Tag Archives: mind reading

brain scans can see your mind’s eye

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Scientists in Japan now have a brain scan that can recreate an image in someone’s minds eye fairly accurately. This could have positive applications, for example to help the disabled. The security and big brother implications seem a bit ominous though.

As the accuracy of the technology continues to improve, the potential applications are mind-boggling. The visualization technology would allow you to draw pictures or make art simply by imagining something; your dreams could be visualized by a computer; the hallucinations of psychiatric patients could be visualized aiding in their care; and brain-machine interfaces may one day allow communication with imagery or thoughts, Kamitani tells CNBC Make It.

While the idea of computers reading your brain may sound positively Jetson-esque, the Japanese researchers aren’t alone in their futuristic work to connect the brain with computing power.

For example, former GoogleX-er Mary Lou Jepsen is working to build a hat that will make telepathy possible within the decade, and entrepreneur Bryan Johnson is working to build computer chips to implant in the brain to improve neurological functions.

wireless ECG

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This paper from MIT describes a technology that can read emotions accurately by detecting heartbeats simply by bouncing a wireless signal off a person. It is supposedly as accurate as a an electrocardiogram. Reading emotions this way is pretty amazing, but to me just the idea of reading a heartbeat accurately this way sounds like a pretty big deal in a medical setting. It also could have obvious implications in psychology, and quite possibly disturbing uses in security, intelligence, military and business settings. Imagine something like Google Glass giving you information on the health and emotions of a person you are talking to.

Emotion Recognition using Wireless Signals

This paper demonstrates a new technology that can infer
a person’s emotions from RF signals reflected off his body.
EQ-Radio transmits an RF signal and analyzes its reflections
off a person’s body to recognize his emotional state (happy,
sad, etc.). The key enabler underlying EQ-Radio is a new
algorithm for extracting the individual heartbeats from the
wireless signal at an accuracy comparable to on-body ECG
monitors. The resulting beats are then used to compute
emotion-dependent features which feed a machine-learning
emotion classifier. We describe the design and implementation
of EQ-Radio, and demonstrate through a user study
that its emotion recognition accuracy is on par with state-of-the-art
emotion recognition systems that require a person
to be hooked to an ECG monitor.