Fully Integrated Biopotential Acquisition Analog Front-End IC

Miniaturization for wearable EEG systems: recording hardware and data processing

As more people desire at-home diagnosis and treatment for their health improvement, healthcare devices have become more wearable, comfortable, and easy to use. In that sense, the miniaturization of electroencephalography (EEG) systems is a major challenge for developing daily-life healthcare devices. Recently, because of the intertwined relationship between EEG recording and processing, co-research of EEG recording hardware and data processing has been emphasized for whole-in-one miniaturized EEG systems. This paper introduces miniaturization techniques in analog-front-end hardware and processing algorithms for such EEG systems. To miniaturize EEG recording hardware, various types of compact electrodes and mm-sized integrated circuits (IC) techniques including artifact rejection are studied to record accurate EEG signals in a much smaller manner. Active electrode and in-ear EEG technologies are also researched to make small-form-factor EEG measurement structures. Furthermore, miniaturization techniques for EEG processing are discussed including channel selection techniques that reduce the number of required electrode channel and hardware implementation of processing algorithms that simplify the EEG processing stage.

Biopotential Signal Monitoring Systems in Rehabilitation: A Review

Monitoring physical activity in medical and clinical rehabilitation, in sports environments or as a wellness indicator is helpful to measure, analyze and evaluate physiological parameters involving the correct subject’s movements. Thanks to integrated circuit (IC) technologies, wearable sensors and portable devices have expanded rapidly in monitoring physical activities in sports and tele-rehabilitation. Therefore, sensors and signal acquisition devices became essential in the tele-rehabilitation path to obtain accurate and reliable information by analyzing the acquired physiological signals. In this context, this paper provides a state-of-the-art review of the recent advances in electroencephalogram (EEG), electrocardiogram (ECG) and electromyogram (EMG) signal monitoring systems and sensors that are relevant to the field of tele-rehabilitation and health monitoring. Mostly, we focused our contribution in EMG signals to highlight its importance in rehabilitation context applications. This review focuses on analyzing the implementation of sensors and biomedical applications both in literature than in commerce. Moreover, a final review discussion about the analyzed solutions is also reported at the end of this paper to highlight the advantages of physiological monitoring systems in rehabilitation and individuate future advancements in this direction. The main contributions of this paper are (i) the presentation of interesting works in the biomedical area, mainly focusing on sensors and systems for physical rehabilitation and health monitoring between 2016 and up-to-date, and (ii) the indication of the main types of commercial sensors currently being used for biomedical applications.

Motion Artifact Removal Techniques for Wearable EEG and PPG Sensor Systems

Removal of motion artifacts is a critical challenge, especially in wearable electroencephalography (EEG) and photoplethysmography (PPG) devices that are exposed to daily movements. Recently, the significance of motion artifact removal techniques has increased since EEG-based brain–computer interfaces (BCI) and daily healthcare usage of wearable PPG devices were spotlighted. In this article, the development on EEG and PPG sensor systems is introduced. Then, understanding of motion artifact and its reduction methods implemented by hardware and/or software fashions are reviewed. Various electrode types, analog readout circuits, and signal processing techniques are studied for EEG motion artifact removal. In addition, recent in-ear EEG techniques with motion artifact reduction are also introduced. Furthermore, techniques compensating independent/dependent motion artifacts are presented for PPG.

An 8.72 µW Low-Noise and Wide Bandwidth FEE Design for High-Throughput Pixel-Strip (PS) Sensors

The front-end electronics (FEE) of the Compact Muon Solenoid (CMS) is needed very low power consumption and higher readout bandwidth to match the low power requirement of its Short Strip application-specific integrated circuits (ASIC) (SSA) and to handle a large number of pileup events in the High-Luminosity Large Hadron Collider (LHC). A low-noise, wide bandwidth, and ultra-low power FEE for the pixel-strip sensor of the CMS has been designed and simulated in a 0.35 µm Complementary Metal Oxide Semiconductor (CMOS) process. The design comprises a Charge Sensitive Amplifier (CSA) and a fast Capacitor-Resistor-Resistor-Capacitor (CR-RC) pulse shaper (PS). A compact structure of the CSA circuit has been analyzed and designed for high throughput purposes. Analytical calculations were performed to achieve at least 998 MHz gain bandwidth, and then overcome pileup issue in the High-Luminosity LHC. The spice simulations prove that the circuit can achieve 88 dB dc-gain while exhibiting up to 1 GHz gain-bandwidth product (GBP). The stability of the design was guaranteed with an 82-degree phase margin while 214 ns optimal shaping time was extracted for low-power purposes. The robustness of the design against radiations was performed and the amplitude resolution of the proposed front-end was controlled at 1.87% FWHM (full width half maximum). The circuit has been designed to handle up to 280 fC input charge pulses with 2 pF maximum sensor capacitance. In good agreement with the analytical calculations, simulations outcomes were validated by post-layout simulations results, which provided a baseline gain of 546.56 mV/MeV and 920.66 mV/MeV, respectively, for the CSA and the shaping module while the ENC (Equivalent Noise Charge) of the device was controlled at 37.6 e⁻ at 0 pF with a noise slope of 16.32 e⁻/pF. Moreover, the proposed circuit dissipates very low power which is only 8.72 µW from a 3.3 V supply and the compact layout occupied just 0.0205 mm² die area.

High-performance fully differential photodiode amplifier for miniature fiber-optic gyroscopes

Electrical cross coupling is regarded as a major obstacle to achieving high-performance miniature fiber-optic gyroscopes (FOGs), because it can cause dead bands, which are critical errors in FOGs. Using a differential photodiode amplifier has proven to be effective in rejecting coupled interference. However, the conventional three-op-amp instrumentation amplifier cannot provide a miniature FOG's bandwidth requirements, because of the large photodiode capacitance and parasitic capacitance. We present a high-performance, fully differential photodiode amplifier, where the bandwidth limitations are removed by applying a reverse bias to the photodiode and replacing the feedback resistor with a modified tee-network and a DC cancellation loop. For an experimental FOG with a 300 m fiber coil, we demonstrate a fully differential photodiode amplifier with 880 kΩ gain and 3.5 MHz bandwidth. In the FOG performance test, it not only reduces the angular random walk and bias drift, but also eliminates the approximately 1°/h dead band observed in the same FOG using a PINFET receiver, demonstrating its effectiveness in suppressing coupled interference.

Biosignal integrated circuit with simultaneous acquisition of ECG and PPG for wearable healthcare applications

BACKGROUND

Wearable healthcare systems require measurements from electrocardiograms (ECGs) and photoplethysmograms (PPGs), and the blood pressure of the user. The pulse transit time (PTT) can be calculated by measuring the ECG and PPG simultaneously. Continuous-time blood pressure without using an air cuff can be estimated by using the PTT.

OBJECTIVE

This paper presents a biosignal acquisition integrated circuit (IC) that can simultaneously measure the ECG and PPG for wearable healthcare applications.

METHODS

Included in this biosignal acquisition circuit are a voltage mode instrumentation amplifier (IA) for ECG acquisition and a current mode transimpedance amplifier for PPG acquisition. The analog outputs from the ECG and PPG channels are muxed and converted to digital signals using 12-bit successive approximation register (SAR) analog-to-digital converter (ADC).

RESULTS

The proposed IC is fabricated by using a standard 0.18 μm CMOS process with an active area of 14.44 mm2. The total current consumption for the multichannel IC is 327 μA with a 3.3 V supply. The measured input referred noise of ECG readout channel is 1.3 μVRMS with a bandwidth of 0.5 Hz to 100 Hz. And the measured input referred current noise of the PPG readout channel is 0.122 nA/√Hz with a bandwidth of 0.5 Hz to 100 Hz.

CONCLUSIONS

The proposed IC, which is implemented using various circuit techniques, can measure ECG and PPG signals simultaneously to calculate the PTT for wearable healthcare applications.

A Wireless ExG Interface for Patch-Type ECG Holter and EMG-Controlled Robot Hand

This paper presents a wearable electrophysiological interface with enhanced immunity to motion artifacts. Anti-artifact schemes, including a patch-type modular structure and real-time automatic level adjustment, are proposed and verified in two wireless system prototypes of a patch-type electrocardiogram (ECG) module and an electromyogram (EMG)-based robot-hand controller. Their common ExG readout integrated circuit (ROIC), which is reconfigurable for multiple physiological interfaces, is designed and fabricated in a 0.18 μm CMOS process. Moreover, analog pre-processing structures based on envelope detection are integrated with one another to mitigate signal processing burdens in the digital domain effectively.

A Reconfigurable Readout Integrated Circuit for Heterogeneous Display-Based Multi-Sensor Systems

This paper presents a reconfigurable multi-sensor interface and its readout integrated circuit (ROIC) for display-based multi-sensor systems, which builds up multi-sensor functions by utilizing touch screen panels. In addition to inherent touch detection, physiological and environmental sensor interfaces are incorporated. The reconfigurable feature is effectively implemented by proposing two basis readout topologies of amplifier-based and oscillator-based circuits. For noise-immune design against various noises from inherent human-touch operations, an alternate-sampling error-correction scheme is proposed and integrated inside the ROIC, achieving a 12-bit resolution of successive approximation register (SAR) of analog-to-digital conversion without additional calibrations. A ROIC prototype that includes the whole proposed functions and data converters was fabricated in a 0.18 μm complementary metal oxide semiconductor (CMOS) process, and its feasibility was experimentally verified to support multiple heterogeneous sensing functions of touch, electrocardiogram, body impedance, and environmental sensors.