Smartwatch seizure detection app achieves near-perfect sensitivity in trial

 With your risk of seizures post stroke, will your competent? doctor prescribe this for you? 

10% seizures post stroke (19 posts to April 2017)

5% epileptic seizures after stroke (10 posts to April 2021)

epileptic seizures (6 posts to December 2015)

post-stroke epilepsy (7 posts to December 2016)

Do you prefer your doctor, hospital and board of director's incompetence NOT KNOWING? OR NOT DOING? Your choice; let them be incompetent or demand action!

You've been wearing a smartwatch containing this for years already because of your risk of Parkinsons, right?

Parkinson’s Disease May Have Link to Stroke March 2017 

Smartwatches Able to Detect Very Early Signs of Parkinson's July 2023 

The latest here:

Smartwatch seizure detection app achieves near-perfect sensitivity in trial

The EpiWatch seizure detection app identified tonic-clonic seizures with 98% sensitivity and an exceptionally low false alarm rate of just 1 false alert every 12.4 days in a multicentre phase 3 study, published in the journal Neurology.

The findings suggest the wearable technology could improve safety for patients with epilepsy -- particularly those at risk for sudden unexpected death in epilepsy (SUDEP) -- while addressing major barriers to adoption seen with existing seizure detection devices.

“For people who have uncontrolled tonic-clonic seizures, which can include a loss of muscle tone and airway obstruction, the risk of SUDEP is high, particularly for those who sleep alone,” said James W. Wheless, MD, Le Bonheur Children’s Hospital, Memphis, Tennessee. “Wearable seizure detection devices can alert caregivers so they can provide first aid, but some devices have high false alarm rates that can discourage use and timely intervention. Our study found the EpiWatch smartwatch app detected nearly all tonic-clonic seizures in participants and had a lower rate of false alarms.”

The study was conducted across 6 epilepsy monitoring units between September 2021 and October 202, enrolling 242 children and adults aged ≥5 years with a history or risk of tonic-clonic seizures who underwent inpatient video-EEG monitoring. Participants wore the smartwatch on the wrist opposite their seizure focus, and seizure detections generated by EpiWatch were compared against independently verified seizure events reviewed by a blinded panel of epileptologists. 

The study’s co-primary endpoints were seizure detection sensitivity and false alarm rate per 24 hours, with additional analyses assessing detection speed and night-time performance.

EpiWatch detected 46 of 47 verified tonic-clonic seizures, yielding an overall sensitivity of 98%. The single missed seizure occurred when a caregiver physically restrained the participant’s arm during the event. Across more than 16,000 hours of monitoring, only 56 false alarms were recorded, corresponding to a false alarm rate of 0.08 per 24 hours -- approximately 1 false alert every 12.4 days and roughly one-tenth the rate reported for other seizure detection devices. 

Median detection latency was 31.5 seconds, and all tonic-clonic seizures occurring during sleep were successfully identified. 

No adverse events were reported. 

“Wearing some seizure monitoring devices may carry a stigma, but using a common smartwatch with an app does not, which is important for encouraging regular use,” said Dr. Wheless. “Being prescribed an app with fewer false alarms can encourage long-term use and provide reliable caregiver alerts to help reduce sudden unexpected deaths and other risks associated with tonic-clonic seizures.”

A limitation of the study was that all seizures occurred in the controlled environment of an epilepsy monitoring unit and may not represent the variety of conditions in which people experience seizures.

Funding for the study was provided by EpiWatch.

Reference: https://www.neurology.org/doi/10.1212/WN9.0000000000000111

SOURCE: American Academy of Neurology

Smartwatches Able to Detect Very Early Signs of Parkinson's

With your risk of Parkinsons post stroke does your doctor have enough functioning brain cells to  use this on you?

Parkinson’s Disease May Have Link to Stroke March 2017 

Do you prefer your doctor incompetence in this NOT KNOWING? OR NOT DOING?

 

The latest here:

Smartwatches Able to Detect Very Early Signs of Parkinson's

Changes in movement detected passively by smartwatches can help flag Parkinson's disease (PD) years before symptom onset, new research shows.

An analysis of wearable motion-tracking data from UK Biobank participants showed a strong correlation between reduced daytime movement over 1 week and a clinical diagnosis of PD up to 7 years later.

"Smartwatch data is easily accessible and low-cost. By using this type of data, we would potentially be able to identify individuals in the very early stages of Parkinson's disease within the general population," lead researcher Cynthia Sandor, PhD, from Cardiff University, said in a statement.

"We have shown here that a single week of data captured can predict events up to seven years in the future. With these results we could develop a valuable screening tool to aid in the early detection of Parkinson's," she added.

"This has implications both for research, in improving recruitment into clinical trials, and in clinical practice, in allowing patients to access treatments at an earlier stage, in future when such treatments become available," said Sandor.

The study was published online July 3 in Nature Medicine.

Novel Biomarker for PD

Using machine learning, the researchers analyzed accelerometry data from 103,712 UK Biobank participants who wore a medical-grade smartwatch for a 7-day period in 2013 to 2016.

At the time of or within 2 years after accelerometry data collection, 273 participants were diagnosed with PD. An additional 196 individuals received a new PD diagnosis more than 2 years after accelerometry data collection (the prodromal group).

The patients with prodromal symptoms of PD and those who were diagnosed with PD showed a significantly reduced daytime acceleration profile up to 7 years before diagnosis, compared with age- and sex-matched healthy control persons, the researchers found.

The reduction in acceleration both before and following diagnosis was unique to patients with PD, "suggesting this measure to be disease specific with potential for use in early identification of individuals likely to be diagnosed with PD," they write.

Accelerometry data proved more accurate than other risk factors (lifestyle, genetics, blood chemistry) or recognized prodromal symptoms of PD in predicting whether an individual would develop PD.

"Our results suggest that accelerometry collected with wearable devices in the general population could be used to identify those at elevated risk for PD on an unprecedented scale and, importantly, individuals who will likely convert within the next few years can be included in studies for neuroprotective treatments," the researchers conclude in their article.

High-Quality Research

Weighing in on the results in a statement from the UK-based nonprofit Science Media Centre, José López Barneo, MD, PhD, with the University of Seville, Spain, said this "good quality" study "fits well with current knowledge."

Barneo noted that other investigators have also observed that slowness of movement is a characteristic feature of some people who subsequently develop PD.

But these studies involved preselected cohorts of persons at risk of developing PD, or they were carried out in a hospital that required healthcare staff to conduct the movement analysis. In contrast, the current study was conducted in a very large cohort from the general UK population.

Also weighing in, José Luis Lanciego, MD, PhD, with the University of Navarra, Spain, said the "main value of this study is that it has demonstrated that accelerometry measurements obtained using wearable devices (such as a smartwatch or other similar devices) are more useful than the assessment of any other potentially prodromal symptom in identifying which people in the [general] population are at increased risk of developing Parkinson's disease in the future, as well as being able to estimate how many years it will take to start suffering from this neurodegenerative process.

"In these diseases, early diagnosis is to some extent questionable, as early diagnosis is of little use if neuroprotective treatment is not available," Lanciego noted.

"However, it is of great importance for use in clinical trials aimed at evaluating the efficacy of new potentially neuroprotective treatments whose main objective is to slow down ― and, ideally, even halt ― the clinical progression that typically characterizes Parkinson's disease," Lanciego added.

The study was funded by the UK Dementia Research Institute, the Welsh Government and Cardiff University. Sandor, Barneo and Lanciego have no relevant disclosures.

Nature Med. Published online July 3, 2023. Abstract