August 2009 Newsletter

By Gordy Slack

There are a lot of illnesses out there. Some of them are simple and straightforward, and others are bafflingly complex. The NIH estimates that of the approximately 20,000 diagnosable medical conditions, there are about 7,000 rare ones that are hard to identify. Even common diseases can present in ways that makes them tricky to diagnose. The National Organization for Rare Disorders says that of patients who were ultimately diagnosed with a rare disease, over 36 percent took more than a year to find a diagnosis. Seventeen percent took more than six years.

Brad Kittredge, a UC Berkeley MBA and Public Health student, has sought an explanation for his own hard-to-diagnose symptoms for four years, a journey that has brought him before nearly 20 doctors around the country. While he learned that his own condition is not too serious, the experience gave Kittredge insight into the challenges and frustrations of hard-to-diagnose patients. Last year, he teamed up with a physician and two computer programmers in search of a way to connect such patients with the doctors who are most likely to successfully diagnose their conditions.

Their new company, ComplexDX, is turning the traditional hunt for a diagnosis on its head. Rather than going from doctor to doctor, patients pay ComplexDX to post their cases to an online database, where participating doctors can examine and solve them.

The idea for ComplexDX first arose in the spring of 2008 during a class taught by Ravi Nemana, CITRIS Executive Director for Services and Health Care. “We realized that there was a huge need going unaddressed,” says Kittredge. “If we could just give doctors the tools and incentive to find patients whose symptom profiles fit their specialties, we could save a lot of suffering, time, and money for thousands of patients.”

At first, Kittredge and his partners called the business Hyoumanity—“to represent the idea of connecting one to many to solve these problems”—and emphasized giving medical specialists a powerful financial incentive to identify and solve tricky cases.  The group won a CITRIS Big Ideas Award for $8,000 in 2009. They have raised additional startup funds and plan to launch the business this fall.

ComplexDX will charge each patient $250-500 to have their case listed in the database and is aiming to pay doctors $1,000 for each correct diagnosis. The team is developing software that will help patients describe their symptoms and develop narratives that will allow the doctors reviewing them to find the telltale signatures of hard-to-diagnose illnesses.

“In addition to financial rewards, many doctors are interested in the sheer intellectual challenge of solving cases and pursuing their Hippocratic mission to help patients,” says Kittredge. “Solving cases also helps doctors build their reputations as experts on certain conditions.”

“These patients have already collected a medical record full of information about their cases,” says Kittredge. “Patients will be able to import and input that record into our system using Google Health, and then we will post it.”

The database will help doctors identify relevant cases and zero in on the ones that fall in their bailiwick. For example, a GI doctor who specializes in infant celiac disease would know that many of these patients lack any gastrointestinal symptoms, a fact leading many pediatricians to miss the diagnosis. This doctor could search our database for symptoms like weight loss, yellowed teeth, and mood changes. Other doctors may have considered Graves disease, growth hormone deficiency, adrenal failure, or diabetes, and may never have come up with celiac because it is usually associated with gastrointestinal distress. The patient may never find this specialist because they do not know to look there and their doctors would need to have had the celiac hypothesis to refer them there. 

After identifying interesting cases on which they can shed light, the ComplexDX-affiliated specialists will then suggest diagnoses and make suggestions about further tests or treatment options. But it will be the patients’ primary care physician who will follow up.

“We are limiting ourselves to providing diagnoses at this point,” says Kittredge, “and steering clear of the treatment business for now.”

For legal reasons, the patients and the ComplexDx doctors who review their cases will each be represented, in the database, only by numbers. Their identities remain private.  “The right diagnostic idea is much more important than the credentials or name of the doctor who has it,” says Kittredge. 

Jonathan Hicks, a computer scientist and Master’s candidate in the UC Berkeley School of Information, is the technical lead of the ComplexDX team. The main challenge, he says, is coordinating the standardized medical information in the patient records with a looser, more qualitative patient narrative.

“The trick is responsibly indexing and organizing it in such a way that a physician can look at it and get the necessary information,” says Hicks. Down the road, the project will also put to use the data they have aggregated about this chronically understudied group of patients.

About half a million people in the U.S. have undiagnosed or misdiagnosed diseases, estimates ComplexDX co-founder Elise Singer, a physician who, like Kittredge, is getting her MBA at Berkeley. That number includes the cumulative incidence of rare diseases as well as complicated and misleading presentations of more common ones, such as multiple sclerosis, Lyme disease, and celiac disease, she says.

“No one has studied these patients as a group before,” says Hicks. “It is hard to find any data on this phenomenon. If we can aggregate thousands of these tough cases that elude diagnosis, there will be a lot of value for basic research and clinical trials,” says Hicks.

As associations between the indexed postings and successful diagnoses accumulate, the system itself may be able to begin to flag likely diagnoses. “It is a learning system,” says Hicks. 

