Now a smart chip that can wirelessly transmit brain signals

Scientists, including one of Indian-origin, have developed a smart chip that can be paired with neural implants for efficient wireless transmission of brain signals

By: PTI | Updated: February 14, 2016 2:17 pm
smart chip, wireless transmission chip, science, Prostheses, Nanyang Technological University, Singapore, brain signals, tech news, technology Scientists have developed a new low-power chip that can transmit brain signals to prosthetic limbs (Source: Nanyang Technological University, Singapore)

Scientists, including one of Indian-origin, have developed a smart chip that can be paired with neural implants for efficient wireless transmission of brain signals to help combat Parkinson’s disease or allow paraplegic people to move their prosthetic limbs.

Neural implants need to be connected by wires to an external device outside the body. For a prosthetic patient, the neural implant is connected to a computer that decodes the brain signals so the artificial limb can move.

These external wires are not only cumbersome but the permanent openings which allow the wires into the brain increases the risk of infections.

The new chip by Nanyang Technological University, Singapore (NTU Singapore) scientists can allow the transmission of brain data wirelessly and with high accuracy.Assistant Professor Arindam Basu from NTU’s School of Electrical and Electronic Engineering said the research team have tested the chip on data recorded from animal models, which showed that it could decode the brain’s signal to the hand and fingers with 95 percent accuracy.

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Assistant Professor Arindam Basu from NTU’s School of Electrical and Electronic Engineering said the research team have tested the chip on data recorded from animal models, which showed that it could decode the brain’s signal to the hand and fingers with 95 percent accuracy.

“It is about a hundred times more efficient than current processing chips on the market. It will lead to more compact medical wearable devices, such as portable ECG monitoring devices and neural implants, since we no longer need large batteries to power them,” said Basu.

To achieve high accuracy in decoding brain signals, implants require thousands of channels of raw data. To wirelessly transmit this large amount of data, more power is also needed which means either bigger batteries or more frequent recharging.

This is not feasible as there is limited space in the brain for implants while frequent recharging means the implants cannot be used for long-term recording of signals.Instead of enlarging the power source to support the transmission of raw data, Basu tried to reduce the amount of data that needs to be transmitted.

Instead of enlarging the power source to support the transmission of raw data, Basu tried to reduce the amount of data that needs to be transmitted.Designed to be extremely power-efficient, the smart chip will analyse and decode the thousands of signals from the neural implants in the brain, before compressing the results and sending it wirelessly to a small external receiver.

Designed to be extremely power-efficient, the smart chip will analyse and decode the thousands of signals from the neural implants in the brain, before compressing the results and sending it wirelessly to a small external receiver.

The smart chip is designed to analyse data patterns and spot any abnormal or unusual patterns.

For example, in a remote video camera, the chip can be programmed to send a video back to the servers only when a
specific type of car or something out of the ordinary is detected, such as an intruder.

This would be extremely beneficial for the Internet of Things (IOT), where every electrical and electronic device is connected to the Internet through a smart chip.

Using the chip, the devices can process and analyse the data on site, before sending back important details in a compressed package, instead of sending the whole data stream. This will reduce data usage by over a thousand times.

The research was published in the journal IEEE Transactions on Biomedical Circuits and Systems.