Cloud-Integrated Smart Nanomembrane Wearables for Remote Wireless Continuous Health Monitoring of Postpartum Women.
Jared MatthewsIra SoltisMichelle Villegas-DownsTara A PetersAnne M FinkJihoon KimLauren ZhouLissette RomeroBarbara L McFarlinWoon-Hong YeoPublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2024)
Noncommunicable diseases (NCD), such as obesity, diabetes, and cardiovascular disease, are defining healthcare challenges of the 21st century. Medical infrastructure, which for decades sought to reduce the incidence and severity of communicable diseases, has proven insufficient in meeting the intensive, long-term monitoring needs of many NCD disease patient groups. In addition, existing portable devices with rigid electronics are still limited in clinical use due to unreliable data, limited functionality, and lack of continuous measurement ability. Here, a wearable system for at-home cardiovascular monitoring of postpartum women-a group with urgently unmet NCD needs in the United States-using a cloud-integrated soft sternal device with conformal nanomembrane sensors is introduced. A supporting mobile application provides device data to a custom cloud architecture for real-time waveform analytics, including medical device-grade blood pressure prediction via deep learning, and shares the results with both patient and clinician to complete a robust and highly scalable remote monitoring ecosystem. Validated in a month-long clinical study with 20 postpartum Black women, the system demonstrates its ability to remotely monitor existing disease progression, stratify patient risk, and augment clinical decision-making by informing interventions for groups whose healthcare needs otherwise remain unmet in standard clinical practice.
Keyphrases
- weight gain
- healthcare
- body mass index
- cardiovascular disease
- polycystic ovary syndrome
- blood pressure
- case report
- deep learning
- big data
- weight loss
- clinical practice
- decision making
- pregnancy outcomes
- type diabetes
- cervical cancer screening
- electronic health record
- physical activity
- low cost
- breast cancer risk
- insulin resistance
- public health
- machine learning
- artificial intelligence
- climate change
- clinical trial
- metabolic syndrome
- coronary artery disease
- social media
- pregnant women
- glycemic control
- cardiovascular risk factors
- high fat diet induced