Smartphone Sensors Could Accurately Foresee Users' Five-Year Mortality Risk

Based on a research released this week, the smartphone in one's pocket may forecast the future 5-year risk of death without the need for any additional applications, activity monitors, or watches.

Complacently accumulating just 6 minutes of strolling data from smartphones' built-in motion detectors successfully predicted the risk of all-cause death rates within and between UK Biobank participants, according to Bruce Schatz, Ph.D. (the University of Illinois at Urbana-Champaign), and collaborators online October 20, 2022, in PLoS Digital Health.

Researchers wanted to see whether they could discover the equivalent of more-controlled hospital strolling tests using simply the data to the simulations that a phone could supply, Schatz explained to TCTMD, emphasizing that the smartphone's motion sensors capture the intensity of walking. He went on to say that it all comes down to the level of physical exercise. It's quite different from what smartwatches are often used for. Smartwatches track how many minutes you spend active each day. Its measuring steps are more concerned with quantity.

Five-Year Probability of Death Risk

Levels of physical activity and all-cause mortality are generally established to have a high association. Schatz claims that around a decade ago, he and a physician discussed if there would be a method to passively observe individuals in their daily activities, as opposed to their donning smartwatches or fitness trackers, and whether it might be used to forecast current and future health state.

To Schatz, expert healthcare providers can typically determine a patient's current health state based on their stride and walking capacity. People have really distinct motions; they'll slow or halt to take a deep breath, for example, and humans thought this was something that could record, even with low-cost sensors.

As reported by SciTech Daily, researchers previously showed that data collected from the phone's motion detectors, which have been worn while cardiopulmonary patients did a routine 6-minute walk test, effectively predicted pulmonary function evaluated by spirometry. Furthermore, data from the phone's motion sensors might forecast levels of oxygen saturation in cardiac patients with high accuracy. This study also showed that motion sensors might anticipate patients' transitions between health status categories.

Keeping this in hand, Schatz as well as colleagues set out to see if phone motion sensors might predict all-cause death. They used datasets from the UK Biobank research, a large-scale database including genetic as well as health information for over 500,000 people, to do this. In that study, 100,655 people wore movement monitors with motion detectors on their wristbands for one week.

The researchers retrieved sensor inputs from such activity monitors which would also be accessible on cheap, already available phones. To the researchers, the actual sensor data of walk strength was taken in twelve 30-second spurts, but these 6 minutes resembled a daily life version of the conventional walk test.

The researchers think that their methods provide a viable pathway for nationwide health risk screening. A new study claims that using smartphone sensors, one can foresee a user's five year mortality risk. iStock / Getty Images Plus

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Using Motion Sensor Data

They used a machine-learning model to examine motion sensor data associated with mortality in around 10% of patients, and they created an algorithm from sensor inputs to calculate the 5-year probability of all-cause death using acceleration acquired over 6 minutes. At 1 and 5 years, the predictive algorithm had a C-index of 0.76 to 0.73 for the entire cohort, respectively. According to the researchers, the algorithm's predicted accuracy is comparable to existing propaganda efforts of gait speed and walking tempo that require physical walk tests including self-reported questionnaires, as per TCTMD.

In terms of therapeutic consequences, Schatz believes smartphone surveillance of physical activity might assist clinicians in better assessing and tracking patients. For instance, the data may be used to forecast all-cause deaths at monthly intervals in individuals above a specific age or in people with concerning test findings. Another area where cell phones might be useful is in evaluating status changes in at-risk patients, like those who have congestive heart failure or COPD.

Such phones have already been linked to a network so data can be sent to the backend, which analyzes it and stores it within the electronic health record, according to Schatz. "I used to tell hospital personnel that this is the domestic equivalent of a medical alert," he added. All healthcare institutions have systems that operate continuously and monitor for unexpected occurrences that should be flagged and reported to physicians. The goal was to convert an inexpensive smartphone into a medical gadget.

Schatz noted that, while none of the present studies is directly related to cardiovascular illness, he feels it will be particularly valuable in this area. CVD is difficult to detect in the absence of hospital visits, he claims. Screening isn't flawless, but it can identify situations that would otherwise go unnoticed. That is the true worth. He anticipates that the most likely effect of this will be to detect cardiac abnormalities in individuals who have recently lost function or in persons who were unaware of a problem.