Paralyzed By Polio, This British Tea Broker Changed the Course Of Medical History Forever
In December 1958, on a vacation with his wife in Kenya, a 28-year-old British tea broker named Robin Cavendish became suddenly ill. Neither he nor his wife Diana knew it at the time, but Robin's illness would change the course of medical history forever.
Robin was rushed to a nearby hospital in Kenya where the medical staff delivered the crushing news: Robin had contracted polio, and the paralysis creeping up his body was almost certainly permanent. The doctors placed Robin on a ventilator through a tracheotomy in his neck, as the paralysis from his polio infection had rendered him unable to breathe on his own – and going off the average life expectancy at the time, they gave him only three months to live. Robin and Diana (who was pregnant at the time with their first child, Jonathan) flew back to England so he could be admitted to a hospital. They mentally prepared to wait out Robin's final days.
But Robin did something unexpected when he returned to the UK – just one of many things that would astonish doctors over the next several years: He survived. Diana gave birth to Jonathan in February 1959 and continued to visit Robin regularly in the hospital with the baby. Despite doctors warning that he would soon succumb to his illness, Robin kept living.
After a year in the hospital, Diana suggested something radical: She wanted Robin to leave the hospital and live at home in South Oxfordshire for as long as he possibly could, with her as his nurse. At the time, this suggestion was unheard of. People like Robin who depended on machinery to keep them breathing had only ever lived inside hospital walls, as the prevailing belief was that the machinery needed to keep them alive was too complicated for laypeople to operate. But Diana and Robin were up for the challenges – and the risks. Because his ventilator ran on electricity, if the house were to unexpectedly lose power, Diana would either need to restore power quickly or hand-pump air into his lungs to keep him alive.
Robin's wheelchair was not only the first of its kind; it became the model for the respiratory wheelchairs that people still use today.
In an interview as an adult, Jonathan Cavendish reflected on his parents' decision to live outside the hospital on a ventilator: "My father's mantra was quality of life," he explained. "He could have stayed in the hospital, but he didn't think that was as good of a life as he could manage. He would rather be two minutes away from death and living a full life."
After a few years of living at home, however, Robin became tired of being confined to his bed. He longed to sit outside, to visit friends, to travel – but had no way of doing so without his ventilator. So together with his friend Teddy Hall, a professor and engineer at Oxford University, the two collaborated in 1962 to create an entirely new invention: a battery-operated wheelchair prototype with a ventilator built in. With this, Robin could now venture outside the house – and soon the Cavendish family became famous for taking vacations. It was something that, by all accounts, had never been done before by someone who was ventilator-dependent. Robin and Hall also designed a van so that the wheelchair could be plugged in and powered during travel. Jonathan Cavendish later recalled a particular family vacation that nearly ended in disaster when the van broke down outside of Barcelona, Spain:
"My poor old uncle [plugged] my father's chair into the wrong socket," Cavendish later recalled, causing the electricity to short. "There was fire and smoke, and both the van and the chair ground to a halt." Johnathan, who was eight or nine at the time, his mother, and his uncle took turns hand-pumping Robin's ventilator by the roadside for the next thirty-six hours, waiting for Professor Hall to arrive in town and repair the van. Rather than being panicked, the Cavendishes managed to turn the vigil into a party. Townspeople came to greet them, bringing food and music, and a local priest even stopped by to give his blessing.
Robin had become a pioneer, showing the world that a person with severe disabilities could still have mobility, access, and a fuller quality of life than anyone had imagined. His mission, along with Hall's, then became gifting this independence to others like himself. Robin and Hall raised money – first from the Ernest Kleinwort Charitable Trust, and then from the British Department of Health – to fund more ventilator chairs, which were then manufactured by Hall's company, Littlemore Scientific Engineering, and given to fellow patients who wanted to live full lives at home. Robin and Hall used themselves as guinea pigs, testing out different models of the chairs and collaborating with scientists to create other devices for those with disabilities. One invention, called the Possum, allowed paraplegics to control things like the telephone and television set with just a nod of the head. Robin's wheelchair was not only the first of its kind; it became the model for the respiratory wheelchairs that people still use today.
Robin went on to enjoy a long and happy life with his family at their house in South Oxfordshire, surrounded by friends who would later attest to his "down-to-earth" personality, his sense of humor, and his "irresistible" charm. When he died peacefully at his home in 1994 at age 64, he was considered the world's oldest-living person who used a ventilator outside the hospital – breaking yet another barrier for what medical science thought was possible.
Podcast: The Friday Five weekly roundup in health research
The Friday Five covers five stories in health research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Covered in this week's Friday Five:
- Sex differences in cancer
- Promising research on a vaccine for Lyme disease
- Using a super material for brain-like devices
- Measuring your immunity to Covid
- Reducing dementia risk with leisure activities
One day in recent past, scientists at Columbia University’s Creative Machines Lab set up a robotic arm inside a circle of five streaming video cameras and let the robot watch itself move, turn and twist. For about three hours the robot did exactly that—it looked at itself this way and that, like toddlers exploring themselves in a room full of mirrors. By the time the robot stopped, its internal neural network finished learning the relationship between the robot’s motor actions and the volume it occupied in its environment. In other words, the robot built a spatial self-awareness, just like humans do. “We trained its deep neural network to understand how it moved in space,” says Boyuan Chen, one of the scientists who worked on it.
For decades robots have been doing helpful tasks that are too hard, too dangerous, or physically impossible for humans to carry out themselves. Robots are ultimately superior to humans in complex calculations, following rules to a tee and repeating the same steps perfectly. But even the biggest successes for human-robot collaborations—those in manufacturing and automotive industries—still require separating the two for safety reasons. Hardwired for a limited set of tasks, industrial robots don't have the intelligence to know where their robo-parts are in space, how fast they’re moving and when they can endanger a human.
Over the past decade or so, humans have begun to expect more from robots. Engineers have been building smarter versions that can avoid obstacles, follow voice commands, respond to human speech and make simple decisions. Some of them proved invaluable in many natural and man-made disasters like earthquakes, forest fires, nuclear accidents and chemical spills. These disaster recovery robots helped clean up dangerous chemicals, looked for survivors in crumbled buildings, and ventured into radioactive areas to assess damage.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.