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Wearable device could provide early warning of Alzheimer’s

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App for monitoring Parkinson’s disease gets FDA clearance

Monitoring daily activity patterns using a wrist-worn device may detect early warning signs of Alzheimer’s disease, according to a new study led by researchers at the Johns Hopkins Bloomberg School of Public Health.

The researchers analysed movement data from wristwatch-like devices called actigraphs worn by 82 cognitively healthy older adults who were participants in a long-running study of aging. Some of the participants had detectable brain amyloid

buildup as measured by PET scan. Buildup of the protein amyloid beta in the brain is a key feature of Alzheimer’s disease.

Using a sensitive statistical technique, the researchers found significant differences between this “amyloid-positive” group and “amyloid-negative” participants in mean activity in certain afternoon periods and differences in variability of activity across days in a broader range of time windows.

The new study was published online February 21 in the journal SLEEP.

“We need to replicate these findings in larger studies, but it is interesting that we’ve now seen a similar difference between amyloid-positive and amyloid-negative older adults in two independent studies,” says Adam Spira, PhD, professor in the Department of Mental Health at the Bloomberg School.

The new study’s results partly confirm findings from an earlier study in a smaller sample, also led by Spira, and suggest that actigraphs someday could be a tool to help detect incipient Alzheimer’s disease before significant cognitive impairment sets in. Data from the prior study came from participants in the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s (A4) and the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) studies.

For their new study, Spira and colleagues investigated the potential of actigraph-based monitoring in 82 community-dwelling individuals whose average age was about 76. Each participant had a PET scan to measure brain amyloid and wore an actigraph 24 hours per day for one week. Using a sensitive statistical technique called FOSR (function-on-scalar regression), the researchers found that the 25 amyloid-positive participants, compared to the 57 amyloid-negative participants, had higher mean activity during the early afternoon, 1:00 to 3:30 p.m., and less day-to-day variability in activity from 1:30 to 4:00 p.m. and 7:30 to 10:30 p.m.

In more conservative analyses, some of these time windows with differences were no longer statistically significant. Nonetheless, the higher afternoon activity and lower afternoon variability echoed the investigators’ prior findings.

Alzheimer’s disease, the leading cause of dementia, is estimated to affect more than six million older adults in the U.S. The Alzheimer’s disease process is still not fully understood but is characterised by amyloid plaques and tangles in the brain, which typically begin to accumulate a decade or two before Alzheimer’s is diagnosed.

The only approved treatments that may slow the disease course are those that target amyloid beta and reduce the plaques. Many researchers believe that such treatments can be much more effective if given earlier in the disease course—ideally, years before dementia becomes evident.

Abnormal patterns of sleep and waking activity have been studied as potential early indicators of Alzheimer’s. Alzheimer’s patients typically have abnormal sleep-wake rhythms, and prior studies have found evidence that amyloid accumulation may disrupt sleep-wake rhythms relatively early in the disease process. There is also evidence that sleep loss promotes amyloid accumulation, suggesting a “vicious circle.”

Such findings hint at the possibility that older adults might someday, among other measures, wear wristwatch-like devices that would automatically track and analyse their sleep and waking activity. Individuals with anomalous activity patterns could then consult their physicians for more in-depth Alzheimer’s screening.

The individuals in the new study were participants in a long-running study, the Baltimore Longitudinal Study of Aging, which is conducted by the Intramural Research Program of the National Institute on Aging (NIA), part of the National Institutes of Health (NIH). Several members of the NIA team were co-authors of the study.

Standard, non-FOSR statistical methods did not detect any significant differences in activity or sleep patterns, suggesting the methods may be less sensitive to amyloid deposition.

In the earlier actigraphy study, the researchers, using FOSR-based analyses in a different sample of 59 participants, found increases in mean activity in afternoon hours and differences in variability, including lower variability in the afternoon, among amyloid-positive participants.

The scientists don’t know why amyloid buildup would trigger differences in activity patterns during these particular times of day. They note that there is a well-known phenomenon among individuals with Alzheimer’s disease called “sundowning,” in which agitation increases in the afternoon and early evening.

“It’s conceivable that the higher afternoon activity we observed is a signal of ‘preclinical sundowning,’” Spira says.

“At the same time, it’s important to note that these findings represent averages among a small sample of older people over a short period of time. We can’t predict whether an individual will develop amyloid plaques based on the timing of their activity. So, it would be premature for older people to be concerned because their fitness trackers say they are particularly active in the afternoon, for example.”

He and his colleagues plan to do larger studies of this kind. They also hope to do longer-term studies to see if daily activity-pattern changes are associated not only with brain amyloid but also with actual cognitive decline.

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UK body calls for more ageing research backing

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The British Society for Research on Ageing (BSRA) is calling for more public backing in the UK for research to help people stay healthier for longer, as an alternative to charities that support research on diseases.

