A 2.4 GHz ULP OOK Single-Chip Transceiver for Healthcare Applications.

This paper describes an ultra-low power (ULP) single chip transceiver for wireless body area network (WBAN) applications. It supports on-off keying (OOK) modulation, and it operates in the 2.36-2.4 GHz medical BAN and 2.4-2.485 GHz ISM bands. It is implemented in 90 nm CMOS technology. The direct modulated transmitter transmits OOK signal with 0 dBm peak power, and it consumes 2.59 mW with 50% OOK. The transmitter front-end supports up to 10 Mbps. The transmitter digital baseband enables digital pulse-shaping to improve spectrum efficiency. The super-regenerative receiver front-end supports up to 5 Mbps with -75 dBm sensitivity. Including the digital part, the receiver consumes 715 µW at 1 Mbps data rate, oversampled at 3 MHz. At the system level the transceiver achieves PER=10 (-2) at 25 meters line of site with 62.5 kbps data rate and 288 bits packet size. The transceiver is integrated in an electrocardiogram (ECG) necklace to monitor the heart's electrical property.

An ultra low energy biomedical signal processing system operating at near-threshold.

This paper presents a voltage-scalable digital signal processing system designed for the use in a wireless sensor node (WSN) for ambulatory monitoring of biomedical signals. To fulfill the requirements of ambulatory monitoring, power consumption, which directly translates to the WSN battery lifetime and size, must be kept as low as possible. The proposed processing platform is an event-driven system with resources to run applications with different degrees of complexity in an energy-aware way. The architecture uses effective system partitioning to enable duty cycling, single instruction multiple data (SIMD) instructions, power gating, voltage scaling, multiple clock domains, multiple voltage domains, and extensive clock gating. It provides an alternative processing platform where the power and performance can be scaled to adapt to the application need. A case study on a continuous wavelet transform (CWT)-based heart-beat detection shows that the platform not only preserves the sensitivity and positive predictivity of the algorithm but also achieves the lowest energy/sample for ElectroCardioGram (ECG) heart-beat detection publicly reported today.

Parallel processing of large datasets from NanoLC-FTICR-MS measurements.

A new approach for automatic parallel processing of large mass spectral datasets in a distributed computing environment is demonstrated to significantly decrease the total processing time. The implementation of this novel approach is described and evaluated for large nanoLC-FTICR-MS datasets. The speed benefits are determined by the network speed and file transfer protocols only and allow almost real-time analysis of complex data (e.g., a 3-gigabyte raw dataset is fully processed within 5 min). Key advantages of this approach are not limited to the improved analysis speed, but also include the improved flexibility, reproducibility, and the possibility to share and reuse the pre- and postprocessing strategies. The storage of all raw data combined with the massively parallel processing approach described here allows the scientist to reprocess data with a different set of parameters (e.g., apodization, calibration, noise reduction), as is recommended by the proteomics community. This approach of parallel processing was developed in the Virtual Laboratory for e-Science (VL-e), a science portal that aims at allowing access to users outside the computer research community. As such, this strategy can be applied to all types of serially acquired large mass spectral datasets such as LC-MS, LC-MS/MS, and high-resolution imaging MS results.

The Dutch-Belgian beamline at the ESRF.

A brief description is given of the design principles and layout of the Dutch-Belgian beamline at the ESRF. This beamline optimizes the use of the available bending-magnet radiation fan by splitting the beam into two branches, each accommodating two experimental techniques.