developed new machine-learning techniques to make the system more accurate and practical for clinical use.
To use fNIRS, sensors are traditionally placed all around a patient's head. Different wavelengths of near-infrared light shine through the skull and into the brain. Oxygenated and deoxygenated hemoglobin absorb the wavelengths differently, altering their signals slightly. When the infrared signals reflect back to the sensors, signal-processing techniques use the altered signals to calculate how much of each hemoglobin type is present in different regions of the brain.
When a patient is hurt, regions of the brain associated with pain will see a sharp rise in oxygenated hemoglobin and decreases in deoxygenated hemoglobin, and these changes can be detected through fNIRS monitoring. But traditional fNIRS systems place sensors all around the patient's head. This can take a long time to set up, and it can be difficult for patients who must lie down. It also isn't really feasible for patients undergoing surgery.
Therefore, the researchers adapted the fNIRS system to specifically measure signals only from the prefrontal cortex. While pain processing involves outputs of information from multiple regions of the brain, studies have shown the prefrontal cortex integrates all that information. This means they need to place sensors only over the forehead.
Another problem with traditional fNIRS systems is they capture some signals from the skull and skin that contribute to noise. To fix that, the researchers installed additional sensors to capture and filter out those signals.
An emerging neuroimaging technique called functional near infrared spectroscopy (fNIRS) could help detect pain.
Pat Greenhouse/The Boston Globe via Getty Images
Personalized pain modeling
On the machine-learning side, the researchers trained and tested a model on a labeled pain-processing dataset they collected from 43 male participants. (Next they plan to collect a lot more data from diverse patient populations, including female patients — both during surgery and while conscious, and at a range of pain intensities — in order to better evaluate the accuracy of the system.)
Each participant wore the researchers' fNIRS device and was randomly exposed to an innocuous sensation and then about a dozen shocks to their thumb at two different pain intensities, measured on a scale of 1-10: a low level (about a 3/10) or high level (about 7/10). Those two intensities were determined with pretests: The participants self-reported the low level as being only strongly aware of the shock without pain, and the high level as the maximum pain they could tolerate.
In training, the model extracted dozens of features from the signals related to how much oxygenated and deoxygenated hemoglobin was present, as well as how quickly the oxygenated hemoglobin levels rose. Those two metrics — quantity and speed — give a clearer picture of a patient's experience of pain at the different intensities.
Importantly, the model also automatically generates "personalized" submodels that extract high-resolution features from individual patient subpopulations. Traditionally, in machine learning, one model learns classifications — "pain" or "no pain" — based on average responses of the entire patient population. But that generalized approach can reduce accuracy, especially with diverse patient populations.
The researchers' model instead trains on the entire population but simultaneously identifies shared characteristics among subpopulations within the larger dataset. For example, pain responses to the two intensities may differ between young and old patients, or depending on gender. This generates learned submodels that break off and learn, in parallel, patterns of their patient subpopulations. At the same time, however, they're all still sharing information and learning patterns shared across the entire population. In short, they're simultaneously leveraging fine-grained personalized information and population-level information to train better.
The personalized models and a traditional model were evaluated in classifying pain or no-pain in a random hold-out set of participant brain signals from the dataset, where the self-reported pain scores were known for each participant. The personalized models outperformed the traditional model by about 20 percent, reaching about 87 percent accuracy.
"Because we are able to detect pain with this high accuracy, using only a few sensors on the forehead, we have a solid basis for bringing this technology to a real-world clinical setting," Lopez-Martinez says.
- Gene mutation causes woman to feel no pain, anxiety - Big Think ›
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How would the ability to genetically customize children change society? Sci-fi author Eugene Clark explores the future on our horizon in Volume I of the "Genetic Pressure" series.
- A new sci-fi book series called "Genetic Pressure" explores the scientific and moral implications of a world with a burgeoning designer baby industry.
- It's currently illegal to implant genetically edited human embryos in most nations, but designer babies may someday become widespread.
- While gene-editing technology could help humans eliminate genetic diseases, some in the scientific community fear it may also usher in a new era of eugenics.
