Posts Tagged Artificial intelligence

[WEB SITE] Personal Rehab and Recovery Through Virtual Therapy

Virtual therapy is based on research that combines leading-edge data techniques with wearable robotics, artificial intelligence and machine learning.

An engineering researcher from New Zealand’s University of Auckland has been awarded a Rutherford Discovery Fellowship.

The Associate Professor, who is developing a virtual therapy technology for personal rehabilitation, is one of eleven Fellows for 2019. The Fellowship provides NZ$ 800,000 in funding over five years.

According to a recent press release, his research combines leading-edge data techniques with wearable robotics, artificial intelligence (AI) and machine learning.

The aim is to create devices that are capable of personalising rehabilitation and recovery plans, which are cheaper and more efficient than humans.

The Problem for Personal Rehabilitation

  • Currently, rehabilitation after a medical event, such as stroke, is carried out by trained physical or occupational therapists.
  • However, much of the work is physically demanding and the cost is relatively high and time-consuming.
  • While some robotics devices used for physical rehabilitation have been developed overseas, they lag far behind what a human therapist is capable of.
  • The current technology has little or no intelligence and can only act on predefined rules. Thus, it is not tailored to individuals and does not have the ability to adapt and learn as a human therapist would.

The Solution for Personal Rehabilitation

  • The researcher’s work, meanwhile, takes a strongly data-driven approach, looking at the fundamental physiology of human movement.
  • It will build on that information in order to create individual recovery plans that take into account the effects of a diverse range of physical impairments.
  • The goal is to make real progress towards creating low-cost robotic ‘virtual therapists’ with the ability to deliver automatic but very precise treatments.
  • The Rutherford Discovery Fellowships, managed on behalf of the government by the New Zealand Royal Society Te Apārangi, aim to attract and retain talented early- to mid-career researchers by helping them establish a track record for future research leadership.
  • The high costs of healthcare not just in New Zealand but around the world mean that progress in the area of medical technologies and personalised therapies and treatments needs to be prioritised.

Stressbuster

In other news, the University was the site of a unique digital treasure hunt recently to mark Stress Less Week.

Stress Less week was held 7 to 11 October as thousands of students prepare to head into study break and exam period.

A student start-up developed the technology used in the app-based game, which challenged the students to unlock and solve riddles on the City Campus to find secret locations and discover rewards.

The start-up’s Founder explained that fun is the ultimate antidote to stress.

They provided an experience that facilitated getting out and connecting with peers, before it gets too close to exams and after the mid-semester wave of assignments.

They are passionate about using new technologies to turn cities into playgrounds, developing a portfolio of technologies in the process.

These technologies include holograms, face-recognition software and transparent glass screens, which they draw on to design interactive games.

Using the campus for a big treasure hunt is a great way to test the waters before thousands of dollars are put into more commercial ventures, and scale-up the app to use in different situations.

 

via Personal Rehab and Recovery Through Virtual Therapy

, , , , ,

Leave a comment

[WEB SITE] AI helps identify patients in need of advanced care for depression

Depression is a worldwide health predicament, affecting more than 300 million adults. It is considered the leading cause of disability and contributor to the overall global burden of disease. Detecting people in need of advanced depression care is crucial.

Now, a team of researchers at the Regenstrief Institute found a way to help clinicians detect and identify patients in need of advanced care for depression. The new method, which uses machine learning or artificial intelligence (AI), can help reduce the number of people who experience depressive symptoms that could potentially lead to suicide.

The World Health Organization (WHO) reports that close to 800,000 people die due to suicide each year, making it the leading cause of death among people between the ages of 15 and 29 years old.

Major depression is one of the most common mental illness worldwide. In the United States, an estimated 17.3 million adults had at least one major depressive episode, accounting to about 7.1 percent of all adults in the country.

Image Credit: Zapp2Photo / Shutterstock

Image Credit: Zapp2Photo / Shutterstock

Predicting patients who need treatment

The study, which was published in the Journal of Medical Internet Research, unveils a new way to determine patients who might need advanced care for depression. The decision model can predict who might need more treatment than what the primary care provider can offer.

Since some forms of depression are far more severe and need advanced care by certified medical health providers, knowing who is at risk is essential. But identifying these patients is very challenging. In line with this, the researchers formulated a method that scrutinizes a comprehensive range of patient-level diagnostic, behavioral, and demographic data, including past clinic visit history from a statewide health information.

Using the data, health care providers can now build a technique on properly predicting patients in need of advanced care. The machine learning algorithm combined both behavioral and clinical data from the statewide health information exchange, called the Indiana Network for Patient Care.

“Our goal was to build reproducible models that fit into clinical workflows,” Dr. Suranga N. Kasthurirathne, a research scientist at Regenstrief Institute, and study author said.

