A fully integrated wearable ultrasound system to monitor deep tissues in moving subjects.
Muyang LinZiyang ZhangXiaoxiang GaoYizhou BianRay S WuGeonho ParkZhiyuan LouZhuorui ZhangXiangchen XuXiangjun ChenAndrea KangXinyi YangWentong YueLu YinChonghe WangBaiyan QiSai ZhouHongjie HuHao HuangMohan LiYue GuJing MuAlbert YangAmer YaghiYimu ChenYusheng LeiChengchangfeng LuRuotao WangJoseph WangShu XiangErik B KistlerNuno VasconcelosSheng XuPublished in: Nature biotechnology (2023)
Recent advances in wearable ultrasound technologies have demonstrated the potential for hands-free data acquisition, but technical barriers remain as these probes require wire connections, can lose track of moving targets and create data-interpretation challenges. Here we report a fully integrated autonomous wearable ultrasonic-system-on-patch (USoP). A miniaturized flexible control circuit is designed to interface with an ultrasound transducer array for signal pre-conditioning and wireless data communication. Machine learning is used to track moving tissue targets and assist the data interpretation. We demonstrate that the USoP allows continuous tracking of physiological signals from tissues as deep as 164 mm. On mobile subjects, the USoP can continuously monitor physiological signals, including central blood pressure, heart rate and cardiac output, for as long as 12 h. This result enables continuous autonomous surveillance of deep tissue signals toward the internet-of-medical-things.
Keyphrases
- heart rate
- blood pressure
- heart rate variability
- electronic health record
- big data
- machine learning
- magnetic resonance imaging
- gene expression
- ultrasound guided
- type diabetes
- small molecule
- artificial intelligence
- metabolic syndrome
- high throughput
- deep learning
- social media
- climate change
- insulin resistance
- health information
- low cost
- single molecule
- weight loss
- living cells