The greatest risk factor for disease is ageing, but we have very little charitable support for research into how to slow ageing, the organisation warns.

Many diseases such as cancers and heart disease tragically shorten lives far too early, or like Alzheimer’s and arthritis, destroy quality of life for patients and carers. There is understandably huge public charitable support for more research. However, the greatest risk factor for those diseases, and even infectious diseases like COVID, is ageing.

Yet in comparison there is currently very little support for research to understand how we can slow ageing to prevent disease. This approach may be more productive in the long term to fight disease. Furthermore, keeping people healthier for longer, or avoiding chronic diseases all together, would be the most favourable outcome.

The UK population is ageing fast, putting pressure on the NHS and the economy. Despite this pressing problem all around us, there is no accessible way for people to support research into ageing in the UK. The BSRA aims to change that.

With a very small budget and almost completely run by volunteers, the BSRA has successfully funded several small research projects but progress needs to be accelerated. More funding is needed because it takes years to see the effects of ageing, so studies are long. Also ageing affects individuals in different ways, meaning that large numbers of people must be studied to make firm conclusions.

Therefore, there is an urgency to get studies funded and the BSRA has decided to launch an ambitious fundraising campaign to boost research into ageing. Initially, the Society aims to fund a series of one year research projects at the Masters degree level at universities across the UK and with plans to raise much more in the future to support longer and more ambitious projects that will impact the lives of the general public.

Chair of the BSRA, Prof David Weinkove from Durham University, says “The time is now to really get behind research into the biology of ageing. We have fantastic researchers across the country, but they are held back by a lack of funding. Evidence-based research is needed to understand how we people can stay healthier for longer, and to then we must make that knowledge available to as many people as possible”.

Dr Jed Lye says “This is a great opportunity for the public to help, for corporations to contribute, or philanthropists wanting a large impact with a relatively small donation; every £20,000 we raise can fund an entire year of research into ageing and longevity, and gets a budding scientist their research qualification.”

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Study detects cognitive changes in older drivers using in-vehicle sensors

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The forward-facing camera is mounted under the rearview mirror and is used to record events external to the vehicle. Photo credit: Jinwoo Jang, Ph.D., FAU College of Engineering and Computer Science

A new, in-vehicle sensing system could provide the first step toward widespread, low-cost early warnings of cognitive change among older drivers in the US and elsewhere.

An estimated 4 to 8 million older adults with mild cognitive impairment are currently driving in the United States, and one-third of them will develop dementia within five years. Individuals with progressive dementias are eventually unable to drive safely, yet many remain unaware of their cognitive decline.

Currently, screening and evaluation services for driving can only test a small number of individuals with cognitive concerns, missing many who need to know if they require treatment.

Nursing, engineering and neuropsychology researchers at Florida Atlantic University are testing and evaluating a readily and rapidly available, unobtrusive in-vehicle sensing system they have developed.

In their study, published in the journal BMC Geriatrics, they systematically examine how this system could detect anomalous driving behaviour indicative of cognitive impairment.

Few studies have reported on the use of continuous, unobtrusive sensors and related monitoring devices for detecting subtle variability in the performance of highly complex everyday activities over time. This significant proportion of older drivers constitutes a previously unexplored opportunity to detect cognitive decline.

Ruth Tappen, Ed.D., principal investigator, senior author and the Christine E. Lynn Eminent Scholar and Professor, FAU Christine E. Lynn College of Nursing, said: “The neuropathologies of Alzheimer’s disease have been found in the brains of older drivers killed in motor vehicle accidents who did not even know they had the disease and had no apparent signs of it.

“The purpose of our study arose from the importance of identifying cognitive dysfunction as early and efficiently as possible. Sensor systems installed in older drivers’ vehicles may detect these changes and could generate early warnings of possible changes in cognition.”

The study uses a naturalistic longitudinal design to obtain continuous information on driving behaviour that is being compared with the results of extensive cognitive testing conducted every three months for three years. A driver facing camera, forward facing camera, and telematics unit are installed in the vehicle and data is downloaded every three months when the cognitive tests are administered.

Researchers gauge abnormal driving such as getting lost, ignoring traffic signals and signs, near-collision events, distraction and drowsiness, reaction time and braking patterns. They also look at travel patterns such as number of trips, miles driven, miles on the highway, miles during the night and daytime, and driving in severe weather.

How it works

The in-vehicle sensor network developed by FAU researchers in the College of Engineering and Computer Science, uses open-source hardware and software components to reduce the time, risks and costs associated with developing in-vehicle sensing units.

