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HaiVision’s MAKO-HD™ Provides Speed, Reliability Key to CRAN Telesurgery Project

MONTREAL — Jan. 26, 2009 — HaiVision Systems Inc., the world’s leading vendor of high-definition (HD) H.264 telepresence codecs, today announced that its hai1000™ codec systems, equipped with the exceptionally low-latency MAKO-HD™ H.264 codec, are being used by France’s CRAN (Research Center for Automatic Control) to support the study of robot-assisted telesurgery. Implemented as part of the RALTT (Robotic Assisted Laparoscopic Telementoring and Telesurgery) project at the hospital of Nancy-Brabois, HaiVision’s advanced H.264 / MPEG-4 AVC compression technology enables reliable low-latency transfer of video over a VPN linking two test sites.

“The success of the RALTT project hinges on our ability to achieve high standards for video compression and transmission, as these principal technology elements are critical to the surgeon’s work and, ultimately, the health of the patient,” said Nedia Nouri, a CRAN doctoral student and member of the RALTT project team. “Telesurgery holds enormous potential for medical facilities and their patients, and HaiVision’s advanced encoding technology is proving to be a key enabler in making this exciting model a reality.”

The CRAN RALTT project was created to study the feasibility of surgical operation techniques relying on assisted robots (da Vinci® robots from Intuitive Surgical) to enable remote surgery with the doctor and patient at two different locations. The goal of the project is to define subjective tolerance limits of use. HaiIVision’s advanced MAKO-HD provides surgeons with very fast and reliable video feedback over a long-distance link. A delay of 1 or 2 seconds is not acceptable for surgical applications, so the MAKO-HD’s ability to reduce latency below 100 ms is critical to the success of CRAN’s tests.

“Most of the technological issues in this project relate to encoding and transmission latencies, and our goal is to maintain the best picture quality with the shortest delays,” said Victor Mauroy, applications engineer for Equipements Scientifiques, which is providing technical support for RALTT. “We have compared many video encoders, and found that HaiVision products offer the best combination of performance, low latency, and reasonable prices. The company has a reputation for providing the fastest HD video encoders ever, and the hai1000 and MAKO-HD correspond to our needs perfectly. They are easy to use, and their performance has been outstanding.”

The hai1000 telepresence codec system delivers the highly efficient MPEG-4 AVC / H.264 video compression standard at unsurpassed levels, enabling communication of high-resolution HD (up to 1080p) or SD video and super wideband audio across IP networks at bandwidths anywhere from 256 kbps to 10 Mbps. The MAKO-HD “zero latency” codec from HaiVision is the highest-performance H.264 codec available for HD, supporting up to 1080p resolution and an imperceptible 70 millisecond end-to-end latency.

Complete information on HaiVision products, including recent case studies and application notes, is available at www.haivision.com/account/downloads/.

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About CRAN
The Centre de Recherche en Automatique de Nancy (CRAN) is a research center funded by the Centre National de la Recherche Scientifique (CNRS) and two universities in Nancy: UHP (Université Henri Poincaré) and INPL (Institut National Polytechnique de Lorraine). The CRAN was set up in Nancy, France, in 1980, and its research activities concentrate on five principal themes: automatic control, systems observation and control, system identification and signal processing, dependability and system diagnosis, health engineering, and ambient manufacturing systems.

About HaiVision Systems Inc.
Based in Montreal, Canada, HaiVision Systems Inc. is a private company and a world leader in delivering the most advanced video networking technology. HaiVision’s products are deployed worldwide within the foremost telepresence suites and boardrooms, in healthcare facilities for video collaboration and training, for continuous presence distance education and remote learning, and within broadcast for remote interviews, IPTV, and content distribution.

ENDS

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