Tribalism and discrimination<p>One question the "Genetic Pressure" series explores: What would tribalism and discrimination look like in a world with designer babies? As designer babies grow up, they could be noticeably different from other people, potentially being smarter, more attractive and healthier. This could breed resentment between the groups—as it does in the series.</p><p>"[Designer babies] slowly find that 'everyone else,' and even their own parents, becomes less and less tolerable," author Eugene Clark told Big Think. "Meanwhile, everyone else slowly feels threatened by the designer babies."</p><p>For example, one character in the series who was born a designer baby faces discrimination and harassment from "normal people"—they call her "soulless" and say she was "made in a factory," a "consumer product." </p><p>Would such divisions emerge in the real world? The answer may depend on who's able to afford designer baby services. If it's only the ultra-wealthy, then it's easy to imagine how being a designer baby could be seen by society as a kind of hyper-privilege, which designer babies would have to reckon with. </p><p>Even if people from all socioeconomic backgrounds can someday afford designer babies, people born designer babies may struggle with tough existential questions: Can they ever take full credit for things they achieve, or were they born with an unfair advantage? To what extent should they spend their lives helping the less fortunate? </p>
Sexuality dilemmas<p>Sexuality presents another set of thorny questions. If a designer baby industry someday allows people to optimize humans for attractiveness, designer babies could grow up to find themselves surrounded by ultra-attractive people. That may not sound like a big problem.</p><p>But consider that, if designer babies someday become the standard way to have children, there'd necessarily be a years-long gap in which only some people are having designer babies. Meanwhile, the rest of society would be having children the old-fashioned way. So, in terms of attractiveness, society could see increasingly apparent disparities in physical appearances between the two groups. "Normal people" could begin to seem increasingly ugly.</p><p>But ultra-attractive people who were born designer babies could face problems, too. One could be the loss of body image. </p><p>When designer babies grow up in the "Genetic Pressure" series, men look like all the other men, and women look like all the other women. This homogeneity of physical appearance occurs because parents of designer babies start following trends, all choosing similar traits for their children: tall, athletic build, olive skin, etc. </p><p>Sure, facial traits remain relatively unique, but everyone's more or less equally attractive. And this causes strange changes to sexual preferences.</p><p>"In a society of sexual equals, they start looking for other differentiators," he said, noting that violet-colored eyes become a rare trait that genetically engineered humans find especially attractive in the series.</p><p>But what about sexual relationships between genetically engineered humans and "normal" people? In the "Genetic Pressure" series, many "normal" people want to have kids with (or at least have sex with) genetically engineered humans. But a minority of engineered humans oppose breeding with "normal" people, and this leads to an ideology that considers engineered humans to be racially supreme. </p>
Regulating designer babies<p>On a policy level, there are many open questions about how governments might legislate a world with designer babies. But it's not totally new territory, considering the West's dark history of eugenics experiments.</p><p>In the 20th century, the U.S. conducted multiple eugenics programs, including immigration restrictions based on genetic inferiority and forced sterilizations. In 1927, for example, the Supreme Court ruled that forcibly sterilizing the mentally handicapped didn't violate the Constitution. Supreme Court Justice Oliver Wendall Holmes wrote, "… three generations of imbeciles are enough." </p><p>After the Holocaust, eugenics programs became increasingly taboo and regulated in the U.S. (though some states continued forced sterilizations <a href="https://www.uvm.edu/~lkaelber/eugenics/" target="_blank">into the 1970s</a>). In recent years, some policymakers and scientists have expressed concerns about how gene-editing technologies could reanimate the eugenics nightmares of the 20th century. </p><p>Currently, the U.S. doesn't explicitly ban human germline genetic editing on the federal level, but a combination of laws effectively render it <a href="https://academic.oup.com/jlb/advance-article/doi/10.1093/jlb/lsaa006/5841599#204481018" target="_blank" rel="noopener noreferrer">illegal to implant a genetically modified embryo</a>. Part of the reason is that scientists still aren't sure of the unintended consequences of new gene-editing technologies. </p><p>But there are also concerns that these technologies could usher in a new era of eugenics. After all, the function of a designer baby industry, like the one in the "Genetic Pressure" series, wouldn't necessarily be limited to eliminating genetic diseases; it could also work to increase the occurrence of "desirable" traits. </p><p>If the industry did that, it'd effectively signal that the <em>opposites of those traits are undesirable. </em>As the International Bioethics Committee <a href="https://academic.oup.com/jlb/advance-article/doi/10.1093/jlb/lsaa006/5841599#204481018" target="_blank" rel="noopener noreferrer">wrote</a>, this would "jeopardize the inherent and therefore equal dignity of all human beings and renew eugenics, disguised as the fulfillment of the wish for a better, improved life."</p><p><em>"Genetic Pressure Volume I: Baby Steps"</em><em> by Eugene Clark is <a href="http://bigth.ink/38VhJn3" target="_blank">available now.</a></em></p>
Meteorologists propose a stunning new explanation for the mysterious events in the Bermuda Triangle.
One of life's great mysteries, the Bermuda Triangle might have finally found an explanation. This strange region, that lies in the North Atlantic Ocean between Bermuda, Miami and San Juan, Puerto Rico, has been the presumed cause of dozens and dozens of mind-boggling disappearances of ships and planes.
A unique exoplanet without clouds or haze was found by astrophysicists from Harvard and Smithsonian.
- Astronomers from Harvard and Smithsonian find a very rare "hot Jupiter" exoplanet without clouds or haze.
- Such planets were formed differently from others and offer unique research opportunities.
- Only one other such exoplanet was found previously.
Munazza Alam – a graduate student at the Center for Astrophysics | Harvard & Smithsonian.
Credit: Jackie Faherty
Jupiter's Colorful Cloud Bands Studied by Spacecraft<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="8a72dfe5b407b584cf867852c36211dc"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/GzUzCesfVuw?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>
Scientists discover burrows of giant predator worms that lived on the seafloor 20 million years ago.
- Scientists in Taiwan find the lair of giant predator worms that inhabited the seafloor 20 million years ago.
- The worm is possibly related to the modern bobbit worm (Eunice aphroditois).
- The creatures can reach several meters in length and famously ambush their pray.
A three-dimensional model of the feeding behavior of Bobbit worms and the proposed formation of Pennichnus formosae.
Credit: Scientific Reports
Beware the Bobbit Worm!<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="1f9918e77851242c91382369581d3aac"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/_As1pHhyDHY?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>
The idea behind the law was simple: make it more difficult for online sex traffickers to find victims.