In-vehicle sensor systems are kept simple and compact by minimising complex wiring, limiting the size of the sensing units, and limiting the number of sensors in a vehicle to support the unobtrusiveness of in-vehicle sensors. Each in-vehicle sensor system is comprised of two distributed sensing units: one for telematics data and the other for video data.

Inertial measurement unit data is processed to determine hard braking, hard accelerations and hard turns and GPS data. It also includes a timestamp, latitude, longitude, altitude, course over ground and the number of communicating satellites.

The video unit has built-in artificial intelligence functions that analyse video in real-time. The driver-facing camera is mounted in the left corner of the windshield and is directed to the driver’s face to analyse his/her behaviour and facial expressions. The forward-facing camera is mounted under the rearview mirror and is used to record events external to the vehicle.

Driver-facing indices include face detection, eye detection (open or closed), yawning, distraction, smoking and mobile phone use. Behaviour indices include traffic sign detection (running a red light), object detection (pedestrian, cyclists, curbs, barriers or nearby vehicles), lane crossing, near-collision and pedestrian detection.

“These travel-pattern-related driver behaviour indices are known to be indicative of the changes in older drivers’ cognition and physical functions since they tend to incorporate deliberate avoidance strategies to compensate for age-related deficits,” said Tappen.

“Driver behaviour indices are evaluated for each driver and are summarised on a daily, weekly and monthly basis and are classified into four categories.”

A total of 460 study participants will be recruited from Broward and Palm Beach counties in Southeast Florida and are classified into three diagnostic groups: mild cognitive impairment, early dementia and unimpaired (normal). The Louis and Anne Green Memory and Wellness Center operated by FAU’s College of Nursing serves as the testing site for a clinical battery including assessments of cognition, functioning in daily activities and mood (depression), and an additional set of tests including executive function and attention.

Tappen adds: “The innovation of our research project lies in the unobtrusive, rapidly and readily available in-vehicle sensing and monitoring system built upon modern open-source hardware and software using existing techniques to develop and customise the components and configure them for this new purpose.”

The study is supported by a grant from the National Institute on Aging.

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Smart wristband developed to identify and manage atrial fibrillation

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It’s one of the most common conditions affecting those over 65 and left untreated can lead to stroke, blood clots in the veins and, in the most extreme cases, heart failure.

Atrial fibrillation currently affects more than 40 million people worldwide and the incidence and prevalence of the medical condition have increased three-fold in the past 50 years as populations age and survival rates for chronic diseases increase.

Now thought of as a global epidemic, 16 million people in the United States alone are projected to have been diagnosed with the ailment by 2050. In Europe, the figure among the over 55s is expected to reach 14 million by 2060.

It is estimated that by 2050, AF will be diagnosed in at least 72 million individuals in Asia.

One of the most common symptoms of AF is a pounding, fluttering, or quivering heartbeat, more commonly known as heart palpitations. Other signs include dizziness, fatigue, a fast heart rate of more than 100 beats per minute, breathlessness, and chest pain – many of the classic stress or anxiety signs that characterise a panic attack.

It’s one of the reasons that millions of people are walking around unaware that they are suffering from atrial fibrillation. How many times have you heard someone attribute their racing heartbeat to a caffeine-induced surge brought about by having drunk one too many coffees?

Many more are asymptomatic, meaning they are producing and showing no symptoms at all.

Often the condition will only be picked up when a patient undergoes a health check for an unrelated matter.

However, early detection and treatment of AF are paramount if later complications are to be avoided.

Without treatment, people with AF are up to five times more likely to suffer strokes, leading to the risk of severe disability and even premature death.

But new patient-safe monitoring technology to check and manage individual factors provoking atrial fibrillation, has been invented by Lithuanian researchers that could hold the key to earlier diagnosis and outcomes for the potentially serious heart condition.

A smart wrist-worn bracelet has been developed by Lithuanian scientists to identify atrial fibrillation. Credit: KTU

It involves patients wearing a so-called smart bracelet – already an accepted accessory for many – that uses an algorithm that can detect atrial fibrillation.

Traditional methods of diagnosing AF involve patients having to wear intrusive and uncomfortable sensors. But this new technology incorporates complementary sensors and a signal processing algorithm, with patients also being asked to input potential arrhythmia triggers on a mobile app.

The device is the result of a successful collaboration between the Kaunas University of Technology Biomedical Engineering Institute (KTU BMEI) and Vilnius University’s Santaros Clinics.

Researchers at KTU BMEI have been working in the field of atrial fibrillation monitoring technology development for more than a decade. It was several years ago that they developed the bracelet – the patent application for the device was submitted to the Lithuanian State Patent Bureau at the end of 2018 – which is aimed at older people, who can be especially self-conscious when using technologies and smart devices.

Professor Vaidotas Marozas, director of KTU BMEI, told Agetech World: “We are focusing on developing technologies which are needed for the public and contemporary medicine. For example, due to the prevalence of this condition (AF), every person older than 65 should be checked for atrial fibrillation.

