Article | “Implementing AI in Wearable Health Apps for Better Tomorrow”

Source: Peerbits Author: Noman Shaikh For practical wearables and Internet of Things (IoT) implementations, Artificial Intelligence studies specific problem solving or reasoning tasks.

 Healthcare mobility solutions boast capabilities such as visual perception, speech recognition, and decision-making.

But wearables and the Internet of Things (IoT) work without an AI engine, why do we need it in the first place.

Because the true value lies in insights.

Artificial intelligence (AI) and machine learning are two vital tools for insights.

Without an AI engine, the data from a wearable would lack any value to the vendor as well as the user.

That’s the reason why, wearable app developers are increasingly adding AI Engine inside wearable health apps and wearable health solutions.

Moreover, AI assisted data mining is also essential to the success of an intelligent healthcare platform that ties many smartphones, website, IoT devices and wearables together to gather data and return intriguing health insights of an individual.

Building the platform-machine learning The platform should contain data points from various medico-sources such as manuals, journals, and public health data to emulate a doctor’s knowledge.

Upon adding patient-specific data, effects of time and location to the platform’s enormous data set, the machine learning system can generate a clinical model of a patient.

Compatible medical wearables and IoT devices can interface with the platform’s API and can be made to exert interesting insights about the data received from the devices.


Wearables for preventive health Google wants to inject nanobots in your arteries.

Don’t be scared already.

If they could find a way to take them out, Google X could be the next breakthrough in medtech.

Once injected via capsules, nanoparticles proactively detect and diagnose diseases, cancers, impending heart attacks or strokes based on changes to the person’s biochemistry, at the molecular and cellular level.

The patient then can use a wearable like a wristwatch clamped on his wrist to receive reading from nanoparticles (nanoparticles are actually IoT devices).

The wearable then feeds the data to the AI engine of the platform and utilizes its machine learning capabilities to detect abnormalities if any in the wearer’s body.

If detected, the wearable reports a potential condition like blocked arteries that could lead to heart stroke or cancerous tumor at a very early stage.

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