Design of a Programmable Passive SoC for Biomedical Applications Using RFID ISO 15693/NFC5 Interface

Low power, low cost inductively powered passive biotelemetry system involving fully customized RFID/NFC interface base SoC has gained popularity in the last decades. However, most of the SoCs developed are application specific and lacks either on-chip computational or sensor readout capability. In this paper, we present design details of a programmable passive SoC in compliance with ISO 15693/NFC5 standard for biomedical applications. The integrated system consists of a 32-bit microcontroller, a sensor readout circuit, a 12-bit SAR type ADC, 16 kB RAM, 16 kB ROM and other digital peripherals. The design is implemented in a 0.18 μ m CMOS technology and used a die area of 1.52 mm × 3.24 mm. The simulated maximum power consumption of the analog block is 592 μ W. The number of external components required by the SoC is limited to an external memory device, sensors, antenna and some passive components. The external memory device contains the application specific firmware. Based on the application, the firmware can be modified accordingly. The SoC design is suitable for medical implants to measure physiological parameters like temperature, pressure or ECG. As an application example, the authors have proposed a bioimplant to measure arterial blood pressure for patients suffering from Peripheral Artery Disease (PAD)

A low-power reconfigurable ADC for biomedical sensor interfaces

This paper presents a 12-bit low-voltage low-power reconfigurable Analog-to-Digital Converter (ADC). The design employs Switched Capacitor (SC) techniques and implements a Successive Approximation (SA) algorithm. The ADC can be tuned to handle a large variety of biopotential signals, with digitally selectable resolution and input signal amplitude. It achieves 10.4-bit of effective resolution sampling at 56kS/s, with a power consumption below 3μW from a 1V voltage supply.Ministerio de Educación y Ciencia TEC2006-03022Junta de Andalucía TIC-0281

A self-calibration circuit for a neural spike recording channel

This paper presents a self-calibration circuit for a neural spike recording channel. The proposed design tunes the bandwidth of the signal acquisition Band-Pass Filter (BPF), which suffers from process variations corners. It also performs the adjustment of the Programmable Gain Amplifier (PGA) gain to maximize the input voltage range of the analog-to-digital conversion. The circuit, which consists on a frequency-controlled signal generator and a digital processor, operates in foreground, is completely autonomous and integrable in an estimated area of 0.026mm 2 , with a power consumption around 450nW. The calibration procedure takes less than 250ms to select the configuration whose performance is closest to the required one.Ministerio de Ciencia e Innovación TEC2009-08447Junta de Andalucía TIC-0281

An ECG-on-Chip with 535-nW/Channel Integrated Lossless Data Compressor for Wireless Sensors

This paper presents a low-power ECG recording system-on-chip (SoC) with on-chip low-complexity lossless ECG compression for data reduction in wireless/ambulatory ECG sensor devices. The chip uses a linear slope predictor for data compression, and incorporates a novel low-complexity dynamic coding-packaging scheme to frame the prediction error into fixed-length 16-bit format. The proposed technique achieves an average compression ratio of 2.25x on MIT/BIH ECG database. Implemented in a standard 0.35 um process, the compressor uses 0.565K gates/channel occupying 0.4 mm2 for four channels, and consumes 535 nW/channel at 2.4 V for ECG sampled at 512 Hz. Small size and ultra-low power consumption makes the proposed technique suitable for wearable ECG sensor applications

A wireless ECG plaster for real-time cardiac health monitoring in body sensor networks

10.1109/BioCAS.2011.61077632011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011205-20

Low Power Circuits for Smart Flexible ECG Sensors

Cardiovascular diseases (CVDs) are the world leading cause of death. In-home heart condition monitoring effectively reduced the CVD patient hospitalization rate. Flexible electrocardiogram (ECG) sensor provides an affordable, convenient and comfortable in-home monitoring solution. The three critical building blocks of the ECG sensor i.e., analog frontend (AFE), QRS detector, and cardiac arrhythmia classifier (CAC), are studied in this research. A fully differential difference amplifier (FDDA) based AFE that employs DC-coupled input stage increases the input impedance and improves CMRR. A parasitic capacitor reuse technique is proposed to improve the noise/area efficiency and CMRR. An on-body DC bias scheme is introduced to deal with the input DC offset. Implemented in 0.35m CMOS process with an area of 0.405mm2, the proposed AFE consumes 0.9W at 1.8V and shows excellent noise effective factor of 2.55, and CMRR of 76dB. Experiment shows the proposed AFE not only picks up clean ECG signal with electrodes placed as close as 2cm under both resting and walking conditions, but also obtains the distinct -wave after eye blink from EEG recording. A personalized QRS detection algorithm is proposed to achieve an average positive prediction rate of 99.39% and sensitivity rate of 99.21%. The user-specific template avoids the complicate models and parameters used in existing algorithms while covers most situations for practical applications. The detection is based on the comparison of the correlation coefficient of the user-specific template with the ECG segment under detection. The proposed one-target clustering reduced the required loops. A continuous-in-time discrete-in-amplitude (CTDA) artificial neural network (ANN) based CAC is proposed for the smart ECG sensor. The proposed CAC achieves over 98% classification accuracy for 4 types of beats defined by AAMI (Association for the Advancement of Medical Instrumentation). The CTDA scheme significantly reduces the input sample numbers and simplifies the sample representation to one bit. Thus, the number of arithmetic operations and the ANN structure are greatly simplified. The proposed CAC is verified by FPGA and implemented in 0.18m CMOS process. Simulation results show it can operate at clock frequencies from 10KHz to 50MHz. Average power for the patient with 75bpm heart rate is 13.34W

Power and area efficient MOSFET-C filter for very low frequency applications

New circuit design techniques for implementing very high-valued resistors are presented, significantly improving power and area efficiency of analog front-end signal processing in ultra-low power biomedical systems. Ranging in value from few hundreds of \hbox{M}\Upomega to few hundreds of \hbox{G}\Upomega , the proposed floating resistors occupy a very small area, and produce accurately tunable characteristics. Using this approach, a low-pass MOSFET-C filter with tunable cutoff frequency (f C =20Hz-184kHz) has been implemented in a conventional 0.18μm CMOS technology. Occupying 0.045mm2/pole, the power consumption of this filter is 540 pW/Hz/pole with a measured IMFDR of 70 d

Relaxing the maximum dc input amplitude vs. consumption trade-off in differential-input band-pass biquad filters.

This paper shows that an important part of the power consumption of a biquad band‐pass filter is associated with the feedback loop that fixes the high‐pass frequency and blocks the direct current (dc) input signals. The dc input amplitude that can be blocked is related to the maximum output current that one of the transconductors can provide, hence impacting on the required consumption through this effect. Then, a technique that efficiently blocks the dc input signal and fixes the high‐pass frequency is introduced and analyzed in depth. Moreover, an architecture for ultra‐low‐power differential‐input biquads is fully presented. The proposed architecture enables lowering the power consumption or blocking higher levels of dc input without jeopardizing the power consumption. Results show that the proposed architecture, compared with a traditional one, presents a 30% reduction in power consumption and more than doubles the dc input that can be blocked