An ultra-low-power pulse oximeter implemented with an energy-efficient transimpedance amplifier

BASS: Safe Deep Tissue Optical Sensing for Wearable Embedded Systems

In wearable optical sensing applications whose target tissue is not superficial, such as deep tissue oximetry, the task of embedded system design has to strike a balance between two competing factors. On one hand, the sensing task is assisted by increasing the radiated energy into the body, which in turn, improves the signal-to-noise ratio (SNR) of the deep tissue at the sensor. On the other hand, patient safety consideration imposes a constraint on the amount of radiated energy into the body. In this paper, we study the trade-offs between the two factors by exploring the design space of the light source activation pulse. Furthermore, we propose BASS, an algorithm that leverages the activation pulse design space exploration, which further optimizes deep tissue SNR via spectral averaging, while ensuring the radiated energy into the body meets a safe upper bound. The effectiveness of the proposed technique is demonstrated via analytical derivations, simulations, and in vivo measurements in both pregnant sheep models and human subjects.

Reflection-Boosted Wearable Ring-Type Pulse Oximeters for SpO2 Measurement with High Sensitivity and Low Power Consumption

In this study, we demonstrated a Monte Carlo simulation to model a finger structure and to calculate the intensity of photons passing through tissues, in order to determine optimal angular separation between a photodetector (PD) and a light-emitting diode (LED), to detect SpO₂. Furthermore, our model was used to suggest a mirror-coated ring-type pulse oximeter to improve the sensitivity by up to 80% and improve power consumption by up to 65% compared to the mirror-uncoated structure. A ring-type pulse oximeter (RPO) is widely used to detect photoplethysmography (PPG) signals for SpO₂ measurement during sleep and health-status monitoring. Device sensitivity and the power consumption of an RPO, which are key performance indicators, vary greatly with the geometrical arrangement of PD and LED within the inner surface of an RPO. We propose a reflection-boosted design of an RPO to achieve both high sensitivity and low power consumption, and determine an optimal configuration of a PD and LED by performing a 3D Monte Carlo simulation and confirming its agreement with experimental measurement. In order to confirm the reflection-boosted performance in terms of signal-to-noise ratio, R ratio, and perfusion index (PI), RPOs were fabricated with and without a highly reflective coating, and then used for SpO₂ measurement from eight participants. Our simulation allows the numerical calculation of the intensity of photon passing and scattering through finger tissues. The reflection-boosted RPO enables reliable measurement with high sensitivity, resulting in less power consumption for the LED and longer device usage than conventional RPOs without any reflective coating, in order to maintain the same level of SNR and PI. Compared to the non-reflective reference RPO, the reflection-boosted RPO design greatly enhanced both detected light intensity (67% in dc and 322% in ac signals at a wavelength λ₁ = 660 nm, and also 81% and 375% at λ₂ = 940 nm, respectively) and PI (23.3% at λ₁ and 25.5% at λ₂). Thus, the reflection-boosted design not only enhanced measurement reliability but also significantly improved power consumption, i.e., by requiring only 36% and 30% power to drive the LED sources with λ₁ and λ₂, respectively, to produce the device performance of a non-reflective RPO reference. It is expected that our proposed RPO provides long-term monitoring capability with low power consumption and an enhanced PI for SpO₂ measurement.

Modeling Energy Aware Photoplethysmography for Personalized Healthcare Applications

The rise of wearable health monitoring has largely incorporated photoplethysmography (PPG), an optical sensing modality, to determine heart rate and blood oxygen saturation metrics by reflecting light through a user's skin. Due to its optical nature, this sensing method is strongly impacted by the skin type, body mass index (BMI), and general physiological composition of the user. In the context of self-powering, there is a need for these devices to consume ultra-low power, to not be dependent on batteries and regular charging, enabling continuous monitoring. This paper presents a novel PPG sensing model for both a custom, ultra-low power (ULP) AFE and the Texas Instruments (TI) AFE4404 which is used to demonstrate the design tradeoffs between system power and SNR. The models also incorporate a novel human skin reflectance component to analyze the effect of the user's skin phototype and BMI on these tradeoffs with the goal of demonstrating inclusive, accurate ULP PPG sensing. Measured results on both devices from 23 participants are included to emphasize the limited design space for enabling self-powered, continuous monitoring wearables.

