Nathan Intrator on epilepsy, AI, and digital signal processing | ApplySci @ Stanford

FacebooktwitterlinkedinFacebooktwitterlinkedin

Nathan Intrator discussed epilepsy, AI and digital signal processing 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 24, 2018 at the MIT Media Lab.  Speakers include:  Mary Lou Jepsen – George ChurchRoz PicardNathan IntratorKeith JohnsonJuan EnriquezJohn MattisonRoozbeh GhaffariPoppy Crum

Ingestible “bacteria on a chip” detects blood, inflammation

FacebooktwitterlinkedinFacebooktwitterlinkedin

MIT’s Timothy Lu has developed an ingestible sensor with embedded genetically engineered bacteria to  diagnose bleeding or other gastrointestinal issues.

The “bacteria-on-a-chip” approach combines living cell sensors with ultra-low-power electronics that convert the bacterial response into a signal read by a phone.

The technology has only been tested in pigs, but shows promise in detecting gastrointestinal blood and inflammation. The researchers believe that the sensor will be able to be remain in the digestive tract for days or weeks, sending continuous signals.

Click to view MIT video


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

Cheap, noninvasive patch monitors glucose

FacebooktwitterlinkedinFacebooktwitterlinkedin

UCSD’s Joe Wang‘s needless adhesive glucose monitor has begun a phase I clinical trial.  The small patch measures insulin levels through sweat on the skin, eliminating the need for a skin prick.  The paper – tattoo is printed with two integrated electrodes that apply a small amount of electrical current.  Glucose molecules residing below the skin are forced to rise to the surface, allowing blood sugar to be measured.

Through its SENSOR study,  the team s testing the tattoo-like sensor’s accuracy, compared to a traditional glucometer. The  trial is enrolling 50 adults, ages 18 to 75, with type 1 or 2 diabetes, or diabetes due to other causes. Participants wear a sensor while fasting, and up to 2 hours after eating.

The goal is a cheap, noninvasive, discreet, user friendly glucose monitor that provides continuous measurement.  The sensor currently provides only one readout.


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

Carla Pugh on hacking healthcare with sensors | ApplySci @ Stanford

FacebooktwitterlinkedinFacebooktwitterlinkedin

Carla Pugh discussed hacking healthcare with sensors 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 24, 2018 at the MIT Media Lab.  Speakers include:  Mary Lou Jepsen – George ChurchRoz PicardNathan IntratorKeith JohnsonJuan EnriquezJohn MattisonRoozbeh GhaffariPoppy Crum

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, 2018 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