“This algorithm is unique because it provides actionable information to clinicians, helping them to identify which patients may be more at risk for adverse events from depression,” he added.

The researchers used the new model to train random forest decision models that can predict if there’s a need for advanced care among the overall patient population and those at higher risk of depression-related adverse events.

It’s important to consider making models that can fit different patient populations. This way, the health care provider has the option to choose the best screening approach he or she needs.

“We demonstrated the ability to predict the need for advanced care for depression across various patient populations with considerable predictive performance. These efforts can easily be integrated into existing hospital workflows,” the investigators wrote in the paper.

Identifying patients in need of advanced care is important

With the high number of people who have depression, one of the most important things to do is determine who are at a higher risk of potential adverse effects, including suicide.

Depression has different types, depending on the level of risk involved. For instance, people with mild depression forms may not need assistance and can recover faster. On the other hand, those who have severe depression may require advanced care aside from what primary care providers can offer.

They may need to undergo treatment such as medications and therapies to improve their condition. Hence, the new method can act like a preventive measure to reduce the incidence of adverse events related to the condition such as suicide.

More importantly, training health care teams to successfully identify patients with severe depression can help resolve the problem. With the proper application of the novel technique, many people with depression can be treated accordingly, reducing serious complications.

Depression signs and symptoms

Health care providers need to properly identify patients with depression. The common signs and symptoms of depression include feelings of hopelessness and helplessness, loss of interest in daily activities, sleep changes, irritability, anger, appetite changes, weight changes, self-loathing, loss of energy, problems in concentrating, reckless behavior, memory problems, and unexplained pains and aches.


Journal reference:

Suranga N Kasthurirathne, Paul G Biondich, Shaun J Grannis, Saptarshi Purkayastha, Joshua R Vest, Josette F Jones. (2019). Identification of Patients in Need of Advanced Care for Depression Using Data Extracted From a Statewide Health Information Exchange: A Machine Learning Approach. Journal of Medical Internet Research. https://www.jmir.org/2019/7/e13809/


via AI helps identify patients in need of advanced care for depression

, , , , , , , , ,

Leave a comment

[NEWS] SofBoost and Scott Verner Launch Rehab Tools Using Artificial Intelligence

Published on 

RehabBoost

SofBoost, an artificial intelligence (AI) body recognition technology company, launches RehabBoost in partnership with healthcare entrepreneur Scott Verner.

Together, Miami-based SofBoost and Verner will work to develop a comprehensive library of rehabilitation tools for medical application, using machine learning and artificial intelligence technology, according to a media release.

“We are thrilled to be able to have the opportunity to disrupt the healthcare and rehabilitation space, as an extension of our broader mission to transform the way movements are learned and practiced,” says SofBoost CEO, Paul Jaure, in the release.

“I’ve closely followed SofBoost’s demonstrated success in the machine learning space, and believe our collaboration will make an important contribution to the healthcare industry,” states Verner, also currently the President and CEO of TRIVIDIA Health, as well as the Chairman of The Job Creators Network Foundation.

“This project aligns with my personal mission to create new business models and strategies that transform the way patient needs are fulfilled, and I’m excited to see our vision come to life.”

SofBoost’s patent-pending technology compares user body positions with predetermined methodologies, drawing on proprietary algorithms to produce personalized corrective analysis in real time. This first-of-its-kind product will offer instant and personalized rehabilitation support from anywhere, through an easy-to-use app interface, the release continues.

RehabBoost marks the company’s first expansion to other categories, and is in line with its growth strategy. SofBoost is actively seeking strategic partnerships to expand into various swing sports, fitness and other line extensions, according to the company.

[Source(s): SofBoost, Business Wire]

 

via SofBoost and Scott Verner Launch Rehab Tools Using Artificial Intelligence – Rehab Managment

, , , , , , ,

Leave a comment

[NEWS] Robotic Rehab Aims for the Home Market in Q3

Published on 

MotusNova

Motus Nova is expanding its list of partner hospitals and clinics using its FDA-approved robotic stroke therapy system. It also plans to introduce its system to the consumer market for home use in Q3 2019.

Twenty-five hospitals in the Atlanta area within Emory Healthcare, the Grady Health System, and the Wellstar Health System are now using the Motus Nova rehabilitation therapy system, which is designed to use Artificial Intelligence (AI) to accelerate recovery from neurological injuries such as strokes.

The system features a Hand Mentor and Foot Mentor, which are sleeve-like robots that fit over a stroke survivor’s impaired hand or foot. Equipped with an active-assist air muscle and a suite of sensors and accelerometers, they provide clinically appropriate assistance and resistance while individual’s perform the needed therapeutic exercises.