“Non-invasive, compact wearable devices are an attractive solution for monitoring the health status of such high-risk groups.”

The disease usually starts with self-terminating so-called ‘paroxysmal episodes’ which, if recognised in time, can be treated by non-medication means.

These episodes may be different for each patient, however. For some, they may last for a short time and recur infrequently. For others, the episodes can be longer and more frequent.

But untreated AF will eventually develop into a persistent condition, which is more complicated to treat.

The smart wristband developed by Lithuanian scientists. Credit: KTU

The KTU-developed smart bracelet – which Lithuanian company, Teltonika, has stepped in to produce – has been used together with other devices in the TriggersAF project supported by the European Regional Development Fund.

The aim of the project coordinated by the Kaunas University of Technology in partnership with Vilnius University, is to develop and test methods that allow patients to identify their individual arrhythmia triggers via a wrist-wearing device.

It is already known that for some patients, atrial fibrillation episodes can be provoked by certain modifiable factors, such as alcohol, increased physical activity, stress, and sleep disturbance.

Identifying and avoiding individual factors would help determine non-pharmaceutical intervention methods to arrhythmia management.

As the project addresses a clinical problem, it has been important to have on board experienced clinicians who deal with AF daily. One of them is Justinas Bacevičius, a cardiologist at VU Hospital Santaros Clinics.

He said: “Although we see a wide variety of atrial fibrillation patients in our hospital, two types can be distinguished. The first group includes older, overweight, diabetic, hypertensive patients or those having sleep apnoea.

“The second group is the complete opposite – often they are young, professional sportspersons, businesspeople or performers who are experiencing a lot of stress.”

Mr Bacevičius said the data from the patients suggests a link between the onset of arrhythmia and sleep disorders.

He added that interestingly, even in patients who are not diagnosed with sleep apnoea, a correlation between snoring during sleep and the onset of atrial fibrillation in the morning, or later in the day, had been identified.

But with no objective methods to identify individual factors influencing the arrythmia in patients, KTU BMEI researchers in collaboration with cardiologists from VU Hospital Santara Clinics and their long-term partner Leif Sörnmo from Lund University in Sweden, have proposed one.

It assumes that arrythmia parameters, such as the relative duration of an episode, increase after an arrythmia-provoking factor.

Vilma Pluščiauskaitė, a PhD student at KTU and a junior researcher on the project, explained: “The essence of our proposed approach is that the patient uses a wearable bio signal-recording device for a set monitoring period, e.g. two weeks, and enters potential triggers for atrial fibrillation into a mobile app.

“For the next two weeks, the patient avoids the identified potential triggers, and the relation is assessed by an equation proposed by KTU BMEI researcher Dr Andrius Petrėnas.

“If a correlation between the influencing factor and the occurrence of arrhythmia is detected, the patient is advised to avoid the specific identified factor.”

The project’s database is the first of its kind in the world. It includes the recorded patients’ physiological signals, such as electrocardiogram and photoplethysmogram (a simple and low-cost technique that sends light pulses through the skin into the blood vessels to detect blood volume changes), and potential arrythmia provoking factors entered in a person’s mobile app.

The database collected by the researchers has allowed them to test the developed method and identify arrythmia-provoking factors in individual patients.

Professor Vaidotas Marozas. Credit: KTU

Project leader, Professor Marozas, is understandably delighted with its success, which will allow further development of the smart bracelet technology.

He said: “The database generated by the project is a unique result. We have managed to interest an international consortium funded by the European Metrology Association in this data. This consortium has invited us to join their new project as a partner and we will continue our work.”

The lack of technology currently available to individually identify arrythmia-provoking factors is probably due to the fact that monitoring has traditionally been inconvenient. Patients usually have to have an electrocardiogram (ECG), which is an electrical recording of their heart rhythm.

If that doesn’t identify a problem, then further monitoring will be needed, involving having to wear a portable ECG recording device for 24 hours or more.

Patients may also be required to fill in numerous questionnaires to pinpoint trigger factors, which can be subject to recall bias, where they either forget about a potential arrhythmia provoking stimulus or are reluctant to acknowledge the presence of certain influences, such as alcohol intake.

Mr Pluščiauskaitė said: “Certain influencing factors for arrythmia, such as increased exercise, stress, or sleep disturbances, can be identified from physiological signals by the dedicated algorithms. However, other influencing factors, such as alcohol consumption, are difficult to identify in the signals, so it is best if the patient has the opportunity to indicate when he or she consumed alcohol.”

He added that it is hoped that in the future, identifying these arrythmia triggers will only require a smart bracelet incorporating complementary sensors and signal processing algorithm.

 

 

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