Cogwear’s Post

Exciting news for heart health! ❤️ This #AI model predicting atrial fibrillation (irregular heartbeat) 30 MINUTES before it occurs! Current methods only detect it right before, but this could be a game-changer. Imagine preventing an episode with early intervention! This is HUGE for people with #atrialfibrillation. Early warnings could allow them to take medication or receive treatment to avoid the episode altogether. The model uses heart rate #data, making it potentially wearable tech compatible (think smartwatches!). ⌚️ What do you think about this technology? https://lnkd.in/exKZyMUE

Doctor's notes. ❤️❤️🩹Help of Artificial Intelligence in diagnosing heart diseases. ❗️ Notify about atrial fibrillation half an hour before it starts using artificial intelligence A method for the preventive diagnosis of atrial fibrillation has been developed, also available for smart watches 💝Atrial fibrillation is the most common type of heart rhythm disorder, which is a risk factor for the development of heart failure, stroke and vascular cognitive impairment. Early diagnosis and treatment are fundamental to the management of these patients. 👩🏼🏫 Scientists from Luxembourg have developed a system for predicting atrial fibrillation from normal sinus rhythm based on machine learning technologies. The system is able to warn about an upcoming violation 3️⃣0️⃣ minutes before it starts with an accuracy of about 80% 🤖 The artificial intelligence system is called WARN (Warning of Atrial fibRillatioN). It was trained and tested on ECG data from 350 patients. The ability to predict an episode of atrial fibrillation depends on the R-R interval (corresponding to heart rate), which is also determined by wearable devices such as smart watches. Moreover, the work of machine learning algorithms can be carried out directly by smartphones to optimize the computing load on less powerful devices (smart watches) 💝Currently, diagnostic methods can only detect atrial fibrillation at the moment of its onset using an ECG and there is no possibility of early warning of this condition ✅ Such technologies, when integrated with wearable devices (for example, smart watches), can significantly contribute to earlier and more effective interventions for atrial fibrillation and, as a result, improve disease outcomes. Artificial intelligence may not be dangerous for doctors, scientists, researchers and all people, but very useful for preserving and maintaining the health of people around the world! I wish everyone good health, happiness, good mood and peaceful skies above their heads. #cardiology #therapy #fibrillation #artificial_intelligence #AI #Medicaldoctors #Worldaid #Globalaid

Modeling multiple sclerosis using mobile and wearable sensor data - npj Digital Medicine #Introduction The blog post discusses the use of mobile and wearable sensor data in modeling multiple sclerosis. #Challenges in Multiple Sclerosis Research Researchers face challenges in collecting and analyzing data related to multiple sclerosis due to its complex nature. #Mobile and Wearable Sensors Mobile and wearable sensors offer a promising solution for monitoring and tracking multiple sclerosis symptoms in real-time. #Data Collection These sensors can collect a wide range of data, including gait patterns, tremors, and fatigue levels, providing valuable insights into the progression of the disease. #Machine Learning Models Machine learning models can be trained using this sensor data to predict disease progression and personalize treatment plans for patients with multiple sclerosis. #Future Implications The integration of mobile and wearable sensor ai.mediformatica.com #data #multiplesclerosis #this #digital #disability #clinical #acce #devices #medicine #wearabledevices #digitalmedicine #diagnosis #digitalhealth #healthit #healthtech #healthcaretechnology @MediFormatica (https://buff.ly/4c7Bpma)

'Like Fitbit for your brain'.. Using the same sensors as an EEG, these headphones by Neurable (partnering with Master & Dynamic), pick up on electrical activity in your brain. The headphones will track your cognitive health and also detect any early signs of any neurodegenerative diseases. Taking note from Fitbit, it lets you set up goals for moving around and incentivises you to score 'focus' point. One of the key product goals is helping people combat burn-out and fatigue. A useful tool, a fad, a mix of both? As technology is rapidly advancing, our thirst for data about pretty much anything, but especially ourselves, seems to be infinite. Are brain reading wearables the next new thing, or are we happy to just stop for a moment and say: "hey, I've been feeling a bit tired?" https://lnkd.in/eRysSpbk

