In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Dave Arnold retired in his 60s and began spending time volunteering in local schools. But then he started misplacing items, forgetting appointments and losing his sense of direction. Eventually he was diagnosed with early stage Alzheimer’s.
“Hearing the diagnosis made me very emotional and tearful,” he said. “I immediately thought of all my mom had experienced.” His mother suffered with the condition for years before passing away. Over the last year, Arnold has worked for the Alzheimer’s Association as one of its early stage advisors, sharing his insights to help others in the initial stages of the disease.
Arnold was diagnosed sooner than many others. It's important to find out early, when interventions can make the most difference. One promising avenue is looking at how people talk. Research has shown that Alzheimer’s affects a part of the brain that controls speech, resulting in small changes before people show other signs of the disease.
Now, Canary Speech, a company based in Utah, is using AI to examine elements like the pitch of a person’s voice and their pauses. In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Developing the AI model
Canary Speech’s CEO, Henry O’Connell, met cofounder Jeff Adams about 40 years before they started the company. Back when they first crossed paths, they were both living in Bethesda, Maryland; O’Connell was a research fellow at the National Institutes of Health studying rare neurological diseases, while Adams was working to decode spy messages. Later on, Adams would specialize in building mathematical models to analyze speech and sound as a team leader in developing Amazon's Alexa.
It wasn't until 2015 that they decided to make use of the fit between their backgrounds. ““We established Canary Speech in 2017 to build a product that could be used in multiple languages in clinical environments,” O'Connell says.
The need is growing. About 55 million people worldwide currently live with Alzheimer’s, a number that is expected to double by 2050. Some scientists think the disease results from a buildup of plaque in the brain. It causes mild memory loss at first and, over time, this issue get worse while other symptoms, such as disorientation and hallucinations, can develop. Treatment to manage the disease is more effective in the earlier stages, but detection is difficult since mild symptoms are often attributed to the normal aging process.
O’Connell and Adams specialize in the complex ways that Alzheimer’s effects how people speak. Using AI, their mathematical model analyzes 15 million data points every minute, focusing on certain features of speech such as pitch, pauses and elongation of words. It also pays attention to how the vibrations of vocal cords change in different stages of the disease.
To create their model, the team used a type of machine learning called deep neural nets, which looks at multiple layers of data - in this case, the multiple features of a person’s speech patterns.
“Deep neural nets allow us to look at much, much larger data sets built out of millions of elements,” O’Connell explained. “Through machine learning and AI, we’ve identified features that are very sensitive to an Alzheimer’s patient versus [people without the disease] and also very sensitive to mild cognitive impairment, early stage and moderate Alzheimer's.” Based on their learnings, Canary is able to classify the disease stage very quickly, O’Connell said.
“When we’re listening to sublanguage elements, we’re really analyzing the direct result of changes in the brain in the physical body,” O’Connell said. “The brain controls your vocal cords: how fast they vibrate, the expansion of them, the contraction.” These factors, along with where people put their tongues when talking, function subconsciously and result in subtle changes in the sounds of speech.
Further testing is needed
In an initial trial, Canary analyzed speech recordings from phone calls to a large U.S. health insurer. They looked at the audio recordings of 651 policyholders who had early stage Alzheimer’s and 1018 who did not have the condition, aiming for a representative sample of age, gender and race. They used this data to create their first diagnostic model and found that it was 96 percent accurate in identifying Alzheimer’s.
Christian Herff, an assistant professor of neuroscience at Maastricht University in the Netherlands, praised this approach while adding that further testing is needed to assess its effectiveness.
“I think the general idea of identifying increased risk for cognitive impairment based on speech characteristics is very feasible, particularly when change in a user’s voice is monitored, for example, by recording speech every year,” Herff said. He noted that this can only be a first indication, not a full diagnosis. The accuracy still needs to be validated in studies that follows individuals over a period of time, he said.
Toby Walsh, a professor of artificial intelligence at the University of New South Wales, also thinks Canary’s tool has potential but highlights that Canary could diagnose some people who don’t really have the disease. “This is an interesting and promising application of AI,” he said, “but these tools need to be used carefully. Imagine the anxiety of being misdiagnosed with Alzheimer’s.”
As with many other AI tools, privacy and bias are additional issues to monitor closely, Walsh said.
Other languages
A related issue is that not everyone is fluent in English. Mahnaz Arvaneh, a senior lecturer in automatic control and systems engineering at the University of Sheffield, said this could be a blind spot.
“The system may not be very accurate for those who have English as their second language as their speaking patterns would be different, and any issue might be because of language deficiency rather than cognitive issues,” Arvaneh said.
The team is expanding to multiple languages starting with Japanese and Spanish. The elements of the model that make up the algorithm are very similar, but they need to be validated and retrained in a different language, which will require access to more data.
Recently, Canary analyzed the phone calls of 233 Japanese patients who had mild cognitive impairment and 704 healthy people. Using an English model they were able to identify the Japanese patients who had mild cognitive impairment with 78 percent accuracy. They also developed a model in Japanese that was 45 percent accurate, and they’re continuing to train it with more data.
