Digital mass testing for Covid-19 could soon be possible through smartphone applications and machine learning techniques to identify patterns in sounds made by simply breathing.

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The sound of a person’s breathing, cough or even their voice could all be used to help diagnose patients with Covid-19, as Khalifa University researchers design an app using artificial intelligence to detect the sounds of a coronavirus infection.

The standard methods to test for Covid-19 rely on polymerase chain reaction (PCR) technologies. While highly accurate, these tests are hindered by the time taken to get results. They also require trained personnel, properly equipped test sites, and robust operational and logistical supply chains. Not to mention, PCR testing is unpleasant for the patient which can deter them from testing regularly.

Finding promising alternatives that are simple, fast and cost-effective is the goal. Plus, since Covid-19 cases continue to increase around the world, a system capable of recognizing the disease in signals recorded by portable devices, such as smartphones, is essential.

Mohanad Alkhodari, Research Associate, and Dr. Ahsan Khandoker, Associate Professor of Biomedical Engineering, investigated the use of breathing sounds and a deep learning framework to determine Covid-19 infections from healthy subjects, including asymptomatic cases. Their results were published in

“Recent studies have used new emerging algorithms in artificial intelligence to detect and classify Covid-19 infections in CT and X-ray images, averaging over 95 percent accuracy,” Alkhodari said. “While the imaging techniques aren’t feasible for frequent testing purposes, the machine learning techniques can be used in determining infection from biological respiratory signals, such as coughing and breathing sounds.”

The human body makes all sorts of noises and physicians have used them to diagnose disease—perhaps the most classic medical device is the stethoscope. Auscultation, the technique of listening to the body, can be challenging for humans to grasp accurately, but it’s a simple task for a machine. Artificial intelligence algorithms can identify features or patterns in sounds that the human ear cannot, and can also pick up noises that are beyond human hearing.

“Respiratory auscultation is a safe and non-invasive technique to diagnose the respiratory system and its associated organs,” Alkhodari said. “Clinicians can hear and record the air sound moving inside and outside the lungs while breathing or coughing, and then identify any abnormalities. This could serve as an early alert to a patient before they move on with further testing.”

Previous studies have investigated the information carried in respiratory sounds in patients who tested positive for Covid-19, forming the dataset necessary to train a machine learning algorithm. Additionally, the vocal patterns seen in patients with Covid-19 show indicative biomarkers for viral infection.

“Although the current gold standard, PCR testing has various limitations, including the high expenses involved in equipment and chemical agents, the need for experts for diagnosis, and the long wait needed for results,” Dr. Khandoker said. “A handheld deep learning model overcomes most of these limitations and allows for a better revival of the healthcare and economic sectors in several countries.”

The team focused on a dataset from India, using a total of 480 breathing sounds from a publicly available dataset. These sounds were recovered by an equal number of healthy and infected subjects using a smartphone microphone and fed into the deep learning framework.

“India is severely suffering from a new genomic variant of Covid-19,” Dr. Khandoker said. “This gives us an insight to the ability of the AI algorithms in detecting infection in patients carrying this new variant, as well as asymptomatic patients.”

The results obtained from testing the deep learning framework on the Indian dataset shows its potential for developing telemedicine and smartphone applications for Covid-19 that can provide real-time results in an efficient and timely manner. It could also be extended beyond Covid-19 to future pandemics or other respiratory diseases. For countries experiencing high infection rates, this technique would also mean isolation behaviors could be maintained, reducing further infection spread, but also provide a diagnostic test that is much cheaper for places struggling to implement the infrastructure needed for mass PCR testing.

“This study paves the way towards implementing deep learning in Covid-19 diagnostics,” Dr. Khandoker said.��

Jade Sterling
Science Writer
1 March 2022

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EBTIC and BT Team Win International Awards Based on Innovation, Relevance and Evidence of Success, for their SPL Solution and Trial ��

The SPL team led by Salwa Alzahmi, a senior researcher at KU’s Emirates ICT Innovation Center (EBTIC), has won two awards in two categories at the prestigious 2021 Artificial Intelligence (AI) and Machine Learning Awards in the UK.��

EBTIC is a research and innovation center focused on driving research and innovation in intelligent systems and applications founded by Khalifa University, Etisalat and BT (British Telecom), and supported by the Telecommunication and Digital Government Authority’s (TDRA) ICT Fund. It is based at the Khalifa University campus in Abu Dhabi.��

The Computing magazine’s AI and Machine Learning Awards recognise the best companies, individuals, and projects in artificial intelligence. The judging process covers several industry segments such as security, ethics, data analysis, and innovation, while showcasing the movers and shakers including the technology heroes and projects that deserve industry-wide praise.��

The awards won by EBTIC’s SPL were in the categories of Best Cloud Automation Tool and Best Use of Automation. An elite panel of 12 judges selected the SPL entries as winners based on the evidence of three factors – innovation, relevance, and achieved success. More specifically, the Best Cloud Automation Tool award was given to EBTIC and BT for the tool’s innovative and fully featured automation solution that is designed to ease the burden of application migration to the Cloud. In their citation, the judges mentioned that the SPL Tool ‘has the opportunity to hugely reduce code complexity, thus improving security and reducing the cost of cloud migration’.��

In the Best Use of Automation award category, the SPL tool was highly recommended for the automation of migrating legacy software systems to cloud-native architecture using artificial intelligence, hence, addressing the challenges of complexity and high associated costs. The judges’ citation mentioned that the SPL team is highly recommended for this category for its ‘SPL project that has a strong topical story and told it well’.��

Dr. Nawaf I. Almoosa, Acting Director, Head of Smart Infrastructure Research, EBTIC, and Associate Professor, Electrical Engineering and Computer Science, Khalifa University, said: “Achieving this success in the 2021 Artificial Intelligence and Machine Learning Awards across two categories strongly indicates the extent of cutting-edge technological innovation being produced by the EBTIC’s SPL team productive partnership with BT to accurately target the future requirements of the industry in these areas. Our team members have demonstrated their talent in another prestigious international competition, and we hope to continue exploring innovation through working on new projects in AI and ML-related areas.”

SPL is a platform developed at EBTIC and uses intelligent methods to simplify and streamline software governance, development, and migration to the Cloud. The technology is currently undergoing commercialisation as a start-up in collaboration with Khalifa Innovation Center (KIC). Salwa Alzahmi, an Emirati researcher and tech entrepreneur, is leading the SPL platform development and commercialization, and has been instrumental in driving the technology, its commercialisation and the collaboration with BT Applied Research to evaluate the tool’s business value. As part of the drive for commercialisation, Alzahmi has set up a UAE-based tech start-up in the Khalifa Innovation Center – KIC khalifainnovation.ac.ae that is registered at Abu Dhabi Global Market. The EBTIC-SPL research team also includes Ahmed Suliman, Corrado Mio and Sid Shakya.

At the Computing AI and Machine Learning Awards 2021 in London, one of the UK’s leading business technology information resource, EBTICs SPL won awards for “Best Cloud or Networking Automation Tool” and was highly commended in the category of “Best Use of Automation”

The judges commented that SPL, in winning the “Best Cloud or Networking Automation Tool” category “has the opportunity to hugely reduce code complexity, thus improving security and reducing the cost of cloud migration.”

Alzahmi, Senior Research at EBTIC who leads the SPL team, said “I’m so proud of my team to be recognised in such a fantastic way. It is testament to all the hard work that has been put in to make the SPL tool such a compelling solution.”

Dr. Nawaf Almoosa, Acting Director of EBTIC, said: “EBTIC has a history of innovating practical AI solutions and have been a leader in intellectual property generation in UAE for the past 10 years. These awards are a further testament to EBTIC’s expertise of applying AI techniques to the operations of its partner organizations, and to their effort to promote Intelligent Systems research in the UAE and the region. We are immensely proud for the SPL team to be winning such prestigious awards, and we have high hopes for the future of SPL. I’d like to thank the SPL Team: Salwa Alzahmi, Corrado Mio, Ahmad Suliman, and Sid Shakya for this great achievement.”

Computing’s AI & Machine Learning Awards recognise the best companies, individuals, and projects in the AI space today. The judging process covers every corner of the industry: security, ethics, data analysis, innovation and more, as well as showcasing the movers and shakers: the technology heroes and projects that deserve industry-wide praise. With judges from prestigious organisations, such as Expedia Group, Network Rail, MET Office, London Stock Exchange and Computing itself, the winning of these awards proves that SPL demonstrates an outstanding, innovative approach in the field of AI.

EBTIC spun-out SPL.Co Ltd as a start-up in its own right, incorporated in 2019 and registered at Abu Dhabi Global Market. It came about following the success of SPL as a research project in 2015. SPL.Co provides corporations with an intelligent software modernization solution to accelerate and reduce the high costs associated with upgrading software systems into a cloud infrastructure.

EBTIC has a very successful history with Computing awards. In 2019, EBTIC’s spares optimization project Inuitu, won two awards for ‘Outstanding AI/Machine Learning Project’ and ‘Most Innovative use of AI/Machine Learning’.

EBTIC has produced more than 500 scientific publications, developed more than 75 inventions, resulting in 60 granted patents, with more pending, and has trained more than 350 students,�� and 250 professionals. It has also organized 10 international technical workshops and developed numerous technologies and worked on many projects in collaboration with its partners and stakeholders.

Clarence Michael
English Editor Specialist
10 August 2021

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