All posts by lisaweiner

BP cuff + accelerometer detect early preeclampsia

FacebooktwitterlinkedinFacebooktwitterlinkedin

Purdue’s Craig Goergen has developed a sensor-based supine pressor test to detect preeclampsia.

The technology measures and notes the difference between a pregnant woman’s diastolic blood pressure while in two different positions, using a BP wrist cuff and accelerometer on the stomach.

The two devices are connected to an app which guides the wearer, and ensures that the readings are taken in correct positions. Diastolic pressure differences are the definitive way to detect preecamplsia, which according to the researchers, can be seen and treated earlier with the simple system.

Click to view Purdue video


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24, 2019 at the MIT Media Lab.  Speakers include:  George ChurchRoz PicardNathan IntratorKeith JohnsonJuan EnriquezJohn MattisonRoozbeh GhaffariPoppy Crum

EEG determines SSRI effectiveness in depression

FacebooktwitterlinkedinFacebooktwitterlinkedin

UT Southwestern researchers are using EEG to determine whether an SSRI would effectively treat a person’s depression.

Part of the EMBARC project, the study tracked 300 depressed patients who were given an 8 week course of an SSRI or a placebo. EEG recordings were taken before and after the trial. Higher rACC theta activity before treatment corresponded with greater treatment response to the antidepressant.

 EMBARC director Madhukar Trivedi hopes that the EEG test, combined with his previous blood-biomarker guided drug choice work will dramatically improve accuracy in predicting whether common antidepressants will work for a patient.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24, 2018 at the MIT Media Lab.  Speakers include Roz Picard – George Church – Poppy Crum – Nathan Intrator – Roozbeh Ghaffari – John Mattison

Gait sensor could detect Alzheimer’s, identify fall risk

FacebooktwitterlinkedinFacebooktwitterlinkedin

Newcastle University’s Lynn Rochester has studied the use of wearable sensors to identify walking characteristics as clinical biomarkers for Alzheimer’s Disease.  The same sensors can detect gait changes that require intervention to prevent falls and prolong independence.

According to Rochester, “free-living gait analysis at home is particularly useful as it allows objective observation of an individual’s day-to-day activity. It also has the benefit of providing continuous data over a prolonged time that may be more sensitive than one-off assessments.”

She believes that continuous walking sensors could make clinical trials more efficient, and support clinician decisions.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24 2018 at the MIT Media Lab

Saliva-monitoring chip to track bone loss, diabetes, inflammatory markers

FacebooktwitterlinkedinFacebooktwitterlinkedin

Washington University’s Erica Lynn Scheller and Shantanu Chakrabartty are developing a gum or dental device-worn sensor to detect early signs of  disease by analyzing saliva or gingival crevicular fluid.

The sensor plus electronic chip is a few millimeters-cube in volume and measures disease-specific peptides.  A wireless ultrasound device reads the peptide levels and connects to the cloud.

The first use will be monitoring  bone breakdown during periodontitis. The goal is to track multiple inflammatory and stress markers and to monitor diabetes.

Click to view Washington University video


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24 2018 at the MIT Media Lab

Muscle-force measuring wearable

FacebooktwitterlinkedinFacebooktwitterlinkedin

University of Wisconsin’s Darryl Thelen and Jack Martin have developed a noninvasive approach to measuring tendon tension while a person is active.

Current wearables can measure movement, but not muscle force.

The technology provides insight into motor control and human movement mechanics, and can be applied in orthopedics, rehabilitation, ergonomics, and sports.

The device is mounted on skin over a tendon, lightly tapping it 50 times per second. Each tap initiates a wave in the tendon, and two miniature accelerometers determine how quickly it travels. This assesses  force via vibrational characteristics of the tendon change during loading.  Tensile stress is then measured.

It has been used to measure forces on the Achilles tendon, patellar and hamstring tendons. Changes were observed when  gait was modified, which can enable clinicians to optimize the treatment of musculoskeletal disease and injuries. It may also be useful to determine when a repaired tendon is  healed.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24, 2018 at the MIT Media Lab

AI CT analysis speeds stroke identification, treatment

FacebooktwitterlinkedinFacebooktwitterlinkedin

Viz.ai‘s algorithms analyze brain scans and immediately transfer data to ensure rapid stroke treatment. The system connects to a hospital CT and sends alerts when a suspected LVO stroke has been identified.  Radiological images are sent to a doctor’s phone.  The company claims that the median time from picture to notification is less than 6 minutes, which can be life-saving, as they also claim that standard stroke workflow is now 66 minutes. Patient transfer to  interventional centers is initiated through messaging and call capabilities connected with emergency and transportation services.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24, 2018 at the MIT Media Lab

DARPA’s Justin Sanchez on driving and reshaping biotechnology | ApplySci @ Stanford

FacebooktwitterlinkedinFacebooktwitterlinkedin

DARPA Biological Technologies Office Director Dr. Justin Sanchez on driving and reshaping biotechnology.  Recorded at ApplySci’s Wearable Tech + Digital Health + Neurotech Silicon Valley conference on February 26-27, 2018 at Stanford University.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 25, 2018 at the MIT Media Lab

Brain sensor monitors cytokines

FacebooktwitterlinkedinFacebooktwitterlinkedin

Macquarie University’s Kaixin Zhang and Ewa Goldys have developed a sensor that detects cytokines in the living brain.

The signaling molecules, secreted by glia cells, affect mood, cognition and behavior.

The optical fiber sensor’s surface is treated with a capture protein that monitors the release of cytokine molecules in discrete and targeted parts of the brain.  The goal is to understand cytokine secretion, neural circuits, and how they work together in brain health and disease.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 25, 2018 at the MIT Media Lab