Small ultrasound patch detects heart disease early

Sheng Xu, Brady Huang, and UCSD colleagues have developed a small, wearable ultrasound patch that  monitors blood pressure in arteries up to 4 centimeters under the skin.  It is meant to detect cardiovascular problems earlier, with greater accuracy

Applications include continuous blood pressure monitoring in heart and lung disease, the critically ill, and those undergoing surgery.  It could be used to measure other vital signs, but this was not studied.

The wearable measures central blood pressure, considered more accurate and better at predicting disease than peripheral blood pressure. Central blood pressure is not routinely measured, and involves a catheter inserted into a blood vessel in the arm, groin or neck, and guiding to the heart. A non-invasive method exists, but it does not produce consistently accurate readings.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24, 2018 at the MIT Media Lab.  Speakers include:  Rudy Tanzi – Mary Lou Jepsen – George ChurchRoz PicardNathan IntratorKeith JohnsonJohn MattisonRoozbeh GhaffariPoppy Crum – Phillip Alvelda Marom Bikson – Ed Simcox – Sean Lane

Continuous blood pressure monitoring glasses

Microsoft’s Glabella glasses, developed by Christian Holz and Edward Wang, will have integrated optical sensors that take pulse wave readings from three areas around the face, according to their recently granted patent.

Blood pressure is calculated by measuring the time between when blood is ejected from the heart and reaches the face. The researchers believe that the device can unobtrusively and continuously measure blood pressure.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24, 2018 at the MIT Media Lab.  Speakers include:  Rudy Tanzi – Mary Lou Jepsen – George ChurchRoz PicardNathan IntratorKeith JohnsonJuan EnriquezJohn MattisonRoozbeh GhaffariPoppy Crum – Phillip Alvelda Marom Bikson – Ed Simcox – Sean Lane

Algorithm predicts low blood pressure during surgery

UCLA’s Maxime Cannesson has developed an algorithm that, in a recent study, predicted  an intraoperative hypotensive event 15 minutes before it occurred in 84 percent of cases, 10 minutes before in 84 percent of cases, and five minutes before in 87 percent of cases.

The goal is early identification and treatment, to prevent complications, such as postoperative heart attack, acute kidney injury, or death.

The algorithm is based on recordings of the increase and decrease of blood pressure in the arteries during a heartbeat—including episodes of hypotension. For each heartbeat, the researchers were able to derive 3,022 individual features from the arterial pressure waveforms, producing more than 2.6 million bits of information. They then identified which of the features—when they happen together and at the same time—predict hypotension.

Cannesson said that the research “opens the door to the application of these techniques to many other physiological signals, such as EKG for cardiac arrhythmia prediction or EEG for brain function” and “could lead to a whole new field of investigation in clinical and physiological sciences and reshape our understanding of human physiology.”


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24, 2018 at the MIT Media Lab.  Speakers include:  Rudy Tanzi – Mary Lou Jepsen – George ChurchRoz PicardNathan IntratorKeith JohnsonJuan EnriquezJohn MattisonRoozbeh GhaffariPoppy Crum – Phillip Alvelda Marom Bikson

REGISTRATION RATES INCREASE FRIDAY, JUNE 15TH

Thin, flexible, adhesive, continuous, cuffless blood pressure sensor

Zhao Ni and Yuan-ting Zhang of the Chinese University of Hong Kong have developed an ultra-thin, waterproof, cuffless blood pressure  sensor that can be worn on the wrist, woven into clothes or bed sheets, or integrated into an earpiece. The monitor detects blood flow and monitors  health data through color reflected by skin and image depth. It provides continuous, wireless monitoring and abnormality alerts.

Professor Zhao believes that in the future, the sensor could use AI to improve itself.  She intends to  broaden its applications to include monitoring breathing rate and blood oxygen level, to also replace a finger -worn pulse oximeter. 


Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen – Daniela Rus

Preferred registration rates available through Friday, June 23rd