New wearable device to diagnose Alzheimer's disease

With tens of millions of people the world over being affected by dementia, and almost 80% of them suffering from Alzheimer's disease (AD), the Early Detection of Neurodegenerative diseases (Edon) is looking into a novel device to test for AD early in the process, using wearable technology. This will play a crucial role in intervening and preventing the progression of this disease, the prevalence of which has increased by almost 90% since 2000.

ARUK EdoN End - Final Cut 090419 16x9 Texted

The need

Advanced AD is generally not reversible, making it essential to detect and treat the disease early before it is clinically apparent. Earlier research shows that AD changes in the cognitive, motor and sensory functions occur years before the earliest clinical manifestations can be picked up. Existing cognitive tests have several limitations, including the time required, their insensitivity at early stages of the disease, the ability to be 'learned' which makes the responses on repeat testing virtually useless, and the need for subjective analysis. Imaging techniques may be better but are costly and invasive at present.

Wearable sensing technology

Wearable devices could be the way out. Wearable devices can retrieve information about the gait, movements, heart rate, patterns of sleep, and similar parameters. For instance, a pilot study in the UK showed that using inexpensive sensors worn over the body could pick up changes in the way the individual walks and behavioral changes, which are essential sensitive indicators of early or impending dementia.

Alzheimer's disease on MRI. Image Credit: Atthapon Raksthaput / Shutterstock

Their advantages include:

  • The easy and wide availability
  • Excellent connectivity providing immediate information
  • Increasing sensitivity and the ability to use multiple sensors
  • The ability to pick up physical and cognitive symptoms and signs
  • No or little burden on the healthcare system
  • Flexible approach allowing passive or prompted measurements

Gait and movement sensors

One researcher from the gait sensor project at Newcastle University Human Movement Science, Lynn Rochester, says, "Free-living gait analysis at home is particularly useful as it allows objective observation of an individual's day-to-day activity. It also has the benefit of providing continuous data over a prolonged time that may be more sensitive than one-off assessments." Early changes include alterations in gait speed, stride, and symmetry.

Fine motor movements may become more clumsy or slow. The sensing of typing or stylus-based drawing itself may offer sensing opportunities.

Other capabilities

Speech and language metrics, eye movements, and pupillary movements are also useful in detecting degeneration in multiple networks. Autonomic nervous system function is reflected by measures like heart rate, heart rate variability, sleep patterns due to disruption of circadian rhythms, and even social and mood changes may all be potentially detected by wearable sensors.

The researchers will be using information from several studies that are ongoing, hoping that by applying artificial intelligence (AI) to the data to get a prototype up and running over the next three years.

Beyond the enormous amount of work involved in predicting AD in the preclinical stages, developing consumer devices capable of reliable sensing, and analyzing the data, extensive studies will be required to provide an accurate measure of variability between subjects and at various times in the same person. Data security is also crucial in this aspect.

The project

The project is partly funded by philanthropist Bill Gates, and partly owes some of its budget to the UK government which wants to use AI on data to prevent chronic diseases and understand how they work. The project will begin work with the UK's Alan Turing Institute, the premier national institute for data science and artificial intelligence.

This part of the project will see the collection of reams of data from studies into AD that are still going on at present. This is because, in the words of the Institute's Chris Holmes, "Artificial intelligence has the potential to transform the learning opportunities from large-scale data studies such as Edon by integrating information from multiple sources. We will use AI to deliver new insights into the early signals of disease by combining digital data measurements with traditional sources such as brain imaging and memory tests."

The idea is to come up with a "digital fingerprint" that can be read using a wearable technology or a smartphone app, thus ensuring that people who are at most risk for several chronic medical conditions, can be identified early for appropriate interventions. The aim is to detect the very first changes in the brain, which would help arrest many of these conditions before they lead to dementia, and the person becomes, in many cases, unable to live normally.

The study will draw volunteers from the 2019 project called Accelerating Detection of Disease Program. This is targeting 5 million volunteers to help change the way disease is diagnosed, using the data they provide on AD, cancer, and heart disease. AI will help detect patterns that will, in turn, help identify AD.

The researchers want to classify and analyze this to understand what signs of the disease occur earlier in its course so that in the future, there will be an early warning system. Previous studies have indicated the feasibility of this as an inexpensive, multicentre home-based approach to monitoring patients more efficiently while still reducing the burden on the healthcare network. It could also boost the efficiency of clinical trials.

Dr. Liji Thomas

Written by

Dr. Liji Thomas

Dr. Liji Thomas is an OB-GYN, who graduated from the Government Medical College, University of Calicut, Kerala, in 2001. Liji practiced as a full-time consultant in obstetrics/gynecology in a private hospital for a few years following her graduation. She has counseled hundreds of patients facing issues from pregnancy-related problems and infertility, and has been in charge of over 2,000 deliveries, striving always to achieve a normal delivery rather than operative.


Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Thomas, Liji. (2020, February 16). New wearable device to diagnose Alzheimer's disease. News-Medical. Retrieved on November 28, 2021 from

  • MLA

    Thomas, Liji. "New wearable device to diagnose Alzheimer's disease". News-Medical. 28 November 2021. <>.

  • Chicago

    Thomas, Liji. "New wearable device to diagnose Alzheimer's disease". News-Medical. (accessed November 28, 2021).

  • Harvard

    Thomas, Liji. 2020. New wearable device to diagnose Alzheimer's disease. News-Medical, viewed 28 November 2021,


The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
You might also like... ×
Predictive model using vocal features from phone conversations can identify early signs of Alzheimer’s disease