APT investigators include Case Western Reserve University faculty members Rahila Ansari, M.D., M.S., an assistant professor of neurology, and Ming-Chun Huang, Ph.D., assistant professor of electrical engineering and computer science. Ansari is also a practicing neurologist at the Louis Stokes Cleveland VA Medical Center. According to Huang, a technology such as the wearable gait laboratory may be a useful tool for clinical evaluation, whether the data is gathered in the hospital or at home. “With the research and the data, we’re gathering,” he said, “we’re trying to accumulate knowledge to see how wearables might trigger effective interventions after an injury.”

An important distinction between many APT projects and most of the wearables available today, said Ansari, is that APT investigators hope to design “closed-loop” systems that take measurements, transmit that data into a control system that analyzes it using algorithms, and activate a mechanism that can take the necessary action. “For example,” she said, “if we’re dealing with a prosthetic limb or a wheelchair, then in order to prevent a breakdown or ulceration, we measure what the forces are, and then we’ll continuously adjust for all those things in real time, so we know we’re preventing problems.”

 

Closing the Loop: Algorithms and Analytics

It’s these next-generation wearable sensing technologies – not devices but systems, of which devices are a component – that signify a transformation in the way doctors and patients interact. Their artificial intelligence will indicate not only what the data say, but what should be done in response.

Josef Stehlik, M.D., MPH, a professor at the University of Utah School of Medicine and cardiologist at the VA Salt Lake City Health Care System, specializes in patients with heart failure, a condition that involves high readmission rates among patients discharged from hospitals. In spring 2018, Stehlik’s research team reported the results from their study of a wearable monitoring system: “a Band-Aid-like patch,” he said, “containing several sensors that detect patients’ physiological parameters.” One hundred veteran patients from four different VA medical facilities wore the monitors, which transmitted data using Bluetooth technology to their smartphones and tablets – which, in turn, uploaded the data to a secure VA server in Sacramento, California.

From there, data from Stehlik’s 100 veteran heart patients, including parameters such as heart rate, respiratory rate, posture, and activity, were fed into an algorithm that compared them to a previously established baseline for each patient. “This predictive algorithm was very accurate in identifying which patients were likely to get in trouble with heart failure exacerbation,” said Stehlik. For patients whose data were heading into dangerous territory, the analytics triggered an alarm that notified the research team. “We’ve also shown that this alarm would come approximately seven to 12 days before the readmission would happen,” Stehlik said. “So presumably, there would be sufficient time to do an intervention: contact the patient, change medications to treat the patient before the exacerbation progresses, on time to prevent a readmission.”

Now that his team has established the ability of the analytics to predict exacerbation for heart patients, Stehlik hopes to show how the data can be integrated usefully into cardiologists’ clinical workflow. “As you can imagine, a lot of clinicians have been bombarded by lots of different data. It’s not just important to make data available – it needs to be processed into an output so that clinicians can respond to it and provide the benefit of that information to the patient. That’s where I think a lot of research is necessary.” He hopes to conduct a trial among VA patients in which he can measure the clinical efficacy of the wearable monitoring system: whether the device paired with a predictive algorithm can reduce readmissions or shorten hospital stays for heart patients.

It’s these next-generation wearable sensing technologies – not devices but systems, of which devices are a component – that signify a transformation in the way doctors and patients interact.

At the Daroff-Dell’Osso Ocular Motility Laboratory at the Cleveland VA Medical Center, neuroscientist Aasef Shaikh, M.D., Ph.D., a professor at Case Western Reserve University, is examining how sensors can be used to aid in diagnosing and differentiating among different tremor disorders that often present similarly. In the laboratory, Shaikh and his colleagues fit patients with sensors – wearable magnetometers with gyroscopes capable of taking fine 3-D positional readings. Just as with Stehlik’s heart patients, this data has been fed into specifically formulated algorithms to distinguish one type of tremor – for example, cervical dystonia, essential tremor, or Parkinsonian tremor – from another.

These assessments currently happen in Shaikh’s lab, but he and his team are developing mobile versions of the sensor that will be able to transmit data wirelessly. “The key thing here,” he said, “is that now we can use wearable technology and machine learning, artificial intelligence, to analyze the output of those wearables to provide better diagnostics – and better care – for the patient.”

Shaikh’s ambition is to develop a closed-loop system that may become directly involved in providing care for tremors. Deep brain stimulation (DBS), a method of dampening muscle-activating signals from the thalamus, is achieved among tremor patients through surgery, in which electrodes are implanted into the thalamus and connected to a generator – Shaikh describes it as a “pacemaker for the brain” – that can block tremor-inducing impulses. With a wearable sensor that can detect the tremor, and an algorithm that can distinguish the tremor type, the system would be capable of applying DBS to relieve the patient’s symptoms.

 

The Future: The Internet of Wearable Things, Big Data, and Doctors

Closed-loop systems with wearable technology may be the key to offering real-time interventions for patients with burdensome conditions that require constant vigilance. Huang, Ansari, and their colleagues at the APT Center, for example, are looking to close the loop for patients at constant risk of having their skin integrity compromised: patients who wear prosthetics or use wheelchairs. If Shaikh can close the loop for tremor patients, he can offer them a degree of relief they’ve never known.