A touchscreen console provides goal-directed biofeedback through interactive games—which Motus Nova calls “theratainment”—that make the tedious process of neuro rehab engaging and fun.

“It’s a system that has proven to be a valuable partner to stroke therapy professionals, where it complements skilled clinical care by augmenting the repetitive rehabilitation requirements of stroke recovery and freeing the clinician to do more nuanced care and assessment,” says Nick Housley, director of clinical research for Atlanta-based Motus Nova, in a media release.

“And while we continue to fill orders for the system to support therapy in the clinic and hospital, we also are looking to use our system to fill the gap patients often experience in receiving the needed therapy once they go home.”

Clinical studies show that neuroplasticity begins after approximately many 10’s to 100’s of hours of active guided rehab. The healing process can take months or years, and sometimes the individuals might never fully recover. Yet the typical regimen for stroke survivors is only two to three hours of outpatient therapy per week for a period of three to four months.

“These constraints were instituted by the Centers for Medicare & Medicaid Services (CMS) in determining Medicare reimbursement without a full understanding of the appropriate dosing required for stroke recovery, and many private insurers have adopted the policy, as well,” states David Wu, Motus Nova’s CEO.

Motus Nova plans to offer a more practical model, the release continues.

“By making the system available for home use at a reasonable weekly rate as long as the patient needs it, the individual can perform therapy anytime,” Wu adds. “A higher dosage of therapy can be achieved without the inconvenience of scheduling appointments with therapists or traveling to and from a clinic, and without the high cost of going to an outpatient center every time the individual wants to do therapy.”

While the system gathers data about individual performance, AI tailors the regimen to maximize user gains, discover new approaches, minimize side effects and help the stroke survivor realize his or her full potential more quickly.

“By optimizing factors such as frequency, intensity, difficulty, encouragement, and motivation, the AI system builds a personalized medicine plan uniquely tailored to each individual user of the system,” Housley comments.

“Our system is durable, too, proven in clinical trials to deliver an engaging physical therapy experience over thousands of repetitions. We look forward to making it available on a much wider scale in the coming months.”

[Source(s): Motus Nova, PR Newswire]

 

via Robotic Rehab Aims for the Home Market in Q3 – Rehab Managment

, , , , , , , , , , ,

Leave a comment

[WEB PAGE] When Will There Ever be a Cure for Epilepsy?

The three-pound organ that serves as command central for the human organism is certainly a marvel, just by virtue of the fact that the brain can appreciate its own awesomeness, even if it hasn’t quite perfected the flying car or even self-driving cars. Yet. Companies developing brain-computer interface technology are enabling humans to do things like send commands to computers by just flexing a bit of muscle. Still, there is much we don’t know about ourselves, no matter how much telepsychiatry we do. And that applies especially to medical conditions that affect the brain like epilepsy, a neurological condition for which there is no cure.

What is Epilepsy?

While most of us are probably familiar with some Hollywood-ized version of epilepsy in which someone starts flailing around after being hit by strobe lights on the disco floor, the reality is that epilepsy refers to a large group of neurological disorders that generally involve chronic, spontaneous seizures that vary greatly in how they manifest. The causes of epilepsy are also all over the place, from traumatic brain injuries and stroke to viral and bacterial infections to genetics.

A new set of classifications for epilepsy came out in 2017.

It is considered a brain disorder, according to the U.S. Centers for Disease Control (CDC), though some researchers have suggested it could be classified as a neurodegenerative disease like Parkinson’s or Alzheimer’s. In fact, there is research that suggests a genetic link between epilepsy and neurodegenerative diseases.

Not surprisingly, many of the companies developing therapies for neurodegenerative diseases are also working on treatments for epilepsy and vice versa. For example, a new, well-funded joint venture involving Pfizer (PFE) and Bain Capital called Cerevel, which we profiled in our piece on Parkinson’s disease, is also in advanced clinical trials for an epileptic drug. Its GABA A positive modulator drug candidate targets GABA (Gamma-Aminobutyric Acid) neurotransmitters that block impulses between nerve cells in the brain, helping keep the nervous system chill.

Impacts of Epilepsy

More than 50 million people worldwide have epilepsy, making it one of the most common neurological diseases globally, according to the World Health Organization (WHO). The CDC estimates about 3.4 million Americans live with the condition. Globally, an estimated 2.4 million people are diagnosed with epilepsy each year. Interestingly, the disorder seems to target those who can least afford it: WHO said nearly 80% of people with epilepsy live in low- and middle-income countries.

