2014-495 Wireless Wearable Big Data Brain Machine Interface (W2B2/WWBB)

Wireless Wearable Big Data Brain Machine Interface (W2b2/Wwbb)

 

SUMMARY

UCLA researchers have developed a wireless wearable big data brain machine interface. This technology provides a user-friendly brain machine interface system that can monitor/record a large amount of brain activities and transfer, wirelessly, the processed/raw data to a remote mobile unit.

 

BACKGROUND

A brain machine interface is a direct communication pathway between the brain and an external device. It is often directed at assisting, augmenting, or repairing human cognitive or sensory-motor functions. There is a need to improving the quality of neuronal recordings, achieve stable, long-term performance, and extend the brain-machine interface approach to a broad range of motor and sensory functions. The brain-computer interface market is technology-driven and is continuously witnessing various technological advancements, which has led to high functionality and miniaturization of devices. The traditional use of EEG devices as a diagnostic tool has now expanded to a range of applications.

 

INNOVATION

- User-friendly wearable brain machine interface system

- Ability to monitor and record large amount of neural activity to a remote terminal wirelessly

 

APPLICATIONS

- Investigating brain activity mapping

- Monitoring function during neurosurgery

- Diagnosing brain abnormalities

- Developing new technology/treatment to prevent/cure brain-related illness

- Develop more advanced brain-machine interface systems

- Control wearable prostheses

- Control exoskeletons

 

ADVANTAGES

- Big data transfer

- High throughput data transfer

- Fine and large scale resolution of neural activity

- Wireless communication: it enables the patient/subject to move freely

- Wearable format

- Real-time neural activity monitoring

Patent Information:
For More Information:
Megha Patel
Business Development Officer
Megha.patel@tdg.ucla.edu
Inventors:
Wentai Liu
Mau-Chung Frank Chang
Yan Zhao
Yen-Cheng Kuan
Yi Kai Lo