Deans' stroke musings: Accurately detecting heartattacks and strokes with Apple Watch and fitbits

Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Friday, May 12, 2017

Accurately detecting heartattacks and strokes with Apple Watch and fitbits

Or you could do the expensive testing in the hospital.
https://www.nextbigfuture.com/2017/05/accurately-detecting-heartattacks-and-strokes-with-apple-watch-and-fitbits.html

Heartbeat measurement app Cardiogram and the University of California, San Francisco used the Apple Watch for 97 percent accurate detection the most common abnormal heart rhythm when paired with an AI-based algorithm.
The study involved 6,158 participants recruited through the Cardiogram app on Apple Watch. Most of the participants in the UCSF Health eHeart study had normal EKG readings. However, 200 of them had been diagnosed with paroxysmal atrial fibrillation (an abnormal heartbeat). Engineers trained a deep neural network to identify these abnormal heart rhythms from Apple Watch heart rate data.
About a quarter of strokes are caused by an abnormal heart rhythm, according to Cardiogram co-founder and data scientist for UCSF’s eHeart study Brandon Ballinger.
Two-thirds of those types of strokes are preventable with relatively inexpensive drugs.
Digital health company AliveCor and Rochester, MN-based Mayo Clinic are teaming up to glean new insights from data captured with AliveCor’s mobile ECG device.
The Mobile EKG sticks onto the back of a smartphone and uses the Kardia app to determine abnormal heart rhythm, and determined it was as good as other EKG devices used in the doctor’s office. The Mayo Clinic felt invested in AliveCor’s latest $30 million round.

Together, the Mountain View, CA-based company and Mayo will apply AliveCor’s machine learning technology to 10 million ECG recordings taken by users of the company’s Kardia product, an FDA-cleared mobile device that pairs with smartphones to measure electrical activity in the heart. The goal is to “uncover hidden physiological signals to improve heart and overall human health,” according to a press release.
In particular, the findings could lead to insights about the relationship between cardiac arrhythmias and changes in blood potassium levels, which can indicate kidney failure.
“Working with Mayo Clinic, we are hopeful that soon physicians will be turning to ECG data for the care of many types of patients, not just those with typical cardiovascular issues,” Dave Albert, MD, AliveCor’s chief medical officer, said in the press release.