Impacts of epilepsy graphic

A 2015 study of a bunch of other studies that estimated the cost of epilepsy in the United States found that epilepsy-specific costs probably average out to about $10,000 based on the variety of ranges, which means epilepsy costs the United States healthcare system about $34 billion, though the numbers are widely debated. Conversely, WHO says low-cost treatments are available, with daily medication coming as cheaply as $5 per year, so another win for the U.S. healthcare system.

Treatments for Epilepsy

There are more than 20 antiepileptic drugs used to treat epilepsy, usually to help prevent or slow the occurrence of seizures. Other therapies include surgery and electroceutical treatment in which electrical stimulation is applied, usually to the vagus nerve, the longest cranial nerve in the body. While many find relief from one or more of these options, a third of those who suffer from epilepsy are not able to manage their seizures, according to the U.S. National Institutes of Health (NIH). Below we take a look at a range of innovative therapies designed to detect, stop, or find a cure for epilepsy.

Brain Stimulation Therapies

In our article on electroceutical treatments, we highlighted a London company called LivaNova (LIVN) that offers an implantable Vagus Nerve Stimulation (VNS) therapy that has been approved by the U.S. Food and Drug Administration (FDA) to help treat those with partial seizures who do not respond to seizure medications. A medical device company with a lengthy track record of returning value to investors, Medtronic (MDT) got FDA pre-market approval last year for its Deep Brain Stimulation (DBS) therapy for use in reducing partial-onset seizure for those who have proven to not respond to three or more antiepileptic medications. DBS therapy delivers controlled electrical pulses to an area in the brain called the anterior nucleus of the thalamus, which is part of a network involved in seizures. Yet another company offering a variation of brain stimulation therapy is NeuroPace, which markets its responsive neurostimulation device, or RNS system, as “the first and only brain-responsive neurostimulation system designed to prevent epileptic seizures at their source.”

Artificial Intelligence to Detect, Predict, and Control Epilepsy

The NIH is funding further research into implantable devices that can detect, predict, and stop a seizure before it happens, “working closely with industry partners to develop pattern-recognition algorithms,” which sounds an awful lot like artificial intelligence and machine learning will be at the forefront of some future diagnostics and treatment. AI in healthcare has been an ongoing theme around here, with a recent dive into AI and mental health. Back to AI and epilepsy: A group of neurologists at the Medical University of South Carolina developed a new method based on artificial intelligence to predict which patients will see success with surgical procedures designed to stop seizures. Sounds like a great idea to learn beforehand if it’s necessary to crack open your skull.

Click for company websiteA Boston area startup called Empatica, spun out from MIT in 2011, has raised $7.8 million for a smartwatch that detects possible seizures by monitoring subtle electrical changes across the surface of the skin. Other methods normally rely on electrical activity in the brain that tracks and records brain wave patterns called an electroencephalogram. Empatica’s seizure detection algorithm, on the other hand, can detect complex physiological patterns from electrodermal activity that is most likely to accompany a convulsive seizure. Psychology Today reportedthat the device, Embrace Watch, received FDA approval earlier this year for seizure control in children after getting the green light for the technology for adults in 2018.

The Empatica smartwatch can detect electrical currents in the skin to predict the onset of an epileptic seizure.

Click for company websiteAI and drug discovery for better epileptic drug candidates is yet another application that we would expect to see grow in the coming years. Silicon Valley-based startup System1 Biosciences raised $25 million last year, which included Pfizer among its dozen investors. System1 builds a sort of brain model for testing drug candidates using stem cell lines derived from patients with brain disease. The company uses robotic automation to develop these three-dimensional cerebral organoids, allowing it to generate huge datasets in a relatively short amount of time, then applying “advanced data analysis” (also AI?) to detect patterns that might match the characteristics of a neurological disease (what it refers to as deep phenotypes) such as epilepsy with novel treatments.

Cannabis for Controlling Seizures

We’ve written extensively about the suddenly booming hemp CBD market, noting that the FDA approved a CBD-based drug for epilepsy last year in our recent article on the best certified CBD oils on the market. However, we’ve only briefly profiled the company behind Epidiolex for treating rare forms of epilepsy, GW Pharmaceuticals (GWPH). Sporting a market cap just south of $5 billion, GW Pharmaceuticals has taken in about $300 million in post-IPO equity since our article, bringing total post-IPO equity funding to about $568 million. Aside from its successful epileptic drug, GW also developed the world’s first cannabis-based prescription medicine for the treatment of spasticity due to multiple sclerosis that is available in 25 countries outside the United States.

The forms of epilepsy that GW Pharmaceuticals can treat or can potentially treat.

Back on the epilepsy side, Epidiolex has been approved for two rare forms of epilepsy, with clinical trials underway for two more rare neurological disorders associated with seizures – tuberous sclerosis complex and Rett syndrome. Also in the pipeline is a drug dubbed CBDV (GWP42006) that’s also for treating epileptic seizures, though the results of a trial last year were not encouraging. The same compound is also being investigated for autism. Be sure to check out our article on Charlotte’s Web, a CBD company that came about because of epilepsy.

