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DopFone app can accurately track fetal heart rate using only a smartphone

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A team of researchers from the University of Washington has developed DopFone, an innovative app that accurately tracks fetal heart rate using just a smartphone. By utilizing the existing speaker and microphone, DopFone mimics a Doppler ultrasound, emitting a tone while listening for subtle echo variations caused by fetal heartbeats. This technology leverages a machine learning model to estimate the heart rate, offering a convenient and accessible solution for expectant parents and healthcare providers.
DopFone app can accurately track fetal heart rate using only a smartphone

In a remarkable intersection of technology and healthcare, researchers at the University of Washington have developed DopFone, an innovative app capable of accurately tracking fetal heart rates using just a smartphone. By mimicking traditional Doppler ultrasound technology, the app emits a sound wave and listens for the echo variations caused by a fetus’s heartbeat, analyzing this information through machine learning algorithms. This breakthrough not only has the potential to make prenatal care more accessible but also aligns with a growing trend of leveraging everyday technology for life-changing medical applications. In a time when healthcare advancements often feel out of reach for many, DopFone represents a step toward democratizing essential services, similar to how the Court Rules Texas State Must Reinstate Prof Fired for Israel-Palestine Talk highlighted the importance of academic freedom in critical discussions.

The implications of DopFone extend well beyond mere convenience. For many expectant parents, especially those in underserved areas, access to reliable prenatal care is often limited. Traditional monitoring methods can be expensive and require specialized equipment that isn't always available. DopFone’s ability to transform a smartphone into a diagnostic tool could bridge this gap, potentially allowing more parents to track their baby’s health from the comfort of their homes. This is particularly significant given that prenatal care is crucial for ensuring safe pregnancies and healthy births. It raises essential questions about how we can continue to harness technology to create equitable healthcare solutions. Similar efforts in conservation, such as those described in UW researchers decipher beluga calls to bolster conservation efforts, show a growing recognition of the need for innovative approaches to pressing challenges.

However, while the potential of DopFone is exciting, it also invites scrutiny regarding data privacy and the accuracy of such devices. As we integrate more technology into healthcare, ensuring that the data collected is secure and used ethically must be a priority. The reliance on machine learning algorithms to interpret fetal heart rates raises questions about potential misinterpretations and the consequences they could have on expectant parents who may rely on this information for peace of mind. It’s crucial that as we celebrate such innovations, we also remain vigilant about the standards of accuracy and privacy that should accompany them.

Looking forward, DopFone is a promising example of how technology can reshape healthcare, but it also serves as a reminder of the responsibilities that come with such advancements. As we continue to witness innovations that leverage our everyday devices for significant healthcare solutions, the question remains: how will we ensure that these advancements are accessible, reliable, and ethical? As students at WSU and beyond, we should engage in these conversations, advocating for solutions that not only enhance our lives but also prioritize community health and well-being. The future of healthcare may well hinge on our collective ability to navigate these challenges together, ensuring that technology serves as a bridge rather than a barrier.

DopFone uses an off-the-shelf smartphone’s existing speaker and microphone to accurately estimate fetal heart rate. The phone mimics a Doppler ultrasound, emitting a tone and listening for the subtle variations in its echo caused by fetal heart beats. A machine learning model then estimates the heart rate. Photo: Garg et al./Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Heart rate is an important sign of fetal health, yet few technologies exist to easily and inexpensively track fetal heart rates outside of doctors’ offices. This can create risks for pregnancies in low-resource regions where doctors are far away or inaccessible. 

A team led by University of Washington researchers has created DopFone, a system that uses an off-the-shelf smartphone’s existing speaker and microphone to accurately estimate fetal heart rate. The phone mimics a Doppler ultrasound, emitting a tone and listening for the subtle variations in its echo caused by fetal heart beats. A machine learning model then estimates the heart rate. In a clinical test with 23 pregnant women, DopFone estimated heart rate with an average error of 2 beats per minute, or bpm. The accepted clinical range is within 8 bpm. 

The team published its research Dec. 2 in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 

“Eventually DopFone could let people test fetal heart rate regularly, rather than relying on the intermittent tests at a doctor’s office, or not getting tested at all,” said lead author Poojita Garg, a UW doctoral student in the Paul G. Allen School of Computer Science & Engineering. “Patients might then send this data to doctors so that they can better judge patients’ health when they’re not in a clinic.”

Traditional Doppler ultrasounds, the clinical standard for fetal heart rate monitoring, work by sending high-frequency sound into a person’s body and tracking how the echo changes in frequency. They’re very accurate at measuring fetal heart rate but require costly equipment and a skilled technician to operate it.

To use DopFone, a user places the phone’s microphone against their abdomen for one minute. The phone emits a subaudible 18 kilohertz tone. The team chose this low frequency because — unlike a Doppler’s high frequencies, above 2,000 kilohertz —  it sits within the range smartphone microphones can record while still traveling well through tissue. As the tone is reflected through the user’s abdomen, the fetus’s heartbeat creates small shifts in the sound. 

A machine learning model then estimates the heart rate using the audio and the patient’s demographic information

The team tested DopFone in UW Medicine’s maternal-fetal medicine division on 23 pregnant patients between 19 and 39 weeks of pregnancy. On average its readings were within 2.1 bpm of the medical Doppler ultrasound. Its accuracy was slightly diminished for patients with high body mass indexes, though those readings were still within normal limits. Because an irregular fetal heartbeat is often an emergency, DopFone was not tested on patients with irregularities. 

Next, the team plans to gather more data outside a lab to better train the model. Eventually they want to deploy it as a publicly available app.

“This women’s health space is often overlooked,” Garg said. “So I want to focus on accessible alternatives that can be available to people in low resource areas, whether that’s here in the U.S. or in other countries. Because health belongs to everyone.”

Co-authors include Mingzhuo Ma, a UW graduate student in electrical and computer engineering; Hayley Jane MacKinnon and Dr. Michael Richley, both OB/GYNs in UW Medicine’s  maternal-fetal medicine division; and Vikram Iyer, a UW assistant professor in the Allen School. Shwetak Patel, a UW professor in the Allen School and in electrical and computer engineering, and Alexander T. Adams of the Georgia Institute of Technology, were senior authors. This research was funded by the UW Gift Fund. 

For more information, contact Garg at pgarg70@uw.edu.

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#Washington State University#WSU research programs#student life at WSU#public land-grant university#DopFone#fetal heart rate#smartphone#Doppler ultrasound#machine learning#University of Washington#clinical test#pregnant women#heart beats#health#low-resource regions#research#Proceedings of the ACM#echo#high-frequency sound#accelerated testing