Ambient health sensing on passive surfaces using metamaterials.
Dat T NguyenQihang ZengXi TianPatrick ChiaChangsheng WuYuxin LiuJohn S HoPublished in: Science advances (2024)
Ambient sensors can continuously and unobtrusively monitor a person's health and well-being in everyday settings. Among various sensing modalities, wireless radio-frequency sensors offer exceptional sensitivity, immunity to lighting conditions, and privacy advantages. However, existing wireless sensors are susceptible to environmental interference and unable to capture detailed information from multiple body sites. Here, we present a technique to transform passive surfaces in the environment into highly sensitive and localized health sensors using metamaterials. Leveraging textiles' ubiquity, we engineer metamaterial textiles that mediate near-field interactions between wireless signals and the body for contactless and interference-free sensing. We demonstrate that passive surfaces functionalized by these metamaterials can provide hours-long cardiopulmonary monitoring with accuracy comparable to gold standards. We also show the potential of distributed sensors and machine learning for continuous blood pressure monitoring. Our approach enables passive environmental surfaces to be harnessed for ambient sensing and digital health applications.
Keyphrases
- low cost
- health information
- public health
- healthcare
- air pollution
- machine learning
- blood pressure
- mental health
- human health
- particulate matter
- biofilm formation
- health promotion
- escherichia coli
- heart rate
- metabolic syndrome
- deep learning
- big data
- skeletal muscle
- artificial intelligence
- weight loss
- single molecule
- simultaneous determination