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How technology can bring an additional layer of AI to wearable devices

Whilst AI implementations have yet to compete with the learning speed and intuition of a human, things are starting to change.

By James Nunns

Feel the pulse

Ever since Pulsar launched its calculator wristwatch back in the 80’s, wearable devices have been increasing in popularity. However, after a few spluttered starts, it wasn’t really until the launch of the Fitbit several decades later that the segment really took off in the consumer realm. It is predicted that by 2020 the number of connected wearable devices worldwide is expected to reach 830 million[1]. Up from the 325 million devices currently in use.

The term that has become ubiquitous with wearable devices is “smart”, yet often the devices aren’t nearly as smart as we give them credit for. This is about to change though, with patent-pending technology becoming available that can add an additional layer of artificial intelligence (AI) onto a new wave of wearable devices.


Ignore the doomsayers

Whilst there will always be doomsayers that will warn about the rise of the machines, most of us have become used to the concept of AI and the benefits it brings. Found in everything from computer games to lawn mowers, AI applies to any machine that mimics cognitive functions that humans associate with other human minds, such as learning and problem solving.

It is thought that in as little as a generation’s time, the mere concept of driving yourself anywhere will be outdated. Autonomous cars with AI at their core are being developed by all of the major car manufacturers (along with the likes of Apple and Google) and are capable of sensing their environment and navigating without human input through the likes of radar, laser light, GPS, odometry, and computer vision.


Time for an appraisal

To add AI on to wearables, we need them to understand human emotions as best as possible. To do this, advanced machine learning technology as well as psychological models are being built based on the Appraisal Theory used in psychology. The theory relates to the principle that a person’s emotions are extracted from a live evaluation of events that cause specific reactions. Essentially, our appraisal of a situation causes an emotional, or affective, response that is going to be based on that appraisal. Think how your own mood may change with the weather.

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Getting emotional

Previously, only heavy emotional classes such as anger and happiness were able to be classified using speech analysis on a wearable device. However, today far greater emotional nuances can be recognised in real time, giving a far better reading of the subject’s complex emotional state.

Using social and emotional AI, technology can listen between the lines of text and detects when, how and under what condition something is said, not what. This gives a deeper insight that simple speech recognition cannot and fundamentally can enable machines to act and react socially and emotionally competent.

The integration of AI based on advanced machine learning including deep learning and transfer learning methods into wearables and hearables will change how we interact with our devices. Better emotional classification can only enhance the user experience to drive higher usage and enable them to reach higher levels of predictability and intelligence.


The silver bullet

The ability for devices to classify emotions accurately in real time empowers a whole host of applications and devices with a previously unheard-of layer of artificial intelligence. Adding an emotional classified AI could be the silver bullet that wearable and hearables need to be able to not only enrich all our lives but potentially save them too.


The potential use cases for such intelligence are numerous but include the ability to use the technology to analyse the breathing pattern, paralinguistic or emotional state of a professional athlete to provide detailed feedback on their execution that could then be used to enhance future performances. Or in a mental health environment, where having the technology implementation on a wearable device would mean you could analyse a patient’s mood throughout the day, monitoring their emotional state 24/7 to build up a better picture of what care was needed.


Changing times

Research group Counterpoint believe that AI powered wearables will grow 376% annually this year to reach 60 million units[2]. The biggest growth sector will be hearables, with it predicting they will contribute 50% of the AI powered wearables market in 2017, growing over 2500% annually[3].

Times are changing. We already have a much smarter Siri on the Apple Watch, Alexa can now be wrist-mounted thanks to the Martian mVoice watch and the latest Android smart watches have had the impressive Google Assistant built in. Whilst AI implementations have yet to compete with the learning speed and intuition of a human, things are starting to change. Meaning wearable and hearable devices will soon have the ability to be as smart, or as real, as you or I.

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