Relief for Asthmatics: New Wearable Under Development
Algorithm Interprets Breathing Difficulties to Aid in Medical Care
August 19, 2015
Hamid Krim, Matt Shipman
Researchers from North Carolina State University have developed an efficient algorithm that can interpret the wheezing of patients with breathing difficulties to give medical providers information about what’s happening in the lungs. The research is part of a larger, ongoing project to develop wearable smart medical sensors for monitoring, collecting and interpreting personal health data.
The work was done by Saba Emrani and Hamid Krim, researchers in the National Science Foundation Nanosystems Engineering Research Center for Advanced Self-Powered Systems of Integrated Sensors and Technologies, or ASSIST Center, which is based at NC State.
“Researchers at ASSIST have developed wearable sensors that are powered by a patient’s body heat and can monitor the sound of a patient’s breathing,” says Krim, a professor of electrical and computer engineering at NC State and senior author of a paper on the work. “Now we’ve developed an algorithm that can assess the onset time, pitch and magnitude (or volume) of wheezing sounds to give healthcare professionals information about the condition of the lungs. This information, in turn, can be used to help doctors make more informed decisions about diagnosis and treatment.”
Wheezing sounds vary depending on where the problem is in the lungs and on the severity of the problem, Krim explains. The algorithm accounts for these differences to tell doctors exactly what is going on. “The algorithm is effective regardless of the physical size of the patient,” Krim says, “and is able to handle the variability and complexity associated with breathing patterns.”
Because the algorithm was developed to work in concert with wearable technology, the goal is for it to ultimately be used to continuously assess the sound of a patient’s breathing over time. This would make it possible for doctors to monitor breathing under a patient’s real-world, day-to-day conditions.
Here’s how the system is eventually supposed to work: sensors that monitor breathing transmit information to a smart device, such as a smartphone. That data is then run through the algorithm. If the algorithm finds that there is a breathing problem, the smart device could then notify the patient and his or her medical provider. Moreover, due to the low computational cost of the algorithm, the long-term goal is for it to be implemented on the sensor device itself. The sensor would then transmit an alert to the smart device only if it detects a problem.
But while researchers have come a long way, they still have challenges to address.
“We have the sensors and we have the algorithm – and we know that they work – but we haven’t yet integrated them into a smart device. That’s next,” Krim says. “We’re currently weighing whether to modify the sensors so that they can run the algorithm and transmit only if there is a problem, or to maintain the current approach of having the sensor transmit all of the data so that the smart device runs the algorithm. ASSIST is also working to develop sensors that can operate wirelessly, so that the sensors don’t need to be physically connected to the smart device.”
Krim also notes that it’s difficult to assess the cost of the relevant hardware at this point, since it’s still under development.
The paper, “Spectral Estimation in Highly Transient Data,” will be presented at the 2015 European Signal Processing Conference being held in Nice, France, Aug. 31 to Sept. 4. Lead author of the paper is Emrani, a Ph.D. student at NC State. The work was supported by the National Science Foundation through the ASSIST Engineering Research Center at NC State, under grant number EEC-1160483.
Note to Editors: The study abstract follows.
“Spectral Estimation in Highly Transient Data”
Authors: Sabra Emrani and Hamid Krim, North Carolina State University
Presented: 2015 European Signal Processing Conference, Nice, France, Aug. 31 to Sept. 4.
Abstract: We propose a new framework for estimating different frequencies in piece-wise periodic signals with time varying amplitude and phase. Through a 3-dimensional delay embedding of the introduced model, we construct a union of intersecting planes where each plane corresponds to one frequency. The equations of each of these planes only depend on the associated frequency, and are used to calculate the tone in each segment. A sparse subspace clustering technique is utilized to find the segmentation of the data, and the points in each cluster are used to compute the normal vectors. In the presence of white Gaussian noise, principal component analysis is used to robustly perform this computation. Experimental results demonstrate the effectiveness of the proposed framework.
From MindThe Horizon:
Diagnosing Breathing Problems Before Disaster – Life-Saving Wearable Tech
Posted on September 13, 2015 By Phoebe-Vowels Webb
North Carolina University researchers are developing wearable technology that could give doctors live updates on their patients’ respiratory problems. Researchers at ASSIST (Advanced Self-Powered Systems of Integrated Sensors and Technologies) have developed wearable sensors powered by body heat, which can be used by the new algorithm to monitor patients’ breathing.
We’ve developed an algorithm that can assess the onset time, pitch and magnitude of wheezing sounds to give healthcare professionals information about the condition of the lungs. This information, in turn, can be used to help doctors make more informed decisions about diagnosis and treatment.” – Hamid Krim, North Carolina University
Saba Emrani and Hamid Krim have already tested their algorithm, and so far there have been successful and promising results, which could eventually be implemented through wearable technology. The idea is that the algorithm is applied to patients’ breathing, and its data collected through body-heat-powered sensors developed by ASSIST researchers. The analysis of wearers’ wheezing would then be transmitted to an app on their smartphones. The suffering of people with breathing problems could very soon be more quickly and effectively treated, and premature death could be prevented.
This work is very important, because even though there’s already a lot of awareness and support for conditions such as asthma and emphysema, too many people still die. On average 3 people die a day from asthma attacks in the UK alone, but this research could soon change this unacceptable death rate.
I used to know a girl at school; she was kind, interesting and hardworking. In the summer before our final year, she had an acute asthma attack in her sleep, and died. Because of a preventable problem a family lost a daughter and a big sister. There are too many other stories like this. Too many people are dying from treatable breathing problems, often because they’re simply asleep. If this research goes ahead further tragedies could be prevented. Krim and Emrani hope their work leads to patients receiving alerts when their breathing becomes too impeded, in time to use their pump, drugs or oxygen. For people with severe cases of breathing conditions, their sensors could report directly to their hospital so that the right help can be dispatched immediately.
Before developing and mass producing the technology, the research will be presented at the 2015 European Signal Processing Conference. If the work is continued, the algorithm and body-heat-powered sensors could revolutionise the way that doctors assist patients with respiratory problems.
Whilst the potentially life-saving benefits of this technology are the obvious headline, people with conditions like asthma, acute sinusitis and emphysema could benefit in another way. Sufferers could gain a deeper understanding of their condition, making it easier for them to identify and avoid triggers by observing their breathing status on their smart phone.
Not only could Krim and Emrani’s research lead to helping millions of people, but it will contribute to the wider global wearables market, which is already predicted to grow at a compound rate of 35% for the next five years., More researchers are developing technology to improve our lives. The JustMilk is just one; it aims to ensure life-saving medicine and nutrients are given to babies through mother’s milk. The rate at which this market is growing, and the calibre of its products, indicates a new era of practical and life-preserving technology. If this algorithm is built into sensors to help diagnose breathing problems, lives could be immediately enhanced as well as the market. The future’s bright.
Image by MedGizmo