Technology Description
· Researchers at Johns Hopkins have developed a wearable patch that continuously monitors blood pressure and cerebral blood flow.
· The device harnesses photoacoustic imaging, pairing LED lights with ultrasonic detectors to monitor flow even in small vessels.
· The device simultaneously measures clinical data on variables such as pulse oximetry, integrates waveform analysis to estimate parameters such as stroke volume, and utilizes machine learning to monitor for early warning signs.
Unmet Need
· Continuous blood pressure data is critical for patient monitoring in both in- and outpatient settings, as static measurements may fail to capture dynamic blood pressure variation.
· Invasive monitoring via arterial catheter is the gold standard for continuous blood pressure monitoring due to its beat-to-beat accuracy. However, this approach requires frequent troubleshooting and may lead to complications (e.g., infection, arterial injuries).
· Non-invasive approaches for continuous monitoring also have significant limitations. Wave Doppler devices are bulky, expensive, and vulnerable to movement artifacts, while finger sensors are uncomfortable, unreliable in patients with impaired finger perfusion, and inaccurate.
· Therefore, there is a strong need to develop accurate methods for continuous non-invasive blood pressure monitoring to improve health outcomes through comprehensive patient data collection.
Value Proposition
· Allows for cost-effective remote patient monitoring in-home or hospital settings.
· Captures high-resolution, real-time blood flow dynamics, overcoming motion-related artifacts.
· Collects data for small vessels that cannot be well-monitored using current methods.
· Integrates multiparametric patient data to enhance clinical care.
Stage of Development
· Prototype development
Publication
N/A