Often an accurate diagnosis can lead to quick and effective treatment, after years of fumbling around. “I know what it is like to have an ailment that evades diagnosis,” says Kittredge, “and if we can give relief to long-suffering patients, we can add real value in terms of medical costs, health outcomes, and quality of life.”

By Gordy Slack

In the 1986 sci-fi classic Aliens, Sigourney Weaver’s character defeats her nemesis with a huge exoskeleton device that she operates from inside with buttons and a joystick. Twenty-two years later, Tony Stark steps inside Iron Man, a much sleeker and more agile version of a wearable robot. How was Iron Man manipulated? Possibly with sensors that could read electrical signals coming from the brain with an EEG-like device embedded in the helmet or implanted into the motor cortex of the brain. Or maybe it was a simpler touch interface that would simply read the contact force applied by the body itself and amplify or convert its motions into movement of the robotic exoskeleton.

All of those approaches are feasible and, in fact, being investigated or implemented by engineers around the world in efforts to explore alternative ways to operate the coming generation of wearable machines.

Jacob Rosen and his colleagues in the UCSC Bionics Lab are taking a different approach. They have developed a robotic arm controlled by the electrical signals sent by the brain through the nerves to contract the muscles – signals known as electromyograph (EMG). These signals can be sensed by electrodes attached to the skin in key locations above the muscles.
There are several advantages to operating robotic devices from EMG signals, Rosen says. It is less invasive and expensive than other “upstream” (closer to the brain) sources, such as electrodes implanted directly in the motor cortex, an approach that also requires a long period of training to generate the appropriate control signals. Nor does interpreting EMGs lead to brain tissue death, as implants do, eventually making the implants obsolete anyway.

EMG also has significant advantages over further “downstream” methods, such as simple touch interfaces. First this approach can teach us a lot about muscle physiology and improve our ability to simulate and predict specific movements. Second, EMG has timing in its favor.

Our neuromuscular  system operates with an inherent time delay, known as the  electromechanical time delay, of somewhere between 50 and 300 milliseconds after a command to move is initiated by the motor cortex in the brain and communicated to the muscle by the nerve in, say, the arm, but before the muscle mechanically contracts.

“That is plenty of time,” Rosen says, “to take the neural signal along with the joint angle and velocity, and predict what the muscle is about to do, and then do the same thing, only amplified, with the robotic exoskeleton.

“It is like walking with a dog,” says Rosen. “If the dog is young and does not know its way, it is going to pull the leash. You would have to apply a force on the dog to direct it. [Like the old, touch interface.] But if the dog knows its way, then the leash can be loose. We are trying to allow a loose-leash situation by developing software that employs algorithms that emulate the muscle physiology, also known as a myoprocessor, to predict what a muscle is going to do before it has begun to do it.”

“Developing the myoprocessor model is difficult,” Rosen says, “partly because the body is so redundant.” There are three different muscles that are responsible for flexing an elbow, for example. This adds another level of complexity that must be incorporated into the algorithms even though the EMG signals are collected from only one muscle out of the three.

While Rosen is modeling the muscles to make his wearable robots more responsive to human intentions, he is also using the robots to help study how human motion works, how it sometimes does not, and how best to repair it when it is not working properly.

“I focus on medical applications, specifically on rehabilitation,” says Rosen, who is working with a physical therapist at UCSF and a neurologist at the San Francisco VA Medical Center on projects that will, he hopes, help stroke victims and victims of other neural damage recover use of their limbs.

Recovering from neurological disorder often requires the rewiring of the brain, making new pathways through undamaged brain territory, says Rosen. And that requires repetition of movement. “Lots of repetition,” he says. “So many repetitions, in fact, that therapists do not always have the time themselves to deliver such treatments.”

The device Rosen has developed, called the EXO-UL7, can stand in for the therapist, allowing what little muscle control persists in a damaged arm to move the whole arm plus a load with the aid of the robot. The EXO-UL7 compensates for gravity and lets the patient concentrate on control alone,” says Rosen. And the patient can do that for however long is optimal for recovery, disregarding the schedule of the physical therapist.

Rosen’s group also plans to combine the robotic suit with virtual reality games to ease the tedium of doing long hours of physical therapy. Their research is currently funded in part by the Telemedicine and Advanced Technology Research Center, a U.S. Army health and medical tech funding organization.

The current prototype is anchored to the wall, but future freestanding ones could be used as robotic prosthetics, allowing users with permanent nerve damage to enjoy a free range of movement and to conduct ordinary tasks. Or it could be used to amplify normal human strength. In fact there are at least two models of exoskeletons, mostly developed with DARPA funding for military use, that do just that now nearing implementation, one made in the Berkeley Robotics and Human Engineering Lab of Homayoon Kazerooni and the other by Sarcos, a private company in Salt Lake City, Utah. Neither one uses EMG.

Rosen’s wearable robot could also be employed for the quick and responsive operation of tools at a distance, a function that is key for the implementation of various kinds of telemedicine, like remote surgery. Or for conducting experiments in hard-to-reach or dangerous environments, such as battlefields or other planets.