Hardware

Tapping Into The Emotional Internet

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Gareth Price

Contributor

Gareth Price is the technical director at Ready Set Rocket.

Wearables currently decipher physiological biometrics: heart rate, pulse, caloric intake. But in the coming years, we’ll see emotion-sensing wearable technology that clues us into specific human emotions.

When this data is shared across networks, we’ll enter the dawn of the “Emotional Internet.”

This is not a purely theoretical concept. Already, there are efforts to measure and quantify human emotion in a machine-readable way. Affectiva, an emotion-measurement technology firm, has collected more than a billion frames of spontaneous facial expressions, using the data to develop technology that can detect several types of emotions.

One of the initiatives of Microsoft Research’s Visualization and Interaction for Business and Entertainment (VIBE) division, meanwhile, is to explore human-computer interaction. It has designed a prototype scarf that employs sensors to discern the wearer’s mood and, via Bluetooth, the moods of others.

Another company, Spire, manufactures a small stone-shaped sensor that can be clipped to a bra strap or belt and is able to pick up on your stress levels.

Much of this research and development is part of the emerging field of affective computing, which examines ways to create sensors and computers that can detect and respond to human emotions.

By studying speech patterns, facial expressions, body gestures and physiological reactions to specific stimuli, researchers hope to amass a database of emotions they can train computers to recognize and interact with.

The key challenge here is to establish a standard for what is definitively “happy,” “sad,” “angry” or another state, because right now, many apps and devices that claim to read emotions aren’t drawing from one definitive standard.

Once this occurs, it will be possible to quantify and upload this information into a computer and create devices that can accurately interact with emotions.

Think “wearables that can detect patterns in how you feel when you engage in certain activities” — telling you, for example, that you feel happiest after a rigorous workout or depressed a few days after you’ve had a bit too much to drink.

And now that social media is a part of virtually everyone’s lives, it doesn’t seem far-fetched that once we know what we feel with near-complete accuracy, we’ll share it with others.

Think of how many times you’ve seen a status update where someone says they are feeling happy about something good, or mad, sad or indifferent about another thing.

Emotion-sensing wearable technology will take this to a far deeper level. If we can better understand what makes us tick psychologically, we can learn ways to improve our emotional states and our relationships with other people. Take the pplkpr app as a rudimentary, but instructive, example of how this might work.

Created in a somewhat tongue-in-cheek manner by two artists-in-residence at Carnegie Mellon University, it uses a heart-rate monitor that connects to Bluetooth to measure your response to people around you.

It detects patterns in your body’s reaction to someone, letting you know if he or she makes you anxious, excited or aroused. Over time, you can track how a particular person makes you feel, allowing you to determine if the relationship is healthy or unhealthy.

This also crosses into the workplace. In a well-known study looking at happiness in teenagers, the psychologist Mihaly Csikszentmihalyi found that his subjects were happiest when they were in what he calls a “flow state,” where one is fully engaged with an activity or task. Imagine a device that could help you determine which job duties put you into this “flow state.”

In fact, Hitachi, which has collaborated with Csikszentmihalyi, has invented its Hitachi Business Microscope. Small enough to fit inside the lanyard holding a typical work badge, this sophisticated device can measure, among other things, some of the biometric factors that Csikszentmihalyi and others have posited might indicate a “state of flow.”

We are coming closer than we think to technology that can actually make us happier. It starts with machines, likely in the form of wearable technologies, that can read and interpret emotional information. Once we bring in the human element and share this information with each other, we will realize much broader implications.

Providing we construct a strong set of ethical guidelines for gathering and using such personal data sets, we’ll be tapping into that Emotional Internet and leveraging its power to profoundly change our lives for the better, individually and collectively.

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