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The Impact of Wearable Technology in Disease Diagnosis and Patient Care
By Kevin Cheng, 2023
Wearable technology (or “wearables”) is a category of electronic devices that is designed to continuously measure health data of users. This ranges from accessories including smartwatches, to biosensors such as contact lenses that could monitor glucose concentrations in tears. With the ability to provide easily accessible data at a relatively low cost and continuous technological advancements, wearables are changing the way we approach disease diagnosis and patient care, opening up boundless possibilities and revolutionising the healthcare industry.
The global demand for wearables is continuously on the rise. In fact, the global market size for wearable technology in 2021 was worth USD 115.8 billion, and is projected to surpass USD 380.5 billion by 2028. One of the most common types of wearables is smartwatches, made popular by industry leaders such as Apple and Fitbit. In addition to providing real-time health and fitness metrics such as heart rate, step counts and sleeping patterns, smartwatch data also carries the potential for predicting the development of certain disorders such as Parkinson’s disease.
Parkinson’s disease is a progressive neurodegenerative disease that is associated with movement disorders, including uncontrolled shaking, stiffness or issues with balance and coordination. This condition is caused due to a reduction of dopaminergic neurons in the substantia nigra, which are responsible for dopamine production and subsequently regulating body movement. Unfortunately, at the stage when such symptoms appear and a clinical diagnosis is made, 50-70% of these nerve cells would have been degenerated. Moreover, there is currently no direct cure for this disease, making it crucial to identify the disease before such motor symptoms start manifesting clinically, allowing for early intervention and treatment to prevent further neuronal damage.
Before being diagnosed with Parkinson’s disease, patients may have started experiencing prodromal symptoms years beforehand, including rapid eye movement or REM sleep behaviour disorder (RBD), and signs of slowness in daily activities. Thus, creating tools that can accurately identify these prodromal symptoms is essential for early diagnosis of the disease. Researchers at the UK Dementia Research Institute (UK DRI) and the Neuroscience and Mental Health Innovation Institute (NMHII) at Cardiff University have shown that data obtained from smart watches could predict Parkinson’s disease as early as seven years before symptoms become apparent.
Smartwatches contain a sensor known as an accelerometer, which senses and measures the acceleration of movement of users, allowing for continuous recording of physical activity. The study analysed accelerometry data from the UK Biobank, which included a subset of 103,712 participants that have worn accelerometers over a period of 7 days in 2013-2016. Researchers then compared data between a subset of patients that have already been diagnosed with Parkinson’s disease, and a group of patients who have received a diagnosis up to seven years after data collection. Using artificial intelligence prediction models, they were able to not only identify participants that would later on develop the disease, but also estimate the expected time before a clinical diagnosis is made.
In addition, the study compared accelerometry data to other existing prodromal symptoms or modalities including genetics and blood biochemistry, and found that accelerometry data outperforms other markers and modalities in predicting future Parkinson’s diagnosis. This implies that accelerometry could be a potential screening tool for detecting early stage Parkinson’s within the general population, which also creates the opportunity to identify the corresponding patient population for clinical trials. This study is published in Nature Medicine.
The field of developing wearables that can detect Parkinson’s disease and other types of dementia is an ever-evolving landscape. Researchers such as Dr Michele Hu - a professor at the Nuffield Department of Clinical Neuroscience at University of Oxford, is researching the creation of tools with the ability to monitor sleep behaviour or RBD to predict the onset of Parkinson's disease.
Apart from smart watches, there has also been an increasing focus on the application of socks in healthcare monitoring. “SmartSocks”, invented by Dr Zeke Steer, has the ability to measure and record one’s sweat levels, temperature, motion and so on. These socks do not require charging and can be machine washed, making the technology simple for adoption into real world settings. Data collected from these socks are wirelessly transmitted to an app that is accessible to home care staff. When patients are experiencing distress, alert signals are sent to the app to notify carers, allowing for early intervention and patient support.
Dr Steer had also founded a care technology start-up called Milbotix, which is partnering with two research teams to test the efficacy of SmartSocks. One that is currently in collaboration with UK DRI Care Research and Technology Centre at Imperial College London, is testing whether these socks can detect signs of distress or agitation and prevent falls in dementia patients in a home setting. This could enable patients to receive support at the comfort of their own homes, whilst alleviating the workload for home care staff.
A separate study led by the University of Exeter aims to test whether the same technology can support people with dementia that may not effectively articulate their thoughts or control their movements. Such technology can also be applied to cases outside of dementia, to patients with other conditions that may also affect communication, such as autism.
Nonetheless, adoption of wearable technology also contains its challenges. Firstly, there are concerns related to customer safety and privacy, in particular the potential risk of hacking or data manipulation. Underdeveloped algorithms in wearable technology may also create inaccurate predictions for medical conditions. A previous study in 2022 used smartwatches to record electrocardiography (ECG) and detect atrial fibrillation, but the smartwatch algorithm displayed inconclusive results or false positives, leading to unreliable findings which could lead to potential misdiagnosis. In this case, wearables should only be used as a preliminary screening tool, and experts could consider data collected from wearables as part of their decision process when making clinical diagnoses.
All in all, wearable technology carries a huge potential in advancing patient care and remote health monitoring. As we witness the integration of MedTech into everyday life, alongside the expansion of such technologies to the wider demographic, the future of wearables in healthcare remains promising and optimistic.
Additional Resources
Kim, J., Campbell, A.S., de Ávila, B.EF. et al. Wearable biosensors for healthcare monitoring. Nat Biotechnol 37, 389–406 (2019). https://doi.org/10.1038/s41587-019-0045-y
Smart watches could detect parkinson’s up to seven years before hallmark symptoms appear https://ukdri.ac.uk/news-and-events/smart-watches-could-detect-parkinsons-up-to-seven-years-before-hallmark-symptoms-appear
'Smart’ socks that track distress in people living with dementia could transform care