The future
Canary is using their model to look at other diseases like Huntington’s and Parkinson’s. They’re also collaborating with pharmaceuticals to validate potential therapies for Alzheimer’s. By looking at speech patterns over time, Canary can get an indication of how well these drugs are working.
Dave Arnold and his wife dance at his nephew’s wedding in Rochester, New York, ten years ago, before his Alzheimer's diagnosis.
Dave Arnold
Ultimately, they want to integrate their tool into everyday life. “We want it to be used in a smartphone, or a teleconference call so that individuals could be examined in their home,” O’Connell said. “We could follow them over time and work with clinical teams and hospitals to improve the evaluation of patients and contribute towards an accurate diagnosis.”
Arnold, the patient with early stage Alzheimer’s, sees great promise. “The process of getting a diagnosis is already filled with so much anxiety,” he said. “Anything that can be done to make it easier and less stressful would be a good thing, as long as it’s proven accurate.”
In the U.S., hospitals generate an estimated 6,000 tons of waste per day. A few clinics are leading the way in transitioning to clean energy sources.
She decided to research alternatives for plastic in the medical sector and learned that cups could be reused and easily disinfected. All dentists routinely disinfect their tools anyway and, Stroetzel reasoned, it wouldn’t be too hard to extend that practice to cups.
It's a good example for how often plastic is used unnecessarily in medical practice, she says. The health care sector is the fifth biggest source of pollution and trash in industrialized countries. In the U.S., hospitals generate an estimated 6,000 tons of waste per day, including an average of 400 grams of plastic per patient per day, and this sector produces 8.5 percent of greenhouse gas emissions nationwide.
“Sustainable alternatives exist,” Stroetzel says, “but you have to painstakingly look for them; they are often not offered by the big manufacturers, and all of this takes way too much time [that] medical staff simply does not have during their hectic days.”
When Stroetzel spoke with medical staff in Germany, she found they were often frustrated by all of this waste, especially as they took care to avoid single-use plastic at home. Doctors in other countries share this frustration. In a recent poll, nine out of ten doctors in Germany said they’re aware of the urgency to find sustainable solutions in the health industry but don’t know how to achieve this goal.
After a year of researching more sustainable alternatives, Stroetzel founded a social enterprise startup called POP, short for Practice Without Plastic, together with IT expert Nicolai Niethe, to offer well-researched solutions. “Sustainable alternatives exist,” she says, “but you have to painstakingly look for them; they are often not offered by the big manufacturers, and all of this takes way too much time [that] medical staff simply does not have during their hectic days.”
In addition to reusable dentist cups, other good options for the heath care sector include washable N95 face masks and gloves made from nitrile, which waste less water and energy in their production. But Stroetzel admits that truly making a medical facility more sustainable is a complex task. “This includes negotiating with manufacturers who often package medical materials in double and triple layers of extra plastic.”
While initiatives such as Stroetzel’s provide much needed information, other experts reason that a wholesale rethinking of healthcare is needed. Voluntary action won’t be enough, and government should set the right example. Kari Nadeau, a Stanford physician who has spent 30 years researching the effects of environmental pollution on the immune system, and Kenneth Kizer, the former undersecretary for health in the U.S. Department of Veterans Affairs, wrote in JAMA last year that the medical industry and federal agencies that provide health care should be required to measure and make public their carbon footprints. “Government health systems do not disclose these data (and very rarely do private health care organizations), unlike more than 90% of the Standard & Poor’s top 500 companies and many nongovernment entities," they explained. "This could constitute a substantial step toward better equipping health professionals to confront climate change and other planetary health problems.”
Compared to the U.K., the U.S. healthcare industry lags behind in terms of measuring and managing its carbon footprint, and hospitals are the second highest energy user of any sector in the U.S.
Kizer and Nadeau look to the U.K. National Health Service (NHS), which created a Sustainable Development Unit in 2008 and began that year to conduct assessments of the NHS’s carbon footprint. The NHS also identified its biggest culprits: Of the 2019 footprint, with emissions totaling 25 megatons of carbon dioxide equivalent, 62 percent came from the supply chain, 24 percent from the direct delivery of care, 10 percent from staff commute and patient and visitor travel, and 4 percent from private health and care services commissioned by the NHS. From 1990 to 2019, the NHS has reduced its emission of carbon dioxide equivalents by 26 percent, mostly due to the switch to renewable energy for heat and power. Meanwhile, the NHS has encouraged health clinics in the U.K. to install wind generators or photovoltaics that convert light to electricity -- relatively quick ways to decarbonize buildings in the health sector.
