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.
Specific targeting children with cerebral palsy (who are involved in current studies), autism, or tbi, the robot is designed to function in the home, to supplement services provided by clinicians. It engages users as their human therapist would — monitoring performance, and providing motivation and feedback.In a recent experiment, motion trackers monitored user movements as Darwin offered encouragement, and demonstrated movements when they were not performed correctly. Researchers claimed that wth the exception of one case, the robot’s impact was “significantly positive.
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.
Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston
– Featuring Roz Picard, Tom Insel, John Rogers and Nathan Intrator – September 19, 2017 at the MIT Media Lab
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
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.
Wearable Tech + Digital Health NYC 2015 – June 30 @ New York Academy of Sciences
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.
Professor Vivek Prabhakaran at the University of Wisconsin is developing a device that combines a brain-computer interface with electrical stimulation of damaged muscles to help stroke patients relearn how to move limbs. Eight patients who had lost movement in one hand have been through six weeks of therapy with the device. They reported improvements in their ability to complete daily tasks.
Patients wear a cap of electrodes that picks up brain signals. Those signals are decoded by a computer. The computer sends tiny jolts of electricity through wires to sticky pads placed on the muscles of a patient’s paralyzed arm. The jolts act like nerve impulses, telling the muscles to move. A video game prompts patients to try to hit a target by moving a ball with their affected arm. Patients practice with the game for two hours, every other day.
Researchers scanned the patients’ brains before, during and a month after they finished 15 sessions with the device. The more patients practiced, the more they were able to train their brains.