MetaMedical™ Solutions Inc

AI has the potential to make smartwatches a user’s definitive health copilot

Utilised correctly, AI has the potential to make smartwatches a user’s health copilot thanks to its myriad capabilities such as health monitoring, stress management, personalised insights, fitness coaching, emergency alerts, and early detection of diseases and potential health issues, among others.

However, striking the right balance between convenience and accuracy is vital.

Smartwatches are increasingly being used for health and fitness monitoring

Most smartwatch vendors are currently targeting their devices toward the consumer market, and the development of accurate clinical-grade products is challenging. Smartwatches still lack the killer use case that would make them indispensable to healthcare.

Smartwatches today are primarily used for tracking sleep, activity, the menstrual cycle, blood oxygen levels, as well as electrocardiogram (ECG) monitoring.

While the accuracy and clinical relevance of some of these are still in question, the various data collected from smartwatches can help identify potential health concerns before even the obvious symptoms appear.

In 2022, Xplore Lifestyle and CardiacSense collaborated to offer smartwatches that monitor heart activity and alert clinicians and patients’ families when they detect an abnormal or irregular heartbeat.

A study published in a Nature Medicine report that same year tested the ability of a smartwatch to accurately detect heart failure in non-clinical environments.

In February 2023, the Murdoch Children’s Research Institute partnered with Apple to use the Apple Watch’s ECG data to study cardiac toxicity for cancer treatment in children.

AI can unleash the potential of smartwatches

One benefit of AI integration in smartwatches is the ability to boost a device‘s interaction with users through voice technologies using conversational platforms.

These platforms employ a variety of AI technologies – including natural language processing, context-aware computing, and machine learning – to enable human-like voice interaction.

Apple, for instance, provides Siri support on its smartwatches, and Google’s Assistant is on its Wear OS watches. Users can access news, send messages, track exercises, play music, and make flight reservations (among other things) using these conversational platforms, without the need to access apps manually.

Elsewhere, startups are equipping their wearables with AI. Sensoria Fitness provides consumers with in-app coaching to improve running routines using performance analytics while Qardio products gather health data from wearables, analyse it, and then use an algorithm to prioritise the patients that need more attention.

AI-enabled smartwatches can collect health-related data, analyse it, and provide tailored health insights and guidance.

In May 2023, Zepp Health launched Zepp Coach, its AI-powered coaching algorithm that provides a training plan based on a user’s physical characteristics, exercise experience level, and preferred training time per week.

The AI monitors a user’s fatigue level, fitness level, and training status as they progress and subsequently modifies the intensity of the training plan.

AI in smartwatches can also better identify patterns that might indicate the onset of certain health conditions.

Researchers at the UK Dementia Research Institute and the Neuroscience and Mental Health Innovation Institute at Cardiff University found that smartwatch data can be used to predict Parkinson’s disease seven years before the symptoms appear.

AI-powered smartwatches must address privacy concerns

Although the use of AI in smartwatches is increasing, concerns around privacy, data security, and accuracy must be addressed for the devices to become an efficient health copilot. If the AI system malfunctions, it could cause panic, confusion, and mistrust among users.

Smartwatch vendors must prioritise the development of accurate AI algorithms to ensure the reliable functionality of their smartwatch health features.

They must ensure that AI systems are free of bias, as this can result in discrimination or unjust decision-making.

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