A low noise amplifier suitable for biomedical recording analog front-end in 65nm CMOS technology

This paper presents a fully integrated Front-end, low noise amplifier, dedicated to the processing of various types of bio-medical signals, such as Electrocardiogram (ECG), Electroencephalography (EEG), Axon Action Potential (AAP). A novel noise reduction technique, for an operational transconductance amplifier (OTA), has been proposed. This adds a current steering branch parallel to the differential pair, with a view to reducing the noise contribution by the cascode current sources. Hence, this reduces the overall input referred noise of the Low Noise Amplifier (LNA), without adding any additional power. The proposed technique implemented in 65nm CMOS technology achieves 30dB closed loop voltage gain, 0.05Hz lower cut-off frequency and 100MHz 3-dB bandwidth. It operates at 1.2V power supply and draws 1µA static current. The prototype described in this paper occupies 3300µm2silicon area

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

High performance circuit techniques for neural front-end design in 65nm CMOS

Integrated low noise neural amplifiers become recently practical in CMOS technologies. In this paper, a low noise OTA technique has been proposed while keeping the power consumption constant. A capacitive feedback, ac coupled 46dB amplifier with high pass cutoff frequency close to the 90Hz has been achieved. The proposed amplifier has been implemented in 65nm CMOS technology; at room temperature circuit consumes 323uA current from 1.2V power supply. The circuit occupies 2627um 2 silicon area

Receiver Front-Ends in CMOS with Ultra-Low Power Consumption

Historically, research on radio communication has focused on improving range and data rate. In the last decade, however, there has been an increasing demand for low power and low cost radios that can provide connectivity with small devices around us. They should be able to offer basic connectivity with a power consumption low enough to function extended periods of time on a single battery charge, or even energy scavenged from the surroundings. This work is focused on the design of ultra-low power receiver front-ends intended for a receiver operating in the 2.4GHz ISM band, having an active power consumption of 1mW and chip area of 1mm². Low power consumption and small size make it hard to achieve good sensitivity and tolerance to interference. This thesis starts with an introduction to the overall receiver specifications, low power radio and radio standards, front-end and LO generation architectures and building blocks, followed by the four included papers. Paper I demonstrates an inductorless front-end operating at 915MHz, including a frequency divider for quadrature LO generation. An LO generator operating at 2.4GHz is shown in Paper II, enabling a front-end operating above 2GHz. Papers III and IV contain circuits with combined front-end and LO generator operating at or above the full 2.45GHz target frequency. They use VCO and frequency divider topologies that offer efficient operation and low quadrature error. An efficient passive-mixer design with improved suppression of interference, enables an LNA-less design in Paper IV capable of operating without a SAW-filter

A self-powered single-chip wireless sensor platform

Internet of things” require a large array of low-cost sensor nodes, wireless connectivity, low power operation and system intelligence. On the other hand, wireless biomedical implants demand additional specifications including small form factor, a choice of wireless operating frequencies within the window for minimum tissue loss and bio-compatibility This thesis describes a low power and low-cost internet of things system suitable for implant applications that is implemented in its entirety on a single standard CMOS chip with an area smaller than 0.5 mm2. The chip includes integrated sensors, ultra-low-power transceivers, and additional interface and digital control electronics while it does not require a battery or complex packaging schemes. It is powered through electromagnetic (EM) radiation using its on-chip miniature antenna that also assists with transmit and receive functions. The chip can operate at a short distance (a few centimeters) from an EM source that also serves as its wireless link. Design methodology, system simulation and optimization and early measurement results are presented

Ultra-low power mixed-signal frontend for wearable EEGs

Electronics circuits are ubiquitous in daily life, aided by advancements in the chip design industry, leading to miniaturised solutions for typical day to day problems. One of the critical healthcare areas helped by this advancement in technology is electroencephalography (EEG). EEG is a non-invasive method of tracking a person's brain waves, and a crucial tool in several healthcare contexts, including epilepsy and sleep disorders. Current ambulatory EEG systems still suffer from limitations that affect their usability. Furthermore, many patients admitted to emergency departments (ED) for a neurological disorder like altered mental status or seizures, would remain undiagnosed hours to days after admission, which leads to an elevated rate of death compared to other conditions. Conducting a thorough EEG monitoring in early-stage could prevent further damage to the brain and avoid high mortality. But lack of portability and ease of access results in a long wait time for the prescribed patients. All real signals are analogue in nature, including brainwaves sensed by EEG systems. For converting the EEG signal into digital for further processing, a truly wearable EEG has to have an analogue mixed-signal front-end (AFE). This research aims to define the specifications for building a custom AFE for the EEG recording and use that to review the suitability of the architectures available in the literature. Another critical task is to provide new architectures that can meet the developed specifications for EEG monitoring and can be used in epilepsy diagnosis, sleep monitoring, drowsiness detection and depression study. The thesis starts with a preview on EEG technology and available methods of brainwaves recording. It further expands to design requirements for the AFE, with a discussion about critical issues that need resolving. Three new continuous-time capacitive feedback chopped amplifier designs are proposed. A novel calibration loop for setting the accurate value for a pseudo-resistor, which is a crucial block in the proposed topology, is also discussed. This pseudoresistor calibration loop achieved the resistor variation of under 8.25%. The thesis also presents a new design of a curvature corrected bandgap, as well as a novel DDA based fourth-order Sallen-Key filter. A modified sensor frontend architecture is then proposed, along with a detailed analysis of its implementation. Measurement results of the AFE are finally presented. The AFE consumed a total power of 3.2A (including ADC, amplifier, filter, and current generation circuitry) with the overall integrated input-referred noise of 0.87V-rms in the frequency band of 0.5-50Hz. Measurement results confirmed that only the proposed AFE achieved all defined specifications for the wearable EEG system with the smallest power consumption than state-of-art architectures that meet few but not all specifications. The AFE also achieved a CMRR of 131.62dB, which is higher than any studied architectures.Open Acces