Daniel Teng

Efficient hardware implementation of an image compressor for wireless capsule endoscopy applications

The paper presents an area- and power-efficient implementation of an image compressor for wireless capsule endoscopy application. The architecture uses a direct mapping to compute the two-dimensional discrete cosine transform which eliminates the need of transpose operation and results in reduced area and low processing time. The algorithm has been modified to comply with the JPEG standard and the corresponding quantization tables have been developed and the architecture is implemented using the CMOS 0.18um technology. The processor costs less than 3.5k cells, runs at a maximum frequency of 150 MHz, and consumes 10 mW of power. The test results of several endoscopic colour images show that higher compression ratio (over 85%) can be achieved with high quality image reconstruction (over 30 dB).

Implementation of a Physical Activity Monitoring System for the Elderly People with Built-in Vital Sign and Fall Detection

Physical activity monitoring of the elderly people provides valuable information for health aware services. This paper presents the implementation of a system to sense, send, display and store physiology activity. The system includes a wearable device to be worn by the individual to collect physical activity data, a wireless communication link between the patient and the monitoring network. A fall detection and heart beat measurement are also included to provide better monitoring. Testing results show the system function properly and provide accurate fall detection and data for monitoring purpose.

A Fall and Near-Fall Assessment and Evaluation System

The FANFARE (Falls And Near Falls Assessment Research and Evaluation) project has developed a system to fulfill the need for a wearable device to collect data for fall and near-falls analysis. The system consists of a computer and a wireless sensor network to measure, display, and store fall related parameters such as postural activities and heart rate variability. Ease of use and low power are considered in the design. The system was built and tested successfully. Different machine learning algorithms were applied to the stored data for fall and near-fall evaluation. Results indicate that the Naïve Bayes algorithm is the best choice, due to its fast model building and high accuracy in fall detection.

Pulse transit time-based blood pressure estimation using hilbert-huang transform

The pulse transit time (PTT) based method has been suggested as a continuous, cuffless and non-invasive approach to estimate blood pressure. It is of paramount importance to accurately determine the pulse transit time from the measured electrocardiogram (ECG) and photoplethysmo-gram (PPG) signals. We apply the celebrated Hilbert-Huang Transform (HHT) to process both the ECG and PPG signals, and improve the accuracy of the PTT estimation. Further, the blood pressure variation is obtained by using a well-established formula reflecting the relationship between the blood pressure and the estimated PTT. Simulation results are provided to illustrate the effectiveness of the proposed method.

Data acquisition system using six degree-of-freedom inertia sensor and Zigbee wireless link for fall detection and prevention

Fall detection and prevention require logged physiological activity data of a patient for a long period of time. This work develops a data acquisition system to collect motion data from multiple patients and store in a data base. A wireless sensor network is built using high precision inertia sensors and low power Zigbee wireless transceivers. Testing results prove the system function properly. Researchers and physicians can now retrieve and analyze the accurate data of the patient movement with ease.

A new decimal antilogarithmic converter

This paper presents a new design and implementation of a 32-bit decimal floating-point (DFP) antilogarithmic converter based on the digit-recurrence algorithm with selection by rounding. The converter can calculate the accurate antilogarithm (10dec) of the 32-bit DFP numbers which are defined in the IEEE 754-2008 standard. The sequential architecture of the proposed 32-bit DFP antilogarithmic converter is implemented on Xilinx Virtex-II Pro P30 FPGA device. The proposed architecture occupies 2, 315 out of 13696(16%) slices and can obtain a faithful 32-bit DFP antilogarithm in 11 clock cycles running at 51.5 MHz. The 7-digit decimal fixed-point (FXP) antilogarithmic converter is an essential operational part of the 32-bit DFP antilogarithmic converter. We transform it to a 7-digit decimal exponential converter to compare with a 24-bit binary FXP exponential converter. The compared results show that the 7-digit decimal exponential converter occupies 2.18 times more area and 1.66 times slower than the 24-bit binary FXP exponential converter.

A novel decimal-to-decimal logarithmic converter

This paper presents a novel design and implementation of a 7-digit fixed-point decimal-to-decimal logarithmic converter. Two approaches, binary-based decimal approximation algorithm (algorithm 1) and decimal linear approximation algorithm (algorithm 2), are proposed and investigated. It shows that decimal linear approximation algorithm (algorithm 2) is error-free in conversion between decimal and binary formats and also able to reduce maximum absolute error from binary-based algorithm 1s 0.00399 (integer cases) and 0.0483 (fraction cases) to 0.000994 (both cases). The Algorithm 2 is modeled in VHDL and implemented using combinational logic only in a Xilinx Virtex-II Pro P30 FPGA device. The logarithms results can be obtained in a single clock cycle, running at 50.9 MHz.

3-10 GHz ultra wideband front-end transceiver in 0.13 μm complementary metal oxide semiconductor for low-power biomedical radar

A new integrated low-power, low-complexity ultra wideband (UWB) transceiver front-end in standard 130 nm complementary metal oxide semiconductor technology which can be used in UWB radar biomedical sensing applications is proposed in this study. The transceiver comprises of a full UWB band transmitter, an on-chip diplexer and a full UWB band receiver front-end. The transmitter generates Gaussian-pulse-modulated and rectangular-pulse-modulated signals at different carrier frequencies within the designated UWB by using a digitally controlled oscillator. The transmitter consumes an average power of 8 mW at a 10 MHz pulse rate. The on-chip diplexer has a 1 dB insertion loss and an isolation of −30 dB. Its switch is co-designed with the receivers input matching network to optimise the power matching while achieving good noise performance. The receiver low noise amplifier has a 3–10 GHz input matching bandwidth with a power gain of 16 dB. The overall receiver front-end consumes an average power of 12 mW. The core area of the transceiver circuit is 500 μm by 1100 μm. The experiments show that the proposed radar transceiver can successfully detect a human respiration pattern within 50 cm. This novel design using a DCO-type UWB transceiver integrated with an on-chip diplexer demonstrates the use of the low power UWB radar detection in biomedical applications.

Reliability modeling for wireless Ultra Wideband biomedical radar sensing network

Impulse Radio Ultra Wideband technology is a newly emerged technology suitable for low-power, low-complex, and low-cost biomedical radar sensing network. Fault tolerance and reliability, and power-saving perform a critical role in the operation of the IR-UWB human bio-sensing network designed for real-time human body health monitoring. In this paper, an IR-UWB bio-sensing network is proposed and the continuous Markov process is applied to model the proposed UWB bio-sensor network. Two different models are investigated, one is sensor with three transmitting power levels, and the other is sensor with six power levels. Both of them consume same total amount of power. The radar sensor and the sink node Markov model with repair rates taken into account are modeled as well. The paper is a contributing effort to develop an analytical model and explore the trade-offs in wireless IR-UWB bio-sensor network in terms of predicted reliability, operation time (MTTF), and power consumption.

Radar Sensing Using Ultra Wideband – Design and Implementation

Ultra-wideband (UWB) has received significant attention for applications in target positioning and wireless communications recently. The extremely short pulses in turn generate a very wide bandwidth and offer several advantages, such as large throughput, covertness, robustness to jamming, lower power, and coexistence with current radio services. UWB not only can transmit a huge amount of data over a short distance at very low power, but also has the capability to pass through physical objects that tend to reflect signals with narrow bandwidth.