Compared to the U.K., the U.S. healthcare industry lags behind in terms of measuring and managing its carbon footprint, and hospitals are the second highest energy user of any sector in the U.S. “We are already seeing patients with symptoms from climate change, such as worsened respiratory symptoms from increased wildfires and poor air quality in California,” write Thomas B. Newman, a pediatrist at the University of California, San Francisco, and UCSF clinical research coordinator Daisy Valdivieso. “Because of the enormous health threat posed by climate change, health professionals should mobilize support for climate mitigation and adaptation efforts.” They believe “the most direct place to start is to approach the low-lying fruit: reducing healthcare waste and overuse.”
In addition to resulting in waste, the plastic in hospitals ultimately harms patients, who may be even more vulnerable to the effects due to their health conditions. Microplastics have been detected in most humans, and on average, a human ingests five grams of microplastic per week. Newman and Valdivieso refer to the American Board of Internal Medicine's Choosing Wisely program as one of many initiatives that identify and publicize options for “safely doing less” as a strategy to reduce unnecessary healthcare practices, and in turn, reduce cost, resource use, and ultimately reduce medical harm.
A few U.S. clinics are pioneers in transitioning to clean energy sources. In Wisconsin, the nonprofit Gundersen Health network became the first hospital to cut its reliance on petroleum by switching to locally produced green energy in 2015, and it saved $1.2 million per year in the process. Kaiser Permanente eliminated its 800,000 ton carbon footprint through energy efficiency and purchasing carbon offsets, reaching a balance between carbon emissions and removing carbon from the atmosphere in 2020, the first U.S. health system to do so.
Cleveland Clinic has pledged to join Kaiser in becoming carbon neutral by 2027. Realizing that 80 percent of its 2008 carbon emissions came from electricity consumption, the Clinic started switching to renewable energy and installing solar panels, and it has invested in researching recyclable products and packaging. The Clinic’s sustainability report outlines several strategies for producing less waste, such as reusing cases for sterilizing instruments, cutting back on materials that can’t be recycled, and putting pressure on vendors to reduce product packaging.
The Charité Berlin, Europe’s biggest university hospital, has also announced its goal to become carbon neutral. Its sustainability managers have begun to identify the biggest carbon culprits in its operations. “We’ve already reduced CO2 emissions by 21 percent since 2016,” says Simon Batt-Nauerz, the director of infrastructure and sustainability.
The hospital still emits 100,000 tons of CO2 every year, as much as a city with 10,000 residents, but it’s making progress through ride share and bicycle programs for its staff of 20,000 employees, who can get their bikes repaired for free in one of the Charité-operated bike workshops. Another program targets doctors’ and nurses’ scrubs, which cause more than 200 tons of CO2 during manufacturing and cleaning. The staff is currently testing lighter, more sustainable scrubs made from recycled cellulose that is grown regionally and requires 80 percent less land use and 30 percent less water.
The Charité hospital in Berlin still emits 100,000 tons of CO2 every year, but it’s making progress through ride share and bicycle programs for its staff of 20,000 employees.
Wiebke Peitz | Specific to Charité
Anesthesiologist Susanne Koch spearheads sustainability efforts in anesthesiology at the Charité. She says that up to a third of hospital waste comes from surgery rooms. To reduce medical waste, she recommends what she calls the 5 Rs: Reduce, Reuse, Recycle, Rethink, Research. “In medicine, people don’t question the use of plastic because of safety concerns,” she says. “Nobody wants to be sued because something is reused. However, it is possible to reduce plastic and other materials safely.”
For instance, she says, typical surgery kits are single-use and contain more supplies than are actually needed, and the entire kit is routinely thrown out after the surgery. “Up to 20 percent of materials in a surgery room aren’t used but will be discarded,” Koch says. One solution could be smaller kits, she explains, and another would be to recycle the plastic. Another example is breathing tubes. “When they became scarce during the pandemic, studies showed that they can be used seven days instead of 24 hours without increased bacteria load when we change the filters regularly,” Koch says, and wonders, “What else can we reuse?”
In the Netherlands, TU Delft researchers Tim Horeman and Bart van Straten designed a method to melt down the blue polypropylene wrapping paper that keeps medical instruments sterile, so that the material can be turned it into new medical devices. Currently, more than a million kilos of the blue paper are used in Dutch hospitals every year. A growing number of Dutch hospitals are adopting this approach.
Another common practice that’s ripe for improvement is the use of a certain plastic, called PVC, in hospital equipment such as blood bags, tubes and masks. Because of its toxic components, PVC is almost never recycled in the U.S., but University of Michigan researchers Danielle Fagnani and Anne McNeil have discovered a chemical process that can break it down into material that could be incorporated back into production. This could be a step toward a circular economy “that accounts for resource inputs and emissions throughout a product’s life cycle, including extraction of raw materials, manufacturing, transport, use and reuse, and disposal,” as medical experts have proposed. “It’s a failure of humanity to have created these amazing materials which have improved our lives in many ways, but at the same time to be so shortsighted that we didn’t think about what to do with the waste,” McNeil said in a press release.
Susanne Koch puts it more succinctly: “What’s the point if we save patients while killing the planet?”