Time encoding and reconstruction of multichannel data by brain implants using asynchronous sigma delta modulators.

Recently, information technology and microelectronics have enabled implanting miniature and highly intelligent devices within the brain for in-vitro diagnostic and therapeutic functions. Power and physical size constraints of these devices necessitate novel signal processing methods. In this paper we investigate an effective data acquisition and reconstruction method for brain implants based on Asynchronous Sigma Delta Modulators (ASDMs).

Human perception based video preprocessing for telesurgery.

Video transmission plays a critical role in robotic telesurgery because of the required high bandwidth and quality requirement. We propose an adaptive video preprocessing technique to accelerate the transmission of telesurgical video. Using this technique, the bandwidth can be reallocated adaptively from non-essential surrounding regions to the region of interest when preprocessed image sequences are passed to the video encoder, ensuring excellent image quality of critical regions (e.

Content-based video coding for remote monitoring of neurosurgery.

Transmitting high-quality neurophysiology video via the Internet is a challenging problem in telemedicine. We propose a novel content-selective video data processing and compression method based on the Discrete Wavelet Transform (DWT). Our algorithm is adaptive to intraoperative monitoring video data and has a great scalability on real-time network bandwidth allocation.

Orthonormal-basis partitioning and time-frequency representation of cardiac rhythm dynamics.

Although a number of time-frequency representations have been proposed for the estimation of time-dependent spectra, the time-frequency analysis of multicomponent physiological signals, such as beat-to-beat variations of cardiac rhythm or heart rate variability (HRV), is difficult. We thus propose a simple method for 1) detecting both abrupt and slow changes in the structure of the HRV signal, 2) segmenting the nonstationary signal into the less nonstationary portions, and 3) exposing characteristic patterns of the changes in the time-frequency plane. The method, referred to as orthonormal-basis partitioning and time-frequency representation (OPTR), is validated using simulated signals and actual HRV data.