Whether it’s industrial worker safety or personal well-being from a clinical point of view, wearable technology provides the individual with a way to predict and prevent potentially hazardous health conditions.

But while this new technology is definitely exciting, building solutions for precise physiologic monitoring can be challenging on many different levels. Let’s take a look at the overall importance of this developing technology and how biometrics are now being used to reduce injuries, optimize health, and prevent against adverse health conditions.

This post summarizes the discussion in a webinar held with Kenzen CEO Jim McDonnell. You can watch that webinar here or continue reading for more information:


The Growing Concern of Worker Safety

One big reason for the continued growth of wearable technology and biometric monitoring is the overall concern for worker safety. In the U.S. alone, there are currently 130 million workers who fall into the high-risk category. While this has damaging effects personally and monetarily for the individual, employers are also estimated to spend 220 billion on injury and illness for these workers.

Of this sector, 260K of these high-risk individuals are being subjected to heat-related illness. While this number might not seem large at first, keep in mind that heat-related illness is often the cause of other avoidable injuries due to impaired or declining cognitive function—making the end number potentially much higher than what is being accounted for.

To combat some of this basic risk scenarios, sensor-based technology is starting to become more accepted as a piece of personal protective equipment (PPE) in the same line as a helmet or pair of gloves. But unlike other basic protective equipment, wearable technology can be personalized and provide data specific to the individual to improve overall safety.

Why a Solution is Needed Now

Even though concern for worker safety isn’t new, there are several factors driving the immediate need for solutions. Rising temperatures across the planet due to environmental changes are increasing the cause of death and injury, and as more people continue to work in these conditions the more these numbers will continue to grow.

This creates an extra burden for insurers, as the number of workers with worker’s compensation insurance coverage has double in countries like China over the past 10 years. On the employer side, more scrutiny is placed on enforcing regulations which can turn into fines or legal issues for cases of oversight as it relates to worker issues.

The reason heat-related health injuries continue to be a challenging problem is that the guidelines for protecting workers are very generic. This is largely due to the fact that heat is a personalized and contextual condition, and every individual responds to the stresses of the environment in a different manner. This makes it nearly impossible to implement a standard temperature/rehydration guideline for all workers to adhere to, and isn’t a realistic option to protect workers from heat-related illness.

Because of this, a sensor-based approach that can be personalized makes more sense in determining when a person needs to take time to cool down and rehydrate versus when it may not be needed.

How it Works & Sensor Overview

Real-time bio-sensing technology is currently being developed by companies like Kenzen to solve some of these heat-related stress issues. But this technology and overall analytics platform has the potential to be applied in other industrial, sports, and healthcare markets too.

In addition to bio-sensing devices that can measure vitals and activity, these units have the capability to measure biomarkers like sweat for analysis. Once the data is collected, the information that’s gathered from the individual is put into a cloud platform, dynamically notifying a person when a danger such as heat stress may be present. When the notification is given, supervisors will also be able to monitor an individual and ensure that appropriate actions (such as rehydration, etc.) have been taken to protect themselves from injury.

As for the Valencell sensors, there are currently seven different sensors on each unit to measure PPG, heat flux and skin temperature, sweat rate, a one-lead ECG, optical sensors for hydration levels, and an IMU for data on linear and rotational motion. This information is put into the machine learning model to provide individualized results that can change over time depending on how a person adapts to the activity or environment.

The units communicate through wireless BLE connectivity with a 30-hour runtime. Twenty-four hours of data can be stored on the device itself, and haptic feedback has also been included to alert workers who may not be closely monitoring the device as they perform a task. They sensor models have been designed to attach to a disposable adhesive patch that is ideally worn on the chest, which allows for accurate ECG measurement and improved core temperature assessment. Alternatively, the adhesive patch and sensor can also be worn on the upper arm.

Predictive Prevention & The Future

Notifying an individual and members of a safety team that the potential of injury has been elevated is the core principle behind the predictive prevention model. This method of analyzing data real time through biometric sensing has the ability to prevent unnecessary incidents from occurring and keep workers in hazardous occupations safe.

Though models are currently being focused on industries that force workers to operate in high heat environments or are extreme in exertion levels, it can be applied to other markets as well. Professional and youth athletics, the military, elderly home care, and other areas where clinical data of an individual could be highly useful are examples of where this technology could be deployed in the future.

Along with the four-core data readings (heart rate, sweat rate, core temp, and activity), the ability to measure ion-related conditions can provide notifications of imbalances in potassium, sodium, and pH. This can provide information on individuals who are at risk for things like heart failure and kidney disease. Condition-specific models that can notify individuals of at-risk conditions like diabetes, women’s health, and inflammation in the body will also be possible in future models.

These new biomarkers will be measured with Kenzen’s next generation of smart patches that includes a variety of biomarker analysis. These smart patches layer in the electric chemistry readings from sweat to measure things like glucose, lactate, cortisol, and hormones in addition to the data points measured by today’s adhesive patches. A current project with GORE is underway to develop flexible, breathable materials to deliver a patch using their materials.