Olivia Crossley



Arrhythmia, Artificial intelligence, Blood Pressure, Consultant, Digital health, Electrodes, EEG, ECG, FDA, Machine Learning, Side effects, Telemedicine, Ultrasound, UK’s General Data Protection Regulation, Wearable technologies

Digital technologies are electronic devices that analyze and store different kinds of information. These technologies have revolutionized how we communicate, learn, and shop. Now, digital devices are thought to be transforming the public health sector through the creation of the “Digital Health” field, as well as by accelerating the development of Precision Medicine (1). You may already have heard of commercially available digital health technologies such as FitBits or may have an app that let´s you access your medical records or helps you to manage your diabetes. These technologies all come under the umbrella of Digital Health.

Figure 1: Mindmap of Digital Health applications.
Image created using Canva.com.

The term “Digital health” refers to the delivery of healthcare via technology, enabling more precise diagnoses and treatments. With new technologies being introduced into the market every day, digital health is now a multi-billion-dollar sector that is constantly evolving. The concept of digital health is two-fold. Firstly, it enables us to keep track of our health outside of a medical environment, and thereby minimize the necessity for in-person visits to healthcare practitioners. Secondly, evidence-based digital health devices known as digital therapeutics can allow clinicians to intervene early, helping to prevent a condition from worsening, as well as to better characterize diseases that are not yet fully understood (2,3). The use of digital health solutions has the potential to lower costs and demands on healthcare providers, improving the efficacy, efficiency, and sustainability of public health (4). This article will discuss the different kinds of digital health devices and how they can help both doctors and patients to achieve better health outcomes. The future of medicine and healthcare looks to be turning “digital” moving towards the development of virtual hospitals and cutting-edge digital therapeutics, and expanding the variety of treatments that can be offered to tackle disease like never before.  



Table 1: Examples of a variety of digital health devices that are currently available


Examples of Digital Health

mHealth devices

Mobile-health (mHealth) devices are a type of digital health device. These devices are usually hand-held and enable the monitoring of a person’s health or a particular disease or condition that they have been diagnosed with. For example, the IntelliSpace ECG is a device that was first approved in 2013 by regulatory agencies in the United States and Europe for the monitoring of a patient´s heart. The iECG is essentially a phone case that contains electrodes. An electrode is a conductor of electricity. The device allows scientists to study the rhythm of a patient’s heartbeat. The signal coming from the electrodes is converted into an ultrasound that is then detected by the phone’s microphone. This portable device allows the remote monitoring of heart-related diseases. This helps patients to get on with their daily activities more safely (2).

Figure 2: Image of an Intellispace ECG (iECG). A device used to measure heart rate. Image taken from (Dolan B., 2013).


Monitoring diabetes

Conditions such as diabetes can also be monitored using mHealth devices. Work is currently underway to accurately monitor glucose levels in diabetes patients. Dexcom, a leading company in technologies designed for the management of diabetes, has produced an application that determines a patient´s glucose levels every five minutes. This is done using a fine probe that is placed into the skin of the patient. These readings are provided continuously around the clock, alerting patients and clinicians to any changes in blood glucose that may mean that the patient is at risk of hypoglycemia or hyperglycemia. Hypoglycemia refers to instances when the levels of glucose (sugar) in the blood are too low, while hyperglycemia, refers to the condition of a patient when their blood sugar level is too high. Left untreated, these conditions can lead to severe complications such as seizures and can even be fatal in some cases (3).

Figure 3: Image of Dexcom ONE. A device used to monitor patients with diabetes. Image taken from Bloomberg, 2020.
Wearable devices

“Wearable technology or Wearables” are another example of digital health technology. They can be defined as sensors and/or mobile apps that allow for data collection away from a healthcare facility and without the need for trained professionals (3). Wearables aim to provide round-the-clock monitoring at a lower cost than alternative data collection methods. In fact, many of us are already tracking our health using wearable technologies such as Apple watches and Fitbits. Hospitals across the globe including Cedars-Sinai Hospital in Los Angeles (5) are making use of Fitbits to evaluate recovery and mobility in patients. They are also currently being trialed in The Christie NHS Foundation Trust in Manchester (6). Further examples of wearable technology are listed in Table 2.


Table 2: Examples of wearable devices. Description of different wearable devices as well as the company that makes the particular device. Abbreviations: Electroencephalogram (EEG), Electromyography (EMG), Heart Rate (HR), Heart Rate Variability (HRV), Electrocardiography (ECG).
Monitoring diseases associated with the heart

In addition to mobile-health devices, wearable devices are also useful for the study of diseases related to the cardiovascular system. These technologies can measure both heart rate and blood pressure, allowing for the remote monitoring of individuals with high blood pressure or those who have an abnormal heart rate (arrhythmia). The data generated by these devices can help doctors to predict heart-related events that could put the patient in danger (3). An example of a digital health device that is able to monitor diseases associated with the heart is the HeartGuideTM Wearable Blood Pressure Monitor. Unlike other commercially available devices, HeartGuide is clinically accurate and is registered as a medical device by the US Food and Drug Administration (FDA). Therefore, this device can be used in clinical trials (7).

Figure 4: Symptoms associated with Parkinson’s disease. Symptoms of Parkinson’s disease include but are not limited to stooped posture, hand, and leg tremors, as well as difficulty, walking.Image created in BioRender.com.
Monitoring diseases associated with the brain

Aside from their use in monitoring patients with cardiovascular conditions, wearables have also been used to monitor and treat patients with diseases associated with the brain (neurological diseases).  For example, sensors embedded within wearable devices have been used to study Parkinson’s disease. Parkinson’s disease is a neurological disease that affects the functioning of the brain. The effects of Parkinson´s disease arise due to a decrease in the production of a molecule known as dopamine. As the disease directly affects a person’s movement it has been thought that wearable devices such as Fitbit may be used to evaluate symptoms related to Parkinson´s such as involuntary shaking (known as tremors), loss of balance, and impairment of memory and speech (Figure 5) (3).

Figure 5: A diagram of the brain indicating the location of the thalamus. The thalamus is the part of the brain that has been implicated in the tremors associated with Parkinson’s disease. Created in BioRender.com.

A number of digital health technologies have been developed to alleviate the symptoms of Parkinson’s disease. Cala One is a transcutaneous electrical nerve stimulation system that was approved by the FDA in 2018 to control tremors in Parkinson’s disease patients. The device applies electrical stimulation to the surface of a patient’s skin. This stimulates the sensory nerves of the patient. Sensory nerves are made up of cells that carry messages from a person’s limbs to the thalamus. The thalamus being part of the brain implicated in the tremors that Parkinson’s disease patients experience. It is believed that by stimulating these sensory nerves, the process by which tremors occur is disrupted. This helps to reduce the impact of tremors, thereby allowing patients to carry out everyday tasks with less difficulty (8).

Treating insomnia

Recently, the National Institute for Health and Care Excellence (NICE) recommended an application for insomnia as a substitute for taking medications. The app “Sleepio” from the company Big Health UK uses cognitive behavioral therapy techniques to aid people with sleep disorders. Sleepio is distinct from “wellness apps” as it utilizes artificial intelligence algorithms to provide an evidence-based, personalized course of therapy for each individual. The Medical Technologies Advisory Committee actually found that the app was more effective than medications with regards to helping adults to overcome insomnia. Sleepio is thought to be the first of many applications that could be useful to both the UK National Health Service (NHS) as well as clinicians worldwide (9).


Telemedicine can be defined as the remote delivery of healthcare services. During the pandemic, access to many health services e.g., GP consultations and prescriptions were made virtual in order to avoid the risk of patients becoming infected with covid or infecting healthcare professionals and other staff and patients while visiting the hospital or a doctor’s surgery. Virtual services have also helped health services to cope with the shortage of space resulting from the sharp rise in the number of hospitalizations of people with COVID during the pandemic. Virtual hospitals are being set up to facilitate telemedicine. A virtual ward in London, UK is being designed to support patients awaiting heart surgery and allows clinicians to monitor individuals remotely. The digital platform “Ortus iHealth” was developed by Dr. Debashish Das, a consultant who specializes in heart-related disorders and diseases (10).

The platform “collects quantitative data, like blood pressure readings and patient-inputted symptoms, and qualitative data, like responses to questionnaires. It displays that data on a dashboard, alongside a communications link to the patient.”    

 – Dr. Debashish Das.

This project aims to decrease the risk of adverse cardiovascular effects for patients that are currently on the waiting list for heart operations by providing more efficient care both before and after surgery, as well as reducing the number of times that very ill patients need to physically come into the hospital by giving them access to specialists remotely (10).

Digital Health & Precision Medicine

Digital Health is thought to serve as a catalyst for Precision Medicine as the two fields are closely connected. The digitalization of public health will allow for more accurate diagnoses and effective treatment of patients. One of the obstacles to the development of precision medicine is determining how much the environment we live in, as well as our lifestyle, contributes to the characteristics of our disease development, as well as which therapeutics may have a greater impact on us than others. The collection of data via digital health technologies is providing greater clarity as it allows researchers to investigate the influence of specific factors that are separate from our genetic makeup, such as physical activity and diet, on our overall health (11). The rapid and continuing development of the fields of machine learning and artificial intelligence is providing essential tools for analyzing the vast amount of data generated by digital devices and this in turn, is helping to push forward the field of precision medicine (12).

Machine learning & Artificial Intelligence

Artificial intelligence is defined by Microsoft as the “capacity of a computer to mimic human cognitive processes such as learning and problem solving”. A subset or application of artificial intelligence is known as machine learning. Machine learning involves designing mathematical models that are used to teach a computer and which allow the computer system to learn without the need for providing direct instruction to the system every time the model needs to be used (13).

Applications of Machine Learning in Precision Medicine for Cancer

In 2012, the American Society for Clinical Oncology (ASCO) produced a machine learning healthcare system called CancerLinQ. This technology was initially tested in patients with breast cancer. Subsequently, it has been tested on multiple types of cancers. The aim of CancerLinQ is to enable oncologists, (doctors who specialize in the diagnosis and treatment of cancer), to make more informed decisions about the best route of care for a patient. The software achieves this by analyzing patterns observed in individual patients and allows doctors to compare disease characteristics with other similar cases (12). However, access to data from many different patients can raise ethical issues and it is essential that patients are made aware with whom their data is being shared and can consent or decline consent to the sharing of their data.

Rethinking Clinical Trials

In the last few years, digital technologies are increasingly being used in clinical trials. The US Food and Drug Administration (FDA) encourages the use of specific mobile apps to report any adverse effects experienced by clinical trial participants. These apps allow for the continuous collection of data, while allowing people to go about their daily routine, both at home and at work. This makes it possible for the impact of therapeutic interventions being examined through the clinical trial to be more accurately measured (3).  Figure 9 provides a summary of how digital health can impact the clinical trial process in terms of patient enrolment, monitoring of safety, and clinical trial endpoints. ”Endpoints” refer to particular objectively measured outcome/s that are used to determine whether an intervention is beneficial. For example, an endpoint of a clinical trial for a new drug could be that the patient does not experience any severe side effects.

Figure 6: Potential involvement of Digital Health Technologies at different stages of the clinical trials process. Figure showing how digital technologies can be involved at different stages of the clinical trial process, including patient enrolment at the start of the process, safety monitoring of the potential new drug in the middle of the process, as well as endpoints (measures of effectivity) which are used to decide whether the drug should be carried forward for use in patients. Image created using Canva. (3).
What are the ethical aspects of Digital Health?

While the field of Digital Health holds much promise for public health, there are some ethical considerations that need to be addressed (Table 3). As Digital Health technologies often collect vast amounts of data, it is essential that patient data is adequately protected, patient confidentiality is maintained, and the sharing of this data is properly regulated (3). Furthermore, the use of digital health may lead to societal inequalities dependent on the digital literacy of patients (14). Therefore, it will be essential to educate both the public and healthcare professionals who may not be accustomed to using digital devices in their everyday lives or professions, in order to make public health equally accessible to all. In addition to digital literacy, it is also critical that any algorithms that are generated for artificial intelligence (AI) are constructed with the whole population in mind, rather than particular groups. This helps to both eliminate bias and inequality within digital healthcare and to increase the effectiveness of these devices for all consumers (14).


Table 3: How digital health may impact certain ethical values. Table illustrating the different ethical values that may be affected by Digital Health including privacy, security, justice, and autonomy (14).
How are Digital Health devices regulated?

The number of health-related apps and digital health devices being produced is increasing exponentially. How can we ensure that these devices are both accurate and safe to use? Regulatory agencies have come up with their own system to evaluate whether a specific medical device or app and the data it generates can be used to support clinical decision-making. For example, for a specific device to be used in conjunction with a specific medication, it is important that there is an established link between the effectiveness of the drug and the data that the device provides. This demonstrates to regulatory agencies such as the FDA, that the device is appropriate to use for monitoring purposes while taking a particular drug. This is known as a “fit-for-purpose validation” (3). In the UK the Medicines and Healthcare products Regulatory Agency (MHRA), is responsible for the regulation of different medical devices. Requirements for digital health devices in the UK stipulate that the handling of patient data should be carried out under the UK’s General Data Protection Regulation (GDPR). As well as national regulatory agencies, several companies have set up platforms to ensure the safety of digital devices. For example, a digital health quality management platform called ORCHA (Organisation for the Review of Health and Care Apps) applies a well-known risk management approach used in medicine to certify health apps quickly and accurately. ORCHA also provides libraries where you can find the best mobile apps to suit you, wherever you live (15). Figure 7 shows some of the other considerations for the use of new digital health devices to monitor the effectiveness of new therapeutics in clinical trials. Overall, the current focus for the regulation of digital health devices is on their classification. Due to the innovative nature of the field, the scope of digital health devices is broad, and therefore it would not be appropriate to paint all devices with the same brush in terms of their regulation. The future of digital health regulation is still developing as the field is constantly evolving. However,, there is a consensus that a more streamlined approach and official guidelines for data sharing and access are needed, to allow the industry to put good use to the technologies that are on track to reshape the healthcare industry (16).


Figure 7: Some of the factors to be considered in the development and implementation of digital health devices.  Image created using Canva.com.



The field of Digital Health has the potential to transform the way in which clinicians diagnose, treat, manage, and care for their patients. One of the challenges that still needs to be addressed with regard to the implementation of digital health is data protection, as although there are many benefits to making health data more accessible in terms of patient treatment, confidentiality still remains a crucial aspect of medicine and patient care. It is vital that healthcare innovations are accessible to the full patient population and are used to improve healthcare for all rather than for the few. Therefore, in order for the field to advance, collaboration between innovators, patients, and doctors is essential to ensure that new digital technologies and software are designed in such a way that they address unmet needs and that patients are able to access them easily. The future looks to be moving towards having access to healthcare at our fingertips, along with digital solutions to further our understanding of different diseases and their most effective treatments.

Useful links

Digital health – WHO | World Health Organization

Regulating medical devices in the UK – GOV.UK

U.S. Food and Drug Administration



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