How the IoMT is Advancing Remote Patient Monitoring

Shannon Flynn -
Illustration: © IoT For All

The Internet of Medical Things (IoMT) involves using connected devices to enhance health care. Many advancements in this area concern remote patient monitoring. Practitioners can then get a clearer idea of what happens between office visits and which factors lead to deterioration or improvements in a person’s condition. Perhaps you’ve even used a wearable to show your doctor what happens when you experience specific symptoms.

Here’s a fascinating look at some of the IoMT innovations that are moving patient monitoring forward and seem set to do so for the foreseeable future.

Wearables to Catch Main Symptoms of COVID-19

With so much concern over contracting COVID-19, you might wonder if your fitness tracker could give alerts for the telltale signs of fever, shortness of breath, and coughing. One team at Northwestern University determined that such wearables marketed toward consumers are not appropriate for that use. Those devices usually attach to the wrist or finger, which means they’re not ideal choices for detecting a respiratory-based illness.

The researchers came up with a flexible alternative about the size of a postage stamp. It attaches to a patient’s skin just below the suprasternal notch — the noticeable dip at the throat’s base. The pioneering wearable has a pulse oximeter that monitors for abnormally low blood oxygen levels. Accompanying algorithms allow the device to measure skin vibrations that occur when someone breathes or coughs. They also track body temperature.

Wearables: Aid the Rehabilitation Process

For patients recovering from strokes, surgeries to replace multiple joints, or other major events requiring hospitalization, the rehabilitation process is crucial. For example, people in an inpatient rehabilitation facility (IRF) commit to at least three hours of daily therapy, five times per week. Many rehab professionals integrate wearables into their processes, particularly to study a person’s movement patterns.

Wearable portability means that once someone leaves an IRF, a rehabilitation specialist can verify that they maintain a prescribed activity level. Wearables could identify which characteristics of a patient’s movements leave them prone to future injuries. These insights could be precious for a professional athlete trying to avoid a career-ending catastrophe.

Telemonitoring to Keep Risk-Prone Patients Safer

Numerous circumstances — such as if a patient may try self-harm or is at higher-than-average risk of falling — may cause a health care professional to decide a patient needs 24/7 monitoring. The conventional action is to assign a caregiver or family member to watch over the person and ensure they’re never alone. However, that’s not always possible, especially if a person does not have nearby relations or friends.

An emerging option is to use TeleSitters. They’re part of a new class of patient monitoring devices. A clinical technician relies on watching up to 57 patients at once and alert staff members to signs of trouble. One hospital using such a system reports that the average response time to such notification is 15.1 seconds.

Mental Health Monitor Directs College Students to Resources

College students frequently experience mental health struggles, but the perceived stigma surrounding these issues may discourage people from seeking help. A project associated with Texas A&M University hopes to avoid that outcome. Engineers developed sensors and machine learning algorithms to detect excessive anxiety symptoms. The tool works with commercially available smartwatches and provides students with resources to ease their minds.

Besides suggesting that students use mindfulness exercises and biofeedback scenarios presented through the wearable tool, the invention supports the in-person or virtual counseling sessions someone may receive as part of their mental health management. Clinicians can then have a better idea of which interventions are most appropriate for an individual patient.

Wearables Find Trends in Eating Behaviors

Individuals trying to lose or gain weight may follow a nutritionist or other dietary professional’s advice but still fall short. For example, they may occasionally forget to record a day or misremember what they ate over a weekend. A new wearable developed at Carnegie Mellon University called the FitByte aims to eliminate those discrepancies.

The wearable attaches to a pair of eyeglasses and tracks all stages of a person’s food intake. Gyroscopes sense a person’s jaw muscle flexion, while accelerometers pick up on the throat vibrations associated with swallowing. Researchers said their achievement could help health care professionals identify repetitive consumption-related behaviors.

Normalizing High-Tech Monitors

Wearables for remote supervision in health care are not new. In the 1960s, the manufacturer of the Holter monitor let doctors learn more about a person’s heart activity by sending them home to wear it for at least 24 hours. However, these examples indicate that such devices are much more diverse now and reliable in a wide variety of circumstances.

Since the IoMT lets health care providers see what happens when they are not face-to-face with their patients, they could spend less time asking patients to describe their usual activities and more time determining the most effective treatments. Additionally, since these inventions are increasingly non-invasive and user-friendly, patients are more likely to comply with orders to use them.

Many of these IoMT applications are in the early stages. Even so, the results associated with using them are favorable enough to make medical professionals and their current or potential patients take notice.

Author
Shannon Flynn - Technology Writer, rehack.com

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Guest Writer
Guest Writer
Guest writers are IoT experts and enthusiasts interested in sharing their insights with the IoT industry through IoT For All.
Guest writers are IoT experts and enthusiasts interested in sharing their insights with the IoT industry through IoT For All.