State-of-the-Art Light to Digital Converter Circuits Applicable in Non-Invasive Health Monitoring Devices to Combat COVID-19 and Other Respiratory Illnesses: A Review

In the past few years, a tremendous advancement in the outcome of biomedical circuits and systems has been reported. Unfortunately, at the time of the sudden outbreak of COVID-19, the electronic engineering researchers felt dearth on their side to combat the pandemic, as no such immediate cutting-edge solutions were ready to recognize the virus with some standard and smart electronic devices. Likely, in this paper, a detailed comparative and comprehensive study on circuit architectures of the biomedical devices is presented. Mostly, this study relates the industry standard circuit schemes applicable in non-invasive health monitoring to combat respiratory illnesses. The trending circuit architectural schemes casted-off to tapeout non-invasive health-care devices available in the past literature are meticulously and broadly discussed in this study. Further, the comprehensive comparison of the state of art of the device performance in terms of supply voltage, chip area, sensitivity, dynamic range, etc. is also shown in this paper. The inclusive design processes of the health monitoring devices from Lab to Industry is thoroughly discussed for the readers. The authors think, that this critical review summarising all the trending and most cited health-care devices in a single paper will alternately help the industrialists to adapt and modify the circuit architectures of the health monitoring devices more precisely and straightforwardly. Finally, the demand for health monitoring devices particularly responsible to detect respiratory illnesses, measuring blood pressure and heart-rate is growing widely in the market after the the incident of COVID-19 and other respiratory diseases.

Design and Analysis of a Resistive Sensor Interface With Phase Noise-Energy-Resolution Scalability for a Time-Based Resistance-to-Digital Converter

This article presents the design and analysis of a resistive sensor interface with three different designs of phase noise-energy-resolution scalability in time-based resistance-to-digital converters (RDCs), including test chip implementations and measurements, targeted toward either minimizing the energy/conversion step or maximizing bit-resolution. The implemented RDCs consist of a three-stage differential ring oscillator, which is current starved using the resistive sensor, a differential-to-single-ended amplifier, and digital modules and serial interface. The first RDC design (baseline) included the basic structure of time-based RDC and targeted low-energy/conversion step. The second RDC design (goal: higher-resolution) aimed to improve the rms jitter/phase noise of the oscillator with help of speed-up latches, to achieve high bit-resolution as compared to the first RDC design. The third RDC design (goal: process portability) reduced the power consumption by scaling the technology with the improved phase-noise design, achieving 1-bit better resolution as that of the second RDC design. Using time-based implementation, the RDCs exhibit energy-resolution scalability and consume a measured power of 861 nW with 18-bit resolution in design 1 in TSMC 0.35 μm technology (with 10 ms read-time, with one readout every second). Measurements of designs 2 and 3 demonstrate power consumption of 19.2 μW with 20-bit resolution using TSMC 0.35μm and 17.6 μW with 20-bit resolution using TSMC 0.18μm, respectively (both with 10 ms read-time, repeated every second). With 30 ms read-time, design 3 achieves 21-bit resolution, which is the highest resolution reported for a time-based ADC. The 0.35-μm time-based RDC is the lowest-power time-based ADC reported, while the 0.18-μm time-based RDC with speed-up latch offers the highest resolution. The active chip-area for all three designs is less than 1.1 mm2.

A Low-Noise Analog Front End with Interstage Systematically Ambient Interference Cancellation for Pulse Oximeter

This paper presents a low-noise analog front end (AFE) with interstage systematically ambient interference cancellation for a pulse oximeter, which is suitable for clinical oxygen saturation (SPO2) detection with a low perfusion index. The fully differential implementation is adopted to have a better rejection performance of common mode interference and noise. Firstly, the proposed interstage systematically ambient interference cancellation is placed in the two gain stages to decrease low frequency noise in the bandwidth of interest (0.1–20 Hz), so that the larger signal-to-noise ratio (SNR) can be achieved to increase the detection accuracy of this system. Secondly, due to the additional gain stage compared with traditional implementation, the current-reuse OTA is employed to have better noise and power efficiency. Thirdly, the auto zero technique is utilized in the LED Driver to decrease the offset voltage and acquire a larger dynamic range (DR) in the low frequency bandwidth of interest. This PPG AFE chip is designed and fabricated in a 180 nm standard CMOS process. The receiver (RX) of this AFE consumes 220 μW from a 1.8 V supply, and the power consumption of the transmitter (TX) is 60 μW from a 3 V supply. The measurement results show that the input-referred noise current of 2.3 pA/sqrt(Hz) is achieved in RX and 110 dB peak DR is obtained in TX.

