Lady in white lab coat holding a tablet with a digital image of a person and health-icons floating above it

At-home cutting-edge tech paves the way towards the future of medical diagnosis

  • Engineers developed a high-tech toilet seat that monitors your heart health
  • Early signs of atrial fibrillation could be detected by a wearable
  • Detecting the early symptoms of stroke is now easier with a smartphone app
  • A new app can diagnose anemia by analysing a photo of your fingernails
  • Mild cognitive impairment can be detected by a simple multi-sensory test
  • Children’s respiratory diseases can be diagnosed based on the sound of their cough
  • A smartphone app that can detect ear infections in children
  • How will technology affect the future of medical diagnosis?

Medical diagnosis is one of the most important aspects of healthcare. Usually, when a person feels ill, they go to a doctor, who then runs some tests to determine what’s wrong with them and assign a treatment. According to the Centers for Disease Control and Prevention (CDC), 14 billion laboratory tests are performed every year in the United States alone, and their results influence 70 per cent of today’s medical decisions.

An infographic showing the percentage of patient deaths, as well as the percentage of all adverse events in hospitals that can be attributed to diagnostic errors.
The World Health Organization estimates that diagnostic errors are responsible for 6 to 17 per cent of all adverse events in US hospitals, including 10 per cent of all patient deaths.

Providing the right diagnosis and doing it as quickly as possible is paramount to a patient’s chances of recovery. The sooner a doctor can discover what ails the patient, the better their odds of coming out on top. However, that’s not always as simple as it sounds, and getting the diagnosis wrong can often have serious consequences. In fact, diagnostic errors are responsible for approximately 10 per cent of patient deaths in the United States, according to the World Health Organization. In an attempt to improve their diagnostic capabilities and reduce the number of errors, medical professionals around the world are increasingly turning to technology for help.

Engineers developed a high-tech toilet seat that monitors your heart health

The World Health Organization estimates that cardiovascular diseases (CVDs) are responsible for 17.9 million deaths worldwide every year, with 85 per cent of those deaths attributed to heart attacks and strokes. However, many of those deaths could have easily been prevented had the underlying condition been caught in time. To address this issue, engineers from the Rochester Institute of Technology have developed a high-tech toilet seat that allows people to keep track of their cardiovascular health in the privacy of their own home.

An infographic showing the number of deaths worldwide attributed to cardiovascular diseases.
According to the World Health Organization, 17.9 million deaths can be attributed to cardiovascular diseases every year, with heart attacks and strokes responsible for 85 per cent of those deaths.

The toilet seat is powered by a battery and equipped with three sets of sensors that record electrocardiogram (ECG), photoplethysmogram (PPG), and ballistocardiogram (BCG) readings each time a person sits down on it. This data is used to estimate stroke volume, blood pressure, and peripheral blood oxygenation, and then it’s transmitted to a cloud database over WiFi. “The toilet seat–based cardiovascular monitoring system has the potential [to] fill a gap in patient monitoring by capturing trend data that has been previously unattainable,” write the researchers. “This system has the potential to address many of the challenges with in-home monitoring in a form factor that integrates into the daily routine of patients, bypassing barriers to adherence and providing a comprehensive and accurate set of clinically relevant measurements.”

During testing, the engineers found that their system has an accuracy comparable to that of standard hospital measurements in most cases, while in some cases, it even provided greater accuracy. The only drawback of the toilet seat is that it currently can’t collect accurate measurements when the person is actually using the toilet, but the engineers hope to solve this issue in the future.

Early signs of atrial fibrillation could be detected by a wearable

For those who want to keep track of their heart health throughout the day and not just when they sit on the toilet, a new smart wristband may offer a solution. Developed by researchers from the Kaunas University of Technology’s Biomedical Engineering Institute, this prototype device can detect the early signs of atrial fibrillation, one of the most common types of arrhythmia, or irregular heartbeat. Easy to miss in the early stages, undiagnosed atrial fibrillation can lead to far more serious conditions, such as blood clots, stroke, and heart failure.

The device is equipped with PPG and ECG sensors, which allow it to detect blood volume changes within tissue and monitor the heart’s electrical activity through the skin. After filtering out irrelevant digital noise using special algorithms, the device will compare the readings captured by the two sensors and warn the wearer by vibrating if it detects something unusual. “Due to the prevalence of this condition, every person older than 65 should be checked for atrial fibrillation,” says the lead scientist, Dr Vaidotas Marozas. “However, relying on the short-term clinical ECG, the arrhythmia can be detected only if the condition is chronic. What if the episodes are occurring only occasionally? Then our technology is very useful.”

Detecting the early symptoms of stroke is now easier with a smartphone app

Researchers at Valencia’s Polytechnic University (UPV) have developed an Android app that can use a smartphone’s sensors to detect the early symptoms of stroke and automatically notify emergency services. Currently in the testing stage, the app asks users to perform three simple tasks, starting with smiling for the smartphone’s camera. If the user has experienced a stroke, their face may be partially paralysed, making them unable to smile. The second task involves repeating a simple sentence into the phone’s microphone, allowing the app to check the user’s speech coherence. In the final task, users are required to lift each of their arms while holding the smartphone. Users who have experienced a stroke will often be unable to lift one arm as high as the other, which the app can verify using the phone’s accelerometer.

If the user is unable to complete two out of three of these tasks, the app will automatically try to get help by notifying emergency services, as well as the user’s emergency contact. “Despite the awareness campaigns carried out by different entities, many people are unable to identify the signs of this condition,” says Jaime Lloret, an associate professor. “Smartphones seem to be a good platform on which to develop applications aimed at people’s health, such as in this case, to carry out an early detection of a pathology which affects 120,000 people in Spain alone.”

A new app can diagnose anemia by analysing a photo of your fingernails

While not as serious as some of the other conditions mentioned above, anemia can also adversely affect a person’s quality of life, making them feel tired and weak. Characterised by a lack of healthy red blood cells, anemia is a very common blood disorder that affects 2 billion people around the world. It’s typically diagnosed with a blood test known as a complete blood count (CBC), but from now on, it could be as simple as snapping a photo of your fingernails.

Researchers at Emory University have developed a smartphone app that can detect anemia by measuring the concentration of hemoglobin in blood from a photo of fingernail beds. Since fingernail beds don’t contain any melanin that could mask their colour, they can offer a good indication of overall hemoglobin levels, allowing the researchers to create an algorithm that can convert fingernail bed colour to blood hemoglobin levels. The app offers anemia patients a simple, cheap, and non-invasive way to monitor their condition and could be particularly useful in developing countries, where access to medical facilities may be limited. “All other ‘point-of-care’ anemia detection tools require external equipment, and represent trade-offs between invasiveness, cost, and accuracy,” says the principal investigator, Wilbur Lam. “This is a standalone app whose accuracy is on par with currently available point-of-care tests without the need to draw blood.”

Mild cognitive impairment can be detected by a simple multi-sensory test

Mild cognitive impairment (MCI) is a moderate form of age-related cognitive decline that involves problems with memory and thinking. More importantly, it’s also known to lead to more serious conditions like Alzheimer’s disease, with 30-50 per cent of those diagnosed with MCI eventually developing Alzheimer’s as well. That’s why it’s incredibly important to diagnose MCI as early as possible, as it allows doctors to react in time to prevent further cognitive decline. Unfortunately, there’s currently no simple way to diagnose this condition, and patients are usually required to undergo extensive neuropsychological assessment, which can be unreliable at times.

To address this issue, researchers from Switzerland and the UK have developed a simple, cost-effective test that can detect MCI with a high degree of accuracy. In the test, which can be taken on a smartphone or a PC, users are asked to press a button any time they see a flash of light or hear a sound. By analysing the speed at which they detect flashes and sounds, which can appear either alone or simultaneously, the test can accurately identify whether the person is suffering from MCI. “We are particularly excited about this work because it shows how very simple tests can help clinical practice by reaching a wider population, at a lower cost. We are happy that our findings clarify the link between our vision and hearing and their role in supporting memory (dys-)function; it becomes increasingly clear that how preserved our cognitive skills are as we age depends on how intact our senses are,” says Professor Micah Murray from the University of Lausanne, Switzerland.

Children’s respiratory diseases can be diagnosed based on the sound of their cough

Recognised as the second leading cause of children’s visits to emergency services, respiratory disorders can be difficult to differentiate even for the most experienced paediatricians. To solve this problem, researchers at the University of Queensland in Australia have developed a smartphone app that uses machine learning technology to accurately identify various respiratory diseases based on the sound of a child’s cough.

The researchers first collected an audio database that consisted of cough recordings taken from 1,437 hospitalised children between 29 days and 12 years of age, who were all diagnosed with one of the following five conditions: consolidative pneumonia, asthma, bronchiolitis, croup, and general lower respiratory tract disease (LRTD). 852 of those recordings were then used to create a training set that would teach the algorithm to recognise unique auditory characteristics associated with each respiratory disorder. Finally, the algorithm was then applied to the remaining 585 recordings in the database to see whether it would be able to accurately identify the disorders. The app performed quite well, with its accuracy ranging from 81 to 97 per cent, depending on the disorder.

A smartphone app that can detect ear infections in children

The National Institutes of Health lists ear infections as the most common reason parents take their child to see a doctor. Typically caused by bacteria, ear infections occur when fluid builds up behind the eardrum. In addition to being painful, an ear infection can also make it difficult for the child to hear. However, due to vague symptoms, ear infections can be difficult to diagnose. But that may be about to change thanks to researchers from the University of Washington (UW), who have developed a smartphone app that can detect fluid behind the eardrum using nothing more than a piece of paper and the phone’s speaker and microphone.

The paper is first folded into a funnel and placed on the outer ear. The phone is then used to play a continuous 150 millisecond chirping sound through the funnel, which is then picked up by the microphone as it bounces back off the eardrum. The presence or absence of fluid behind the eardrum will affect the vibration pattern of the reflected sound waves differently, making it much easier to diagnose the ear infection. According to researchers, the app detected the presence of fluid with 85 per cent accuracy, which is comparable to current clinical methods. “Designing an accurate screening tool on something as ubiquitous as a smartphone can be game changing for parents as well as health care providers in resource limited regions,” says Shyam Gollakota, an associate professor at UW’s Paul G. Allen School of Computer Science & Engineering. “A key advantage of our technology is that it does not require any additional hardware other than a piece of paper and a software app running on the smartphone.”

How will technology affect the future of medical diagnosis?

Technology has had a major impact on almost every aspect of the medical profession, and the same may soon be true for medical diagnosis as well. Diagnostics plays a key role in medicine and can often mean the difference between life and death for a patient, which is why medical professionals are constantly looking for ways to increase the accuracy and availability of their diagnostic methods.

In recent years, technologies like wearables, artificial intelligence, and machine learning have emerged as increasingly important diagnostic tools that improve efficiency and deliver faster, more accurate results. They also herald a move away from diagnostic testing that’s performed exclusively in a clinical setting towards a more personalised, private testing environment. At this point, it’s not too difficult to imagine a future in which we’ll be able to diagnose and monitor a variety of conditions in the privacy of our own home, instead of going to the doctor.

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