Helping Cells Get Their Vitamin K

Click for company websiteNeuroene Therapeutics is a small startup spun out of the Medical University of South Carolina that recently picked up $1.5 million in funding to tests its lead drug compounds, which are analogous to the naturally occurring form of vitamin K that is essential for brain health. In particular, the lab-developed vitamin K protects the integrity of the cell’s mitochondria, which serves as a sort of power plant for brain cells, helping the neural circuit fire better. Unfortunately, you can’t get the effect from simply eating a bowl of Special K each morning covered in an organic sugar substitute, so the company is developing a method to deliver the effects directly to the brain.

A Nasal Spray to Stop Seizures

Click for company websiteFounded in 2007 near San Diego, Neurelis licenses, develops, and commercializes treatments for epilepsy and other neurological diseases. It has raised $44.8 million in disclosed funding, most coming in a $40.5 million venture round last November. The company’s flagship product is called Valtoco, a formulation that incorporates diazepam, an existing drug used to control seizures and alcohol withdrawal, with a vitamin E-based solution that is delivered using a nasal spray when a sudden seizure episode occurs. The product uses an absorption enhancement technology called Intravail developed by another San Diego area company called Aegis Therapeutics that Neurelis acquired in December last year. Neurelis submitted Valtoco to the FDA for approval in September.

Conclusions

While many people with epileptic conditions can control their seizures with many of the current medications or other therapies available now, there’s a big chunk of the population that is living with uncertainty. Considering the strong link between neurological disorders like epilepsy and certain neurodegenerative disorders, expect to see some good synergies in the next five to 10 years, especially as automation and advanced analytics using AI start connecting the dots between genetics, biochemistry, and brain disorders.

via When Will There Ever be a Cure for Epilepsy? – Nanalyze

, , , , , , , , ,

Leave a comment

[WEB SITE] Assisto & VHAB will dramatically change how people with neuromuscular disabilities communicate

April 4, 2019

 

In our series #TechThursdays, we bring you news about Virtual Rehabilitation (VHAB) and Assisto devices. VHAB, which is based on virtual reality and Assisto, which is on artificial intelligence, are targeted at people with neuromuscular disabilities.

Tech giant Tata Consultancy Services (TCS) are looking to enable people with neuromuscular disabilities in a big way with VHAB (Virtual Rehabilitation) and Assisto. The two devices use the latest available technologies to enhance communication skills.

Assisto addresses the communication difficulties that many people with cerebral palsy face by tuning their voices for better clarity. This is achieved with Algorithm, a speech synthesis. So, when the user speaks, the listener will hear a clearer enunciation.

VHAB, on the other hand, us targeted at children with neuromuscular disabilities like cerebral palsy and autism. Many children diagnosed with disabilities are put through rigorous physiotherapy sessions which can be tiring. VHAB makes these sessions game-based with the help of virtual reality. Gesture analysis, finger-mapping and motion sensors will be used for this.

Both Assisto and VHAB have been successfully tested on children at the Adarsh School in Kochi.

Ashwin KumarPrincipal, Adarsh School believes taht the devices will revolutionize the way people with neuromuscular disabilities communicate.

People with cerebral palsy and autism may have issues with their tongue muscles that can affect communication. Assisto and VHAB devices are definitely going to help them. The software that was developed by TCS was tested on two of our children and it worked really well. In their next phase of the project, they are planning to introduce this to more children and reach out to people who need it.- Ashwin Kumar, Principal, Adarsh School

These devices will also make day-to-day tasks also easier for children with neuromuscular disabilities. The team fine-tuned the devices over three years.

“They provide a gameified app platform and a game environment is created for the user”, says Robin Tommy one of the members of the team that worked on developing them. “It is a combination of physical and game therapies and pain-free as well so kids would love it. The devices aim to enable movements for the user and motivate them to do daily activities with ease. It is mainly based on gesture and motion”.

Seema LalCo-founder of TogetherWeCan, a well known parents supports group in Kerala, believes that technologies like these will be game changers for people with disabilities.

‘We often talk about how technology can be a curse when it comes to things like game addiction and so on. At the same time, it can be a boon for children with neuromuscular disabilities. The United Nations is already talking about the benefits of assistive technology for people with disabilities, and in enabling them to participate actively in many things. I believe this new initiative from TCS is brilliant. Communication is the key for any person and technology is truly a boon”, says Lal.

