Category Archives: Brain

David Axelrod: VR in healthcare & the Stanford Virtual Heart | ApplySci @ Stanford

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David Axelrod discussed VR-based learning in healthcare, and the Stanford Virtual Heart, at ApplySci’s recent Wearable Tech + Digital Health + Neurotech conference at Stanford;


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 JULY 6th

Combined BCI + FES system could improve stroke recovery

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Jose Millan and EPFL colleagues have combined a brain computer interface with functional electrical stimulation in a system that, in a study, showed the ability to enhance the restoration of limb use after a stroke.

According to Millan: “The key is to stimulate the nerves of the paralyzed arm precisely when the stroke-affected part of the brain activates to move the limb, even if the patient can’t actually carry out the movement. That helps re-establish the link between the two nerve pathways where the signal comes in and goes out.”

27 patients with a similar lesion that resulted in moderate to severe arm paralysis following a stroke participated in the trial. Half were treated with the dual-therapy approach, and reported clinically significant improvements.  A BCI system  enabled the researchers to pinpoint where the electrical activity occurred in the brain when they tried to extend their hands. Each time the electrical activity was identified, the system stimulated the muscle controlling the corresponding wrist and finger movements.

The control group received FES only, and had their arm muscles stimulated randomly. This allowed the scientists to understand how much additional motor function improvement could be attributed to the BCI system.


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 JUNE 29TH

Tony Chahine on human presence, reimagined | ApplySci @ Stanford

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Myant‘s Tony Chahine reimagined human presence at ApplySci’s recent Wearable Tech + Digital Health + Neurotech conference at Stanford:


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 JUNE 29TH

Thought, gesture-controlled robots

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MIT CSAIL’s Daniela Rus has developed an EEG/EMG robot control system based on brain signals and finger gestures.

Building on the team’s previous brain-controlled robot work, the new system detects, in real-time, if a person notices a robot’s error. Muscle activity measurement enables the use of hand gestures to select the correct option.

According to Rus: “This work, combining EEG and EMG feedback, enables natural human-robot interactions for a broader set of applications than we’ve been able to do before using only EEG feedback. By including muscle feedback, we can use gestures to command the robot spatially, with much more nuance and specificity.”

The researchers used  a humanoid robot from Rethink Robotics, while a human controller wore electrodes on her or his head and arm.

Human supervision  increased the choice of correct target from 70 to 97 per cent.

The goal is system that can be used for people with limited mobility or language disorders.

Click to view CSAIL video


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 22nd

Phillip Alvelda: More intelligent; less artificial | ApplySci @ Stanford

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Phillip Alvelda discussed AI and the brain at ApplySci’s recent Wearable Tech + Digital Health + Neurotech Silicon Valley conference at Stanford:


Dr. Alvelda will join us again at Wearable Tech + Digital Health + Neurotech Boston, on September 24, 2018 at the MIT Media Lab.  Other speakers include: Rudy Tanzi – Mary Lou Jepsen – George ChurchRoz PicardNathan IntratorKeith JohnsonJuan EnriquezJohn MattisonRoozbeh GhaffariPoppy Crum Marom Bikson

REGISTRATION RATES INCREASE JUNE 22nd

Bob Knight on decoding language from direct brain recordings | ApplySci @ Stanford

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Berkeley’s Bob Knight discussed (and demonstrated) decoding language from direct brain recordings at ApplySci’s recent Wearable Tech + Digital Health + Neurotech Silicon Valley at Stanford:


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

Join Apply Sci at the 10th Wearable Tech + Digital Health + Neurotech Silicon Valley conference on February 21-22, 2019 at Stanford University

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

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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

EEG determines SSRI effectiveness in depression

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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

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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