The team, led by Trisha L. Andrew, professor of chemistry and chemical engineering at the University of Massachusetts Amherst, described pressure as ‘one of the most difficult problems in the quest to create wearable, unobtrusive sensitive sensors’.
“Imagine comfortable clothing that would monitor your body’s movements and vital signs continuously, over long periods of time,” said Andrew.
“Such clothing would give clinicians fine-grained details for remote detection of disease or physiological issues.”
One way to get this information is with tiny electromechanical sensors that turn your body’s movements — such as the faint pulse you can feel when you place a hand on your chest — into electrical signals.
However, Andrew explained that increased pressure (such as when a person receives a hug or lies on their stomach) overwhelms the sensor, interrupting the flow of data and rendering it useless for monitoring natural phenomena.
To address this, the team claims to have developed a sensor that keeps working in various everyday interactions such as being hugged, sat on or leaned on.
Detailed in Advanced Materials Technologies, the team’s solution was vapour-printing clothing fabrics with piezoionic materials such as PEDOT-Cl (p-doped poly(3,4-ethylenedioxythiophene-chloride).
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With this method, even the smallest body movement, such as a heartbeat, leads to the redistribution of ions throughout the sensor, the team said. The fabric turns the mechanical motion of the body into an electric signal, which can then be monitored.
Zohreh Homayounfar, lead author of the study and a graduate student at UMass Amherst, described it as the first fabric-based sensor allowing for real-time monitoring of sensitive target populations, from workers labouring in stressful industrial settings, to children and patients undergoing rehabilitation .
According to the team, one advantage is that the all-fabric sensor can be worn in comfortable, loose-fitting clothing rather than embedded in tight-fitting fabrics or stuck directly onto the skin.
This makes it easier for the sensors to gather long-term data, such as heartbeats, respiration, joint movement, vocalisation, step counts and grip strength, the team said, with potential to track everything from bone density to depression.
Andrew and her group will next use an array of the pressure sensors under additional scenarios to determine what other types of physiological signals can be extracted, and to what degree of accuracy.
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