This is a CSR project of TCS and the great news is that it plans to look at ways to introduce Assisto and VHAB in other schools as well as NGOs. VHAB was recently launched at the ZEP Rehabilitation Centre in Pune,

via Assisto & VHAB will dramatically change how people with neuromuscular disabilities communicate : Newz Hook – Changing Attitudes towards Disability

, , , , , , ,

Leave a comment

[CES 2019] Medical Technology Making Inroads at CES – Augmented reality virtual caregiver, Wearable fitness tracker and Restoring Balance

Although TVs and other consumer electronic gadgets continue to occupy center stage at the Consumer Electronics Show, this year’s showcase in Las Vegas will also feature a number of products and technologies in the healthcare area. While consumer-oriented products such as Fitbit immediately come to mind, many of the technological innovations at CES combine hardware and artificial intelligence (AI) to monitor personal health and in some cases aid their recovery from diseases or falls.

One interesting technology is Addison Care™, an augmented reality virtual caregiver from SameDay Security Inc. that engages aging and chronically ill clients throughout the home to supplement their care and provide various health and safety features. Designed to appear on 15-in. monitors, Addison Care™ (Figure 1) carries on live two-way conversations with users, monitoring their activities around the clock.

 

Flint Rehab, a neuro-rehabilitation device company, is showing its MiGo wearable fitness tracker (Figure 2) . The device is reportedly the first commercially available wearable activity tracker specifically designed for stroke survivors. MiGo tracks upper extremity activity—in addition to walking—and is optimized for the movement patterns performed by individuals with stroke. The device is accompanied by a smartphone app that provides motivational support through digital coaching, progressive goal setting, and social networking with other stroke survivors.

According to the company, the device uses deep learning algorithms to measure the amount of “learned non-use,” where stroke survivors neglect to use their impaired arm or leg, causing their brain to lose the ability to control those limbs altogether. To speed recovery, the device encourages patients to use their impaired limbs every day, enabling them to regain their lost abilities over time. It provides them with an easy-to-understand rep count throughout the day and sets an intelligent activity goal that updates every day based on the wearer’s actual movement ability, Patients are encouraged and rewarded for meeting goals.

 

Figure 2: The MiGo wearable fitness tracker helps stroke survivors regain use of impaired body limbs. Image Source: Flint Rehab

Restoring Balance

Scale-1 Portal is unveiling MoveR, an applications for treating balance disorders. Designed for vestibular rehabilitation therapy, the technology transports patients in virtual scenarios controlled live by a health care professional (see video). It gives patients an immersive experience without any headset and without carrying a motion capture device. MoveR offers two experiences immersing the user in a virtual environment with only a pair of 3D glasses.

Using a touch screen with a simple and clear interface, the health care professional can directly control these scenarios in order to adapt them to the patient. Dedicated to reducing visual dependence in disorders of the balancing system, the two experiments will generate a sensory conflict in order to make greater use of somesthesia and the vestibular system.

One of these immersive experiences also encourages the user to perform movements in response to the physician’s choices. This means, for example, trying to catch virtual objects or avoid obstacles in a scrolling path.

 

 

AerBetic Inc. is demonstrating a non-invasive, wearable diabetes alert system containing nanosensors that detect gases, given off through breath or skin, that are symptomatic of high or low blood sugar. The device will pair with smartphone apps, aiding the ability to push alerts to patients and caregivers.

According to AerBetic CEO Arnar Thors, the device was inspired by his family pet, a yellow Labrador retriever. The sensors will use patient data and feedback to improve and fine tune over time, Thors says, using machine learning and artificial intelligence to increase fidelity at the individual user level and network-wide.

The device is in the final stages of development, with testing slated to begin the first quarter of this year.

 

via Medical Technology Making Inroads at CES

, , , , , , ,

Leave a comment

[WEB PAGE] Reconnecting the Disconnected: Restoring Movement in Paralyzed Limbs – Video

"Moving an arm can involve more than 50 different muscles," UA professor Andrew Fuglevand said. "Replicating how the brain naturally coordinates the activities of these muscles is extremely challenging."

“Moving an arm can involve more than 50 different muscles,” UA professor Andrew Fuglevand said. “Replicating how the brain naturally coordinates the activities of these muscles is extremely challenging.”

UA professor Andrew Fuglevand is using artificial intelligence to stimulate multiple muscles to elicit natural movement in ways previous methods have been unable to do.
Dec. 20, 2018
Andrew Fuglevand

Andrew Fuglevand

Scientists now know that the brain controls movement in people by signaling groups of neurons to tell the muscles when and where to move. Researchers also have learned it takes a complex orchestration of many signals to produce even seemingly simple body movements.

If any of these signals are blocked or broken, such as from a spinal cord injury or stroke, the messages from the brain to the muscles are unable to connect, causing paralysis. The person’s muscles are functional, but they no longer are being sent instructions.

