Discovering ways to non-invasively early detect COVID-19 from heart rate, sleep, or a cough sound, even among the asymptomatic

November 6, 2020 | by

Heart rate, sleep quality, daily movement–cough sound frequency? Several studies in the US and UK are attempting to turn up ways to early diagnose mildly symptomatic, asymptomatic, or even pre-symptomatic COVID-19 cases, without the PCR swab or a blood test.

The more obvious of the two comes out of the Scripps Research Translational Institute. The DETECT study started in March (!) with 30,500 participants sending in data in the first six weeks of the study on heart rate, sleep quality, and daily movement. This information was then matched with self-reported symptoms and diagnostic tests taken if any. In this way, new infections and outbreaks could be detected at an earlier stage.  The study is attempting to confirm if changes in those metrics in an individual’s pattern can identify those even at a pre-symptomatic or asymptomatic stage. 3,811 reported symptoms, 54 reported testing positive, and 279 negative for COVID-19. The numbers seem small, but the analysis carries out that the combination of sensor and symptom data performed better in discriminating between positive and negative individuals than symptom reporting alone. The symptom data were taken from Fitbits and any device connected through Apple HealthKit or Google Fit data aggregators, then reported on the research app MyDataHelps. FierceBiotech, Nature Medicine (study)

Also using vital signs, back in August, Fitbit released early data on a 100,000+ study where changes in heart rate and breathing could detect about half of diagnosed cases at least one day to a week before diagnosis. Symptomatic cases were 1,100 in this sample. Heart rate and breathing were detected to become more frequent in the symptomatic, with the variability in time between each heartbeat dropping, resulting in a more steady pulse. The preferred tracking was at night during rest. However, there was a 30 percent false positive rate on the algorithm used, which is extremely high. FierceBiotech Related to this work, Fitbit was selected at the end of October by the US Army Medical Research and Development Command (USAMRDC) to receive nearly $2.5 million from the US Department of Defense through a Medical Technology Enterprise Consortium (MTEC) award to advance a wearable diagnostic capability for the early detection of a COVID-19 infection. Fitbit will be working with Northwell Health’s Feinstein Institutes for Medical Research to validate their early detection algorithm. Business Wire

And what about that ‘Covid Cough’? MIT is researching that this cough is different than other coughs, like from cold or allergy. Their research found that there’s a difference in the sound of an asymptomatic individual’s cough–and that sound frequency difference could not be heard by human ears. (Dog ears perhaps?) MIT researchers created “the largest audio COVID-19 cough balanced dataset reported to date with 5,320 subjects” out of 70,000 cough samples. The algorithm performed well. “When validated with subjects diagnosed using an official test, the model achieves COVID-19 sensitivity of 98.5% with a specificity of 94.2% (AUC: 0.97). For asymptomatic subjects it achieves sensitivity of 100% with a specificity of 83.2%.” This sure sounds like an AI screening tool that is inexpensive and convenient to use with multiple populations even daily. IEEE-EMB  BBC News reports that similar studies are taking place at Cambridge University, Carnegie Mellon University, and UK health start-up Novoic. The Cambridge study used a combination of breath and cough sounds and had an 80 percent success rate in identifying positive coronavirus cases from their base of 30,000 recordings.

All of these will be useful, but still need to be validated–and that takes time, for which this Editor thinks is short as this virus, like others, will eventually 1) mutate out or 2) be effectively treated as we do with normal flus. But down the road, these will serve as a template for new ways for early screening or even diagnosis of other respiratory diseases.

What it takes to make telehealth really work

September 6, 2015 | by

In line with my fellow editor, forgive this editor engaging in a little nostalgia – going back to 2006, when the Whole System Demonstrator was a still a wonderful idea, before the competing forces of academia and management consultancy put short-term financial gain before long term patient outcome improvement. Those were the days when we genuinely believed that recording vital signs was what it was all about.

Move on nine years and it’s clear from the American Heart Association review referred to in this column recently, and subsequent articles, that one key success factor is drip-fed education. To quote:

“The amount of information that must be conveyed and the support that is necessary to counsel and motivate individuals to engage in behaviors to prevent CVD are far beyond what can be accomplished in the context of face-to-face clinical consultations or through traditional channels such as patient education leaflets,” the researchers say. “Mobile technologies have the potential to overcome these limitations and to transform the delivery of health-related messages and ongoing interventions targeting behavior change.”

This is underlined by a recent study of attempting to control hypertension using just text messaging, which was far from an unqualified success.

Another major driver of course is cost saving, as demonstrated by (more…)

Encouraging signs of change

March 17, 2014 | by

A couple of recent articles have given me hope, after a really depressing session at my local surgery today for an NHS Health Check.  It began when I spotted two adjacent notices in the waiting room, the first encouraging patients to access the surgery’s online facilities, and the second banning the use of mobile devices. It descended further when after producing the form I’d been asked to complete about height, weight, alcohol consumption, family history of disease etc., I was asked every question all over. When I protested, I was told that as most patients don’t fill in the form, or forget it, they ask patients anyway. (Discretion suggested it probably wasn’t the right time to suggest that perhaps that was why people don’t fill in forms…)

However the first article, by Zahid Latif, who heads up healthcare for the Technology Strategy Board, indicates a restlessness with the current use of patient data that appeals to me.  He goes on to explain how the projects in the TSB’s dallas programme (more…)