Study of clustering algorithms for brain computer interface using wireless sensor networks

Abstract

BCIs are often directed at expanding, assisting or restoring human sensory-motor or cognitive functions by offering a direct communication route between the human brain and any external devices. In Invasive BCI the sensors are implanted inside the brain on the surface of cerebrum. So far invasive BCI using wireless sensors has not been achieved. Most research to date regarding invasive BCI using wireless sensors has revolved around communications along the surface of the body by the use of traditional electromagnetic (EM) radio-frequency carrier waves. The major impediment that we face today in order to enable this dream of networked-implantable-devices is caused by the physical nature of propagation in humans. Our body is composed primarily of water, which is a medium through which Radio frequency EM waves do not easily propagate. Therefore, in this article we take a distinctive perspective and inspect the possibility of using ultrasonic waves to wirelessly interconnect sensors in the brain. We propose a new energy model required for ultrasonic propagation. Since the sensors need to be implanted inside the brain, therefore to avoid frequent implants we design a new clustering algorithm which overcomes the drawbacks of existing LEACH algorithm and uses lesser energy, hence enhancing the lifetime of sensors.