Andrew Fuglevand, professor of physiology at the University of Arizona College of Medicine – Tucson and professor of neuroscience at the UA College of Science, has received a $1.2 million grant from the National Institutes of Health to study electrical stimulation of the muscles as a way to restore limb movements in paralyzed individuals. Fuglevand’s goal is to restore voluntary movement to a person’s own limbs rather than relying on external mechanical or robotic devices.

Producing a wide range of movements in paralyzed limbs has been unsuccessful so far because of the substantial challenges associated with identifying the patterns of muscle stimulation needed to elicit specified movements, Fuglevand explained.

“Moving a finger involves as many as 20 different muscles at a time. Moving an arm can involve more than 50 different muscles. They all work together in an intricate ‘dance’ to produce beautifully smooth movements,” he said. “Replicating how the brain naturally coordinates the activities of these muscles is extremely challenging.”

Recent advances in “machine learning,” or artificial intelligence, are making the impossible possible.

Fuglevand, who also is an affiliate professor of biomedical engineering and teaches neuroscience courses at the UA, is employing machine learning to mimic and replicate the patterns of brain activity that control groups of muscles. Tiny electrodes implanted in the muscles replay the artificially generated signals to produce complex movements.

“If successful, this approach would greatly expand the repertoire of motor behaviors available to paralyzed individuals,” he said.

“More than 5 million Americans are living with some form of paralysis, and the leading causes are stroke and spinal injury,” said Nicholas Delamere, head of the UA Department of Physiology. “New innovations in artificial intelligence, developed by scientists like Fuglevand and his team, are allowing them to decode subtle brain signals and make brain-machine interfaces that ultimately will help people move their limbs again.”

“The headway researchers have made in our understanding of artificial intelligence, machine learning and the brain is incredible,” said UA President Robert C. Robbins. “The opportunity to incorporate AI to brain-limb communication has life-changing potential, and while there are many challenges to optimize these interventions, we are really committed to making this step forward. I am incredibly excited to track Dr. Fuglevand’s progress with this new grant.”

Research reported in this release was supported by the National Institutes of Health, National Institute of Neurological Disorders and Stroke, under grant No. 1R01NS102259-01A1. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
A version of this article originally appeared on the UA Health Sciences website:https://opa.uahs.arizona.edu/newsroom/news/2018/reconnecting-disconnected-ua-physiology-professor-receives-12m-nih-grant-use-ai

 

via Reconnecting the Disconnected: Restoring Movement in Paralyzed Limbs | UANews

, , , , , , , ,

Leave a comment

[WEB SITE] New method based on artificial intelligence may help predict epilepsy outcomes

 

Medical University of South Carolina (MUSC) neurologists have developed a new method based on artificial intelligence that may eventually help both patients and doctors weigh the pros and cons of using brain surgery to treat debilitating seizures caused by epilepsy. This study, which focused on mesial temporal lobe epilepsy (TLE), was published in the September 2018 issue of Epilepsia. Beyond the clinical implications of incorporating this analytical method into clinicians’ decision making processes, this work also highlights how artificial intelligence is driving change in the medical field.

Despite the increase in the number of epilepsy medications available, as many as one-third of patients are refractory, or non-responders, to the medication. Uncontrolled epilepsy has many dangers associated with seizures, including injury from falls, breathing problems, and even sudden death. Debilitating seizures from epilepsy also greatly reduce quality of life, as normal activities are impaired.

Epilepsy surgery is often recommended to patients who do not respond to medications. Many patients are hesitant to undergo brain surgery, in part, due to fear of operative risks and the fact that only about two-thirds of patients are seizure-free one year after surgery. To tackle this critical gap in the treatment of this epilepsy population, Dr. Leonardo Bonilha and his team in the Department of Neurology at MUSC looked to predict which patients are likely to have success in being seizure free after the surgery.

Neurology Department Chief Resident Dr. Gleichgerrcht explains that they tried “to incorporate advanced neuroimaging and computational techniques to anticipate surgical outcomes in treating seizures that occur with loss of consciousness in order to eventually enhance quality of life”. In order to do this, the team turned to a computational technique, called deep learning, due to the massive amount of data analysis required for this project.

The whole-brain connectome, the key component of this study, is a map of all physical connections in a person’s brain. The brain map is created by in-depth analysis of diffusion magnetic resonance imaging (dMRI), which patients receive as standard-of-care in the clinic. The brains of epilepsy patients were imaged by dMRI prior to having surgery.

Deep learning is a statistical computational approach, within the realm of artificial intelligence, where patterns in data are automatically learned. The physical connections in the brain are very individualized and thus it is challenging to find patterns across multiple patients. Fortunately, the deep learning method is able to isolate the patterns in a more statistically reliable method in order to provide a highly accurate prediction.

Currently, the decision to perform brain surgery on a refractory epilepsy patient is made based on a set of clinical variables including visual interpretation of radiologic studies. Unfortunately, the current classification model is 50 to 70 percent accurate in predicting patient outcomes post-surgery. The deep learning method that the MUSC neurologists developed was 79 to 88 percent accurate. This gives the doctors a more reliable tool for deciding whether the benefits of surgery outweigh the risks for the patient.

A further benefit of this new technique is that no extra diagnostic tests are required for the patients, since dMRIs are routinely performed with epilepsy patients at most centers.

This first study was retrospective in nature, meaning that the clinicians looked at past data. The researchers propose that an ideal next step would include a multi-site prospective study. In a prospective study, they would analyze the dMRI scans of patients prior to surgery and follow-up with the patients for at least one year after surgery. The MUSC neurologists also believe that integrating the brain’s functional connectome, which is a map of simultaneously occurring neural activity across different brain regions, could enhance the prediction of outcomes.

Dr. Gleichgerrcht says that the novelty in the development of this study lies in the fact that this “is not a question of human versus machine, as is often the fear when we hear about artificial intelligence. In this case, we are using artificial intelligence as an extra tool to eventually make better informed decisions regarding a surgical intervention that holds the hope for a cure of epilepsy in a large number of patients.”

 

via New method based on artificial intelligence may help predict epilepsy outcomes

, , , , , , , , , , ,

Leave a comment

[WEB SITE] Virtual reality games to help patients’ rehabilitation in UAE

The AI system is already in use in Ras Al Khaimah Physiotherapy and Sports Centre and will be rolled out soon in all ministry hospitals.

A therapist will always be present to monitor these sessions of patients.

Games developed specially for rehabilitation in physiotherapy for patients of stroke, cerebral palsy and similar conditions, will be used by the Ministry of Health and Prevention (Mohap) as it rolls out use of artificial intelligence (AI) and virtual reality (VR) in hospitals.

The AI system is already in use in Ras Al Khaimah Physiotherapy and Sports Centre and will be rolled out soon in all other ministry hospitals. “Games are developed for rehab of such patients, for both children and adults, especially those suffering from cerebral palsy and motor delay conditions,” Dr Yousif Mohammed Al Serkal, assistant undersecretary for the hospital sector, told Khaleej Times.

“The AI system is composed of three parts – a TV set, a sensory kinetic bar and an X-Box linked with these. Specific games are used to assess how cognitive a patient is,” he said.

A therapist will always be present to monitor these sessions of patients and will assess their conditions accordingly, he added.

He also explained the advantages of VR using AI in physiotherapy to provide treatment. “This will allow the patient to complete the treatment at his/her home with the possibility of remote rehabilitation,” he said.

“In the treatment of stroke, the virtual reality system evaluates and enhances the recovery of the affected upper parts, in addition to the training for the walking device used for rehabilitation.

“The patient moves at a speed on the motion platform with changing virtual environments being displayed on the front screen to simulate daily activities. In the treatment of the balance disorder, virtual reality is a safe and effective alternative to conventional therapy to improve the balance in patients,” he said. “Patients have reported that they enjoyed VR therapy without suffering from side effects, and with increased motivation.

“This technique is also used to treat children with developmental disorders, including positive developments in both perceived and performance capabilities in areas of daily activities including social activities that they have not been able to do before.”

The virtual therapy also assists cerebral palsy patients in the reorganisation of the brain and movement ability and visual cognitive skills, in addition to social participation and personal factors.

More about VR with AI

The UAE Strategy for Artificial Intelligence (AI) is a project within the Centennial Plan 2071. The plan will also include virtual reality (VR) rehabilitation in physiotherapy for stroke patients, patients suffering from balance disorder and children with development disorders, cerebral palsy and Parkinson’s syndrome.

VR rehabilitation technology makes use of virtual world simulation to meet various requirements for effective medical intervention to achieve the best results using the video game controller and the moving sensor. Scientific studies have proven the effectiveness of this innovative technique in the rehabilitation and treatment of many such cases.

KT NANO EDIT

AI boost to healthcare

Healthcare industry stands to gain significantly by inducting artificial intelligence into various processes. The technology can take the fear out of procedures and make treatments more effective. The UAE has been experimenting on this front and results are encouraging so far. Innovation through AI is becoming more meaningful with its human-centric approach, and the medical experts are now looking at expanding its scope.

asmaalizain@khaleejtimes.com

 

via Virtual reality games to help patients’ rehabilitation in UAE – Khaleej Times

, , , , , ,

Leave a comment

%d bloggers like this: