Join ApplySci at Wearable Tech + Digital Health + Neurotech Silicon Valley on February 26-27, 2018 at Stanford University, featuring: Vinod Khosla – Justin Sanchez – Brian Otis – Bryan Johnson – Zhenan Bao – Nathan Intrator – Carla Pugh – Jamshid Ghajar – Mark Kendall – Robert Greenberg
Ipsihand, developed by Eric Leuthardt and Washington University colleagues, is a brain controlled glove that helps reroute hand control to an undamaged part of the brain. The system uses a glove or brace on the hand, an EEG cap, and an amplifier.
One’s hands are controlled by the opposite side of the brain. If one hemisphere is damaged, it is difficult to control the other hand.
According to Leuthard, the idea of Ipsihand is that if one can “couple those motor signals that are associated with moving the same-sided limb with the actual movements of the hand, new connections will be made in your brain that allow the uninjured areas of your brain to take over control of the paralyzed hand.”
Ipsihand’s cap detects intention signals to open or close the hand, then the computer amplifies them. The brace then opens or closes in a pincer-like grip with the hand inside, bending the fingers and thumb to meet.
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
Georgia Tech’s Ayanna Howard has developed Darwin, a socially interactive robot that encourages children to play an active role in physical therapy.
Darwin is still evolving (pun intended) and has not yet been commercialized.
At MIT, Newman Lab researcher Hermano Igo Krebs has been using robots for gait and balance neurorehabilitation in stroke and cerebral palsy patients since 1989. Krebs’s technology continues to be incorporated into Burke Rehabilitation hospital treatment plans.
UNC and NC State researchers have developed a promising, self-regulating, Heparin releasing patch, meant to optimize levels of the blood thinner in one’s body. It has only been tested on animals, but was found to be more effective at preventing thrombosis than traditional drug delivery methods.
Current protocol requires regular blood testing, to prevent hemorrhaging from a too-high dose, or, of course, thrombosis from an inadequate one.
The patch uses microneedles made of a polymer that consists of hyaluronic acid and Heparin. It responds to thrombin, an enzyme that initiates blood clotting. When elevated thrombin levels come into contact with a microneedle, the enzymes break the amino acid chains that bind the Heparin to the HA, releasing the Heparin into the blood stream.
ApplySci’s 6th Wearable Tech + Digital Health + NeuroTech Silicon Valley – February 7-8 2017 @ Stanford | Featuring: Vinod Khosla – Tom Insel – Zhenan Bao – Phillip Alvelda – Nathan Intrator – John Rogers – Roozbeh Ghaffari –Tarun Wadhwa – Eythor Bender – Unity Stoakes – Mounir Zok – Krishna Shenoy – Karl Deisseroth – Shahin Farshchi – Casper de Clercq – Mary Lou Jepsen – Vivek Wadhwa – Dirk Schapeler – Miguel Nicolelis
His vision is that “instead of performing exercises in an abstract situation at the clinic, patients will be able to integrate them into their daily life at home, supported by a robot.” He observes that existing exoskeletons are heavy, rendering patients unable to lift their hands. They also have difficulty feeling objects and exerting the right amount of force. To address this, the palm of the hand is left free in the new device.
Gassert’s Kyushu University colleague Jumpei Arata developed a mechanism for the finger featuring three overlapping leaf springs. A motor moves the middle spring, which transmits the force to the different segments of the finger through the other two springs. The fingers thus automatically adapt to the shape of the object the patient wants to grasp.
To reduce the weight of the exoskeleton, motors are placed on the patient’s back and force is transmitted using a bicycle brake cable. ApplySci hopes that the size and weight of the motor can be reduced, allowing it to be integrated into the exoskeleton in its next phase.
Gassert wants to make the exoskeleton thought controlled, and is using MRI and EEG to detect, in the brain, a patient’s intention to move his or her hand, and communicating this to the device.
ApplySci’s 6th Wearable Tech + Digital Health + NeuroTech Silicon Valley – February 7-8 2017 @ Stanford | Featuring: Vinod Khosla – Tom Insel – Zhenan Bao – Phillip Alvelda – Nathan Intrator – John Rogers – Mary Lou Jepsen – Vivek Wadhwa – Miguel Nicolelis – Roozbeh Ghaffari – Unity Stoakes – Mounir Zok – Krishna Shenoy
MedyMatch uses big data and artificial intelligence to improve stroke diagnosis, with the goal of faster treatment.
Patient CT photos are scanned and immediately compared with hundreds of thousands of other patient results. Almost any deviation from a normal CT is quickly detected.
With current methods, medical imaging errors can occur when emergency room radiologists miss subtle aspects of brain scans, leading to delayed treatment. Fast detection of stroke can prevent paralysis and death.
The company claims that it can detect irregularities more accurately than a human can. Findings are presented as 3D brain images, enabling a doctor to make better informed decisions. The cloud-based system allows scans to be uploaded from any location.
Wearable Tech + Digital Health San Francisco – April 5, 2016 @ the Mission Bay Conference Center
NeuroTech San Francisco – April 6, 2016 @ the Mission Bay Conference Center
Wearable Tech + Digital Health NYC – June 7, 2016 @ the New York Academy of Sciences
NeuroTech NYC – June 8, 2016 @ the New York Academy of Sciences
Samsung’s Early Detection Sensor & Algorithm Package (EDSAP), developed by Se-hoon Lim, is meant to detect early signs of stroke.
A multiple sensor headset records electrical impulses in the brain, algorithms determine the likelihood of a stroke in one minute, and results are presented in a mobile app. EDSAP can also analyze stress and sleep patterns, and potentially be used to monitor heart activity. The company believes that the system can one day be built into one’s own glasses.
Medfield Diagnostics and Chalmers University have developed “Strokefinder,” a microwave helmet that quickly determines whether a person has had a stroke, enabling early and appropriate treatment. It has been tested on 45 patients.
The helmet uses microwave typography to determine whether a stroke is caused by a clot or bleeding. Strokes caused by clots require a drug to dissolve the clot within 4.5 hours. Less than 10% of patients diagnosed by CT or MRI get anti-clotting drugs on time, as too much time often elapses between a patient’s hospital arrival and a diagnostic scan. Strokes caused by bleeding require different treatment.
An early prototype involved a modified bike helmet and was able to differentiate between the two types of stroke accurately some of the time. The team has since refined the device, building a custom helmet that better adapts to different skulls. The plan is to carry out a large scale study in order to improve the predictive power of the algorithms.
Case Western‘s Michael Bruckman and colleagues have developed a multifunctional nanoparticle that pinpoints blood vessel plaques caused by atherosclerosis using MRI. The goal is to create a non-invasive method of identifying heart attack and stroke causing plaques vulnerable to rupture, in time for treatment.
Currently doctors can only identify narrowing blood vessels caused by plaque accumulation via incision and the insertion of a catheter inside a blood vessel in the arm, groin or neck. The catheter emits a dye that enables X-rays to show the narrowing.
The researchers found that a nanoparticle built from a rod-shaped virus, commonly found on tobacco, locates and illuminates plaque in arteries more effectively, with a fraction of the dye. The tailored nanoparticles target plaque biomarkers, opening the possibility that particles can be programmed to identify vulnerable plaques from stable. Untargeted dyes alone cannot accomplish this.
Sun Yat-sen University researchers claim that Kinect based virtual reality training could promote the recovery of upper limb motor function in subacute stroke patients, and brain reorganization by Kinect based training may be linked to the contralateral sensorimotor cortex. They have completed a study in which they located the target brain region for Kinect based intervention and preliminarily explored the mechanism of the system for physical rehabilitation of upper limb dysfunction.