A 134 DB Dynamic Range Noise Shaping Slope Light-to-Digital Converter for Wearable Chest PPG Applications

This paper presents a low power, high dynamic range (DR), light-to-digital converter (LDC) for wearable chest photoplethysmogram (PPG) applications. The proposed LDC utilizes a novel 2^nd-order noise-shaping slope architecture, directly converting the photocurrent to a digital code. This LDC applies a high-resolution dual-slope quantizer for data conversion. An auxiliary noise shaping loop is used to shape the residual quantization noise. Moreover, a DC compensation loop is implemented to cancel the PPG signal's DC component, thus further boosting the DR. The prototype is fabricated with 0.18 μm standard CMOS and characterized experimentally. The LDC consumes 28 μW per readout channel while achieving a maximum 134 dB DR. The LDC is also validated with on-body chest PPG measurement.

In Vivo Evaluation of a Subcutaneously Injectable Implant with a Low-Power Photoplethysmography ASIC for Animal Monitoring

Photoplethysmography is an extensively-used, portable, and noninvasive technique for measuring vital parameters such as heart rate, respiration rate, and blood pressure. The deployment of this technology in veterinary medicine has been hindered by the challenges in effective transmission of light presented by the thick layer of skin and fur of the animal. We propose an injectable capsule system to circumvent these limitations by accessing the subcutaneous tissue to enable reliable signal acquisition even with lower light brightness. In addition to the reduction of power usage, the injection of the capsule offers a less invasive alternative to surgical implantation. Our current prototype combines two application-specific integrated circuits (ASICs) with a microcontroller and interfaces with a commercial light emitting diode (LED) and photodetector pair. These ASICs implement a signal-conditioning analog front end circuit and a frequency-shift keying (FSK) transmitter respectively. The small footprint of the ASICs is the key in the integration of the complete system inside a 40-mm long glass tube with an inner diameter of 4 mm, which enables its injection using a custom syringe similar to the ones used with microchip implants for animal identification. The recorded data is transferred wirelessly to a computer for post-processing by means of the integrated FSK transmitter and a software-defined radio. Our optimized LED duty cycle of 0.4% at a sampling rate of 200 Hz minimizes the contribution of the LED driver (only 0.8 mW including the front-end circuitry) to the total power consumption of the system. This will allow longer recording periods between the charging cycles of the batteries, which is critical given the very limited space inside the capsule. In this work, we demonstrate the wireless operation of the injectable system with a human subject holding the sensor between the fingers and the in vivo functionality of the subcutaneous sensing on a pilot study performed on anesthetized rat subjects.

A 280 μW, 108 dB DR PPG-Readout IC With Reconfigurable, 2nd-Order, Incremental ΔΣM Front-End for Direct Light-to-Digital Conversion

This paper reports on a low-power readout IC (ROIC) for high-fidelity recording of the photoplethysmogram (PPG) signal. The system comprises a highly reconfigurable, continuous-time, second-order, incremental delta-sigma modulator (I-ΔΣM) as a light-to-digital converter (LDC), a 2-channel 10b light-emitting diode (LED) driver, and an integrated digital signal processing (DSP) unit. The LDC operation in intermittent conversion phases coupled with digital assistance by the DSP unit allow signal-aware, on-the-fly cancellation of the dc and ambient light-induced components of the photodiode current for more efficient use of the full-scale input range for recording of the small-amplitude, ac, PPG signal. Fabricated in TSMC 0.18 μm 1P/6M CMOS, the PPG ROIC exhibits a high dynamic range of 108.2 dB and dissipates on average 15.7 μW from 1.5 V in the LDC and 264 μW from 2.5 V in one LED (and its driver), while operating at a pulse repetition frequency of 250 Hz and 3.2% duty cycling. The overall functionality of the ROIC is also demonstrated by high-fidelity recording of the PPG signal from a human subject fingertip in the presence of both natural light and indoor light sources of 60 Hz.

