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

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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

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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

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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

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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

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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

Urine test for cancer biomarkers

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Minoru Sakairi and Hitachi scientists have developed a urine test for early cancer detection.

5,000 types of metabolites can be analyzed for cancer biomarkers in urine.  The team began a study three years ago, resulting in the identification of 30 metabolites that can be used to discriminate between healthy people and cancer patients.  Further validation studies will begin in September at Nagoya University.

According to Sakairi:  “For the comprehensive analysis of urine metabolites, we used a liquid chromatograph/mass spectrometer (LC/MS). Taking measurements with an LC/MS, and focusing on differences in the water-and fat-solubility of metabolites so as to optimize measurement conditions, we were able to detect over 1,300 metabolites in the urine samples. Using 30 biomarkers from among these, a look at their measured values for 15 cases each of breast cancer patients, colorectal cancer patients, and healthy subjects showed that we had made a breakthrough in being able to discriminate the difference between cancer and not cancer.”


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

TMS + VR for sensory, motor skill recovery after stroke

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EPFL’s Michela Bassolino has used transcranial magnetic stimulation to create hand sensations when combined with VR.

By stimulating the motor cortex,  subjects’ hand muscles  were activated, and involuntary short movements were induced.

In a recent study, when subjects observed a virtual hand moving at the same time and in a similar manner to their own during TMS, they felt that a virtual hand was a controllable body part.

25 of 32 participants experienced the effect within two minutes of stimulation. Bassolino believes that the effect may also be achieved through less immersive video.

The technology could  help patients recover sensory and motor skills after a stroke — and also be used as a gaming enhancement.


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