Wearable biosensors have been widely used to assist disease diagnosis or monitor health conditions, making the authorization to communicate with these biosensors very critical. The potential tampering attack may cause disasters that threaten human lives. In this paper, a tampering attack detection method is proposed for securing key parameters of a real-time ECG monitoring system. The detection method is based on a built-in triangle waveform and the corresponding extracted abnormal pattern vector examination. When the deviation of the pattern vector is above the defined attack detection threshold value, we could recognize that an attack occurs. Two representative records of ECG data are used to evaluate the different attack levels impact. The proposed tampering attack detection framework is implemented using 0.18 $\mu m$ standard CMOS process and costs 41413 $\mu m ^{2}$ chip area, with an estimated dynamic power consumption of 15 nW, which is very hardware-efficient and easy to be implemented.

This paper presents a ternary low-density parity-check (LDPC) error correction system for wireless electrocardiogram sensors to improve the accuracy of arrhythmia classification. The classification system is based on ternary Delta-modulated bitstreams and rotation linear kernel support vector machines, which identifies the supraventricular ectopic beat (SVEB) and the ventricular ectopic beat (VEB) over the normal heartbeats. We model errors using a ternary symmetric channel with probability parameter$p$and construct a variety of ternary LDPC codes with different coding rates by concatenating two-component sub-matrices to form a parity-check matrix with a quasi-cyclic structure that facilitates the hardware design. In particular, a hardware-friendly LDPC encoder circuit is proposed that leverages the highly structured parity-check matrix to perform serial generation of the parity symbols using an accumulator and a look-up table. The encoder circuits are implemented on FPGA and synthesized on ASIC using a 32 nm CMOS process. Simulation results show that the ternary LDPC codes can significantly improve classification accuracy in the presence of errors. For example, with an error probability of up to 21% in the sensor output bitstreams, the classification accuracy remains above 99% with the proposed error correction system.

The divider is one of the most complex hardware units in Stochastic Computing (SC); even though several new designs have been presented to reduce the computation latency of the conventional divider, all of them still require a considerable number of clock cycles. Moreover, they incur in low performance due to the employed arithmetic computational scheme. In this paper, a Delta Sigma Modulator (DSM) based stochastic divider is proposed. As an entirely digital circuit, the proposed divider offers the best computation latency and accuracy over all existing stochastic dividers found in the technical literature (with a typical reduction between 66.8% and 96.9% in the number of clock cycles and a reduction from$10^{\mathrm {-3.4}}$to$10^{\mathrm {-3.9}}$in the average mean square error for a 10-bit resolution). An SC-based Neural Network (NN) is considered as an initial case study to evaluate the advantages of the proposed design in an emerging application; results show that the proposed divider enables an SC-based NN to achieve a higher classification accuracy and hardware efficiency than existing designs. To show the flexibility of the proposed divider design, its application to Sobol-based sequences is also presented; also in this case, its superiority over other designs is confirmed. These features make the proposed design very attractive for hardware-constrained platforms; moreover, such a novel design approach that incorporates ideas from analog/mixed signal circuit design into a digital circuit design, can motivate other researchers to design efficient SC designs using similar schemes.

This paper reports a novel optical localization method, including both the hardware design and algorithm design, to track mobile Unmanned Aerial Vehicles (UAVs). The method relies on a circle-shaped blinking LED marker installed on the UAV and uses a single Dynamic Vision Sensing (DVS) camera to sense the temporal difference of the video streams. A temporal-filtering algorithm processes the video stream and detects the target marker by filtering out the background image. The triangulation-based spatial localization algorithm captures the trace of the target with the help of the prior knowledge of the physical size of the marker. The proposed system was evaluated in flight tests and compared with ground truth data provided by a motion capture system. The proposed system provides a simple and accurate localization solution for UAV tracking with a low computing overhead.

In this paper, we present a compressed sensing based framework for a wireless sensor based biological sensing system for recording the frequency of fish electric organ discharge. We investigate the trade-offs between the parameters of compressed sensing, such as sampling matrix, reconstructed signal's signal to noise ratio, and compression ratio. The measured results show that our framework can be used to reduce the transmitted data size by 70% (3×) while maintaining at least 10 dB signal to noise ratio for the reconstructed time domain frequency data. This size reduction with acceptable reconstructed signal quality will help reduce transmission energy and storage requirements for long-term sensing experiments, thus enabling the use of small and low power wireless sensors.

We present a non-coherent wireless communication testing platform for ultra wide-band impulse radio (UWB-IR) with frequency-shift-keying (FSK) on-off-keying (OOK). Both transmitter and receiver platform will be present with a control graphic user interface (GUI) supported by Spartan-3 FPGAs. The transmitter chip is integrated while the receiver is build from off-the-shelf components. Monopole antennas are used in the system. The demonstration shows a transformative wireless communication technology for low power low cost short range applications.

In this paper we present a low power temporal-difference image sensor with wireless communication capability designed specifically for imaging sensor networks. The event-based image sensor features a 64 × 64 pixel array and can also report standard analog intensity images. An ultra-wide-band radio channel allows to transmit digital temporal difference images wirelessly to a receiver with high rates and reduced power consumption. The sensor can wake up the radio when it detects a specific number of pixels intensity modulation, so that only significant frames are communicated. The prototype chip was implemented using a 2-poly 3-metal AMIS 0.5 μ m CMOS process. Power consumption is 0.9 mW for the sensor and 15 mW for radio transmission to distance of 4 m with rates of 1.3 Mbps and 160 fps.

People rarely put in their papers the things that didn't work, the mistakes they made, and how they found out what went wrong. Such confessions can help others learn how to avoid similar mistakes. Twenty-six confessions were collected to form the bulk of this paper. Themes that arise are errors that result from not understanding the limitations of simulation tools in modeling physical reality, chip verification errors that result from lack of clear communication between designers, and projects that are considered in their own isolated environment of technical challenges rather than the broader context of their environment or application.

Clock-less synchronization and data recovery can be achieved with FSK-OOK modulation and demodulation in non-coherent UWB impulse radio (UWB-IR) system. In this work we report a 30 Mbps non-coherent FSK-OOK UWB-IR transmitter. The chip is fabricated with 0.25 μm Silicon on Sapphire (SOS) process. The chip size is 1 mm by 1 mm with pad. The power consumption with 2.5 V supply is 30 mW. A graphic user interface was developed to control the power and frequency of the transmitter as well as the data rate of the test-bench.

We demonstrate a low power temporal-difference image sensor with wireless communication capability designed specifically for imaging sensor networks. The event-based image sensor features a 64×64 pixel array and can also report standard analog intensity images. An ultra-wide-band (UWB) radio channel allows to transmit digital temporal difference images wirelessly to a receiver with high rates and reduced power consumption. The sensor wakes up when it detects enough scene changes and only communicates meaningful frames. A complete demo platform, for both the wireless sensor (transmitter) and a receiver was developed. Power consumption is 0.9 mW for the sensor and 15 mW for radio transmission to 4 m with rates of 1.3 Mbps and 160 fps.

In this paper we present a low power temporal-difference image sensor with wireless communication capability designed specifically for imaging sensor networks. The event-based image sensor features a 64 × 64 pixel array and can also report standard analog intensity images. An ultra-wideband (UWB) radio channel allows to transmit digital temporal difference images wirelessly to a receiver with high rates and reduced power consumption. The sensor wakes up when it detects enough scene changes and only communicates meaningful frames. Power consumption is 0.9 mW for the sensor and 15 mW for radio transmission to 4 m with rates of 1.3 Mbps and 160 fps.

Long term monitoring of neuronal activity in awake behaving subjects can provide fundamental information about brain dynamics for both neuroscience and neuroengineering applications. Recent advances in VLSI systems has focused on designing wireless neural recording systems which can be mounted on animals and acquire neural signals in real time. These advances provide an unparalleled opportunity to study phenomenon such as neural plasticity in both a basic science setting (learning and memory), and also a clinical setting (injury and recovery). Here we present an integrated VLSI system for wireless telemetry of the entire spectrum of neural signals, spikes, local field potentials, electrocorticograms (ECoG) and electroencephalograms (EEG). The system integrates two custom designed VLSI chips, a 16 channel neural interface which can amplify, filter and digitize neural data up to 16 kS/sec and 12 bits and a low power ultra-wideband (UWB) chip which can transmit data at rates up to 14 Mbps. The entire system which includes these VLSI circuits, a digital interface board and a battery, is small, 1.2 × 1.2 × 2.6 in3, and light weight, 33 grams, so it can be chronically mounted on a rat. The system consumes 32.8 mA at 3.3V and can record for 6 hours running from the 200 mAh coin cell battery. Bench-top and in vitro characterization of the system showed comparable performance to the wired recording system.

In this paper, we report on the noise analysis of low current measurement systems for biomedical applications. We analyzed resistive feedback, capacitive feedback and current conveyor circuits for low current measurement systems. Detailed noise analysis are presented and matched with measurement data using a 0.5-μm fabrication process. Based on the theoretical analysis and the measurements, the capacitive feedback system provides better noise performance for the measurement of low current. The capacitive feedback is capable of measuring 700fA RMS at 10KHz sampling rate, whereas the resistive feedback provides 4pA and the current conveyor provides 600pA. This paper provides design guidelines to maximize the measurement performance of low current for biomedical instrumentation.

We present a 4-channel bio-potential recording system using asynchronous delta analog-to-digital converter. The system is designed to reduce the amount of data in neuro-physiological sensors. The circuit includes low-power low-noise amplifiers with asynchronous delta modulators. The analog front end offers a gain of 53 dB within bandwidth of 200 Hz-20 kHz. In this asynchronous data converter, the minimum input-referred delta resolution is 4μV. The input-referred rms noise is 2μV. T h e system was fabricated with AMI 0.5μm CMOS technology. The chip size is 1.5mm by 1.5mm. The power consumption of the 4-channel system with 3.3V supply is 118.8μW in static state and 501.6μW with 240kbps data conversion rate. A graphic user interface was developed to monitor the transmitted signal in real time.

We present a low-power pulse-based amplifier and data conversion circuit for recording bio-potentials. The circuit is designed for data reduction in neurophysiological sensor and communication systems. A low-power low-noise AC amplifier with an asynchronous delta A/D converter is implemented. The asynchronous delta modulation has the advantage of data reduction, clock-less and no quantization noise. The amplifier gain is 53 dB (bandwidth of 200 Hz-20 kHz) with DC variation rejection. The input-referred rms noise is 2 muV. The delta amplitude in the A/D converter is 0.1 V at 3.3 V voltage supply. The system is fabricated with AMI 0.5 mum CMOS technology. The chip size is 1191 mum by 713 mum. The power consumption with 3.3 V supply is 75.9 muW in static state and 194.7 muW with 60 kbps data conversion rate. A graphic user interface was developed to monitor the transmitted signal in real time.

We present a low-power high-speed ultra-wideband (UWB) pulse radio transmission test platform. The transmitter circuit is fabricated on the Peregrine semiconductors 0.5 micron silicon-on-sapphire (SOS) CMOS process and packaged in a DIP16 package. 12.5 Mbps data rate of wireless transmission is achieved. The power consumption of the transmitter is 10 mW when the pulse rate is 90 MHz. The core circuit size is 70 mum by 130 mum. The transmission distance is in excess of 4 m. The circuit is a transformative technology candidate for high-data rate and low power wireless biomedical applications.

A low-power tunable transmitter for ultra-wide band (UWB) radio was designed and fabricated. The design is based on a ring oscillator VCO, to produce short pulses. Both the pulse duration and frequency is controllable by two voltage biases. The transmitter can be used in both pulse-amplitude modulation (PAM) and pulse-position modulation (PPM). The circuit was fabricated on a 0.5mum silicon-on-sapphire CMOS process, and has been experimentally characterized with a transmitter and receiver module. The UWB transmitter produces monocycle pulses of 800 ps duration. The power consumption is 75muW when the pulse frequency is 3 MHz. The core pulse generator occupies 0.0091mm2of silicon area.