An interesting and promising use of AI - brain health. Imagine a sleek, portable home device that resembles a headband or cap, embedded with tiny electrodes. Placed on the head, these sensors detect subtle brain wave activity, behaving like a pulse-detecting smartwatch, a blood pressure wrist cuff or a heart rate monitor. But this tool isn’t checking your heartbeat. Using advanced artificial intelligence algorithms to analyze data in real time, a device like this could look for signs of Alzheimer’s disease years before symptoms become apparent. Such a monitor is not yet available, but AI could make it a reality. “The readout could be as simple as a traffic light system — green for healthy activity, yellow for something to keep an eye on and red for when it’s time to consult a health care professional,” said David T. Jones, who directs the Neurology AI Program at the Mayo Clinic. “You would be able to monitor your brain health the same way you now can monitor your heart rate and blood pressure. We’re not there yet, but that is the future.” A team at Massachusetts General Hospital used AI and magnetic resonance imaging (MRI) to develop an algorithm to detect Alzheimer’s. They trained the model using nearly 38,000 brain images from about 2,300 patients with Alzheimer’s and about 8,400 who didn’t have the disease. They then tested the model across five datasets of images to see whether it could accurately identify Alzheimer’s. It did so with 90.2% accuracy, said Matthew Leming, a research fellow in radiology at the hospital’s Center for Systems Biology and one of the study authors. At the University of California at San Francisco, researchers used AI to design an algorithm to determine whether having certain health conditions could predict who might develop the disease in the future. The conditions included hypertension, high cholesterol and vitamin D deficiency in both men and women, erectile dysfunction and an enlarged prostate in men, and osteoporosis in women. They designed the model using a clinical database of more than 5 million people both with and without Alzheimer’s. In a separate group of non-Alzheimer’s patients, the algorithm predicted with 72% accuracy those who would eventually receive an Alzheimer’s diagnosis within seven years. “By the time you are unable to speak and walk, it’s very hard to repair the brain,” he said. “Early detection raises the hope you will be able to try new interventions before the damage occurs. I’m not saying this will happen, but the potential of AI certainly opens the door.”

"How AI could monitor brain health and find dementia sooner" Scientists are exploring how AI could revolutionize brain health monitoring by identifying early signs of dementia, including Alzheimer’s, before symptoms appear. Using AI to analyze brain waves and other biomarkers, researchers aim to create wearable devices that track cognitive health, much like heart rate or blood pressure monitors. AI's ability to handle massive datasets allows it to detect subtle patterns that humans might miss, potentially accelerating early diagnosis and enabling proactive treatment. While the technology is still developing, the potential for early detection could transform how dementia is treated, offering hope for earlier interventions and improved quality of life. Read more here: https://lnkd.in/gipTHUy4 #AI #Healthcare #Dementia #Health #Brain #Alzheimers #Healthcare #Detection

🚀 Revolutionizing Heart Health: Predicting Arrhythmia Before It Strikes! Researchers at the University of Luxembourg's LCSB have developed an AI model that not only identifies atrial fibrillation—a heart condition affecting millions—but predicts it 30 minutes before onset with 80% accuracy. This breakthrough, published in Patterns, could transform patient care with wearable technology, offering timely interventions that drastically improve outcomes. Imagine your smartwatch warning you of a potential heart issue in real-time, allowing for early action and potentially saving lives. Dive into the future of heart health where prevention is just a heartbeat away! #HeartHealth #AI #WearableTech #MedicalInnovation

Wearable sensors supported by machine learning models can continuously monitor and quantify FOG episodes, as well as the patient's general functioning in daily life…

A recently developed and published deep-learning model can predict the transition from a normal cardiac rhythm to atrial fibrillation 30 minutes before it happens! The accuracy is around 80% and could pave the way for early warning systems built into wearable technologies. "This artificial intelligence model, called WARN (Warning of Atrial fibRillatioN), was trained and tested on 24h-recordings collected from 350 patients at Tongji Hospital (Wuhan, China) and gave early warnings, on average 30 minutes before the start of atrial fibrillation, with great accuracy. Compared to previous work on arrhythmia prediction, WARN is the first method to provide a warning far from onset." It could also be implemented in smartphones to process the data from a smartwatch! Patients will become the point of care with such innovations.

I see this amazing advancement that has great potential to help the healthcare system intercede sooner to save more lives. Amazing accomplishment and technology! But with my HFE and system thinking hats on, I have to ask… Does this type of technology also include system level changes being worked on simultaneously? Or will this mean more calls being placed on already stressed HCPs (due to high patient to doctor ratios, for example)? Or is this smartwatch type technology intended to push healthcare into more patients and lay caregivers being asked to address potential serious health events in the home with minimal to no training, education, or skill to appropriately handle this high risk health alert? I’m fascinated how AI and predictive technologies can change the practice of medicine, but I also question if our health systems and healthcare providers are keeping up with the technology potentials and what it necessitates for user and system level changes, which are much harder to advance than technology. This reminds me of the leap many resisted with technologies involved with telemedicine, until there seemed to be a great need (during Covid). And then the roll out was clunky and problematic at best. What does my HF network know about that is currently happening at the system and user levels to help these advanced technologies be successful? I saw #fda is launching a new initiative related to home healthcare: https://lnkd.in/gJ8bA4U5 What else are we doing?! #humanfactorsengineering #humanfactors #usability #systemimprovements #homehealthcare