Domiciliary Hospitalization through Wearable Biomonitoring Patches: Recent Advances, Technical Challenges, and the Relation to Covid-19

This article reviews recent advances and existing challenges for the application of wearable bioelectronics for patient monitoring and domiciliary hospitalization. More specifically, we focus on technical challenges and solutions for the implementation of wearable and conformal bioelectronics for long-term patient biomonitoring and discuss their application on the Internet of medical things (IoMT). We first discuss the general architecture of IoMT systems for domiciliary hospitalization and the three layers of the system, including the sensing, communication, and application layers. In regard to the sensing layer, we focus on current trends, recent advances, and challenges in the implementation of stretchable patches. This includes fabrication strategies and solutions for energy storage and energy harvesting, such as printed batteries and supercapacitors. As a case study, we discuss the application of IoMT for domiciliary hospitalization of COVID 19 patients. This can be used as a strategy to reduce the pressure on the healthcare system, as it allows continuous patient monitoring and reduced physical presence in the hospital, and at the same time enables the collection of large data for posterior analysis. Finally, based on the previous works in the field, we recommend a conceptual IoMT design for wearable monitoring of COVID 19 patients.

Respiratory Monitoring: Current State of the Art and Future Roads

In this article, we present current methodologies, available technologies, and demands for monitoring various respiratory parameters. We discuss the importance of noninvasive techniques for remote and continuous monitoring and challenges involved in the current "smart and connected health" era. We conducted an extensive literature review on the medical significance of monitoring respiratory vital parameters, along with the current methods and solutions with their respective advantages and disadvantages. We discuss the challenges of developing a noninvasive, wearable, wireless system that continuously monitors respiration parameters and opportunities in the field and then determines the requirements of a state-of-the-art system. Noninvasive techniques provide a significant amount of medical information for a continuous patient monitoring system. Contact methods offer more advantages than non-contact methods; however, reducing the size and power of contact methods is critical for enabling a wearable, wireless medical monitoring system. Continuous and accurate remote monitoring, along with other physiological data, can help caregivers improve the quality of care and allow patients greater freedom outside the hospital. Such monitoring systems could lead to highly tailored treatment plans, shorten patient stays at medical facilities, and reduce the cost of treatment.

A Noise-Reduced Light-to-Frequency Converter for Sub-0.1% Perfusion Index Blood SpO[Formula: see text] Sensing

To improve the SpO ₂ sensing system performance for hypoperfusion (low perfusion index) applications, this paper proposes a low-noise light-to-frequency converter scheme from two aspects. First, a low-noise photocurrent buffer is proposed by reducing the amplifier noise floor with a transconductance-boost ( g_m-boost) circuit structure. Second, a digital processing unit of pulse-frequency-duty-cycle modulation is proposed to minimize the quantization noise in the following timer by limiting the maximum output frequency. The proposed light-to-frequency sensor chip is designed and fabricated with a 0.35- μm CMOS process. The overall chip area is 1 × 0.9 mm ² and the typical total current consumption is about 1.8 mA from a 3.3-V power supply at room temperature. The measurement results prove the proposed functionality of output pulse duty cycle modulation, while the SNR of a typical 10-kHz output frequency is 59 dB with about 9-dB improvement when compared with the previous design. Among them, 2-3 dB SNR improvement stems from the gm-boosting and the rest comes from the layout design. In-system experimental results show that the minimum measurable PI using the proposed blood SpO ₂ sensor could be as low as 0.06% with 2-percentage-point error of SpO ₂. The proposed chip is suitable for portable low-power high-performance blood oximeter devices especially for hypoperfusion applications.

A 119dB Dynamic Range Charge Counting Light-to-Digital Converter For Wearable PPG/NIRS Monitoring Applications

This paper presents a low power, high dynamic range (DR), reconfigurable light-to-digital converter (LDC) for photoplethysmogram (PPG), and near-infrared spectroscopy (NIRS) sensor readouts. The proposed LDC utilizes a current integration and a charge counting operation to directly convert the photocurrent to a digital code, reducing the noise contributors in the system. This LDC consists of a latched comparator, a low-noise current reference, a counter, and a multi-function integrator, which is used in both signal amplification and charge counting based data quantization. Furthermore, a current DAC is used to further increase the DR by canceling the baseline current. The LDC together with LED drivers and auxiliary digital circuitry are implemented in a standard 0.18 μm CMOS process and characterized experimentally. The LDC and LED drivers consume a total power of 196 μW while achieving a maximum 119 dB DR. The charge counting clock, and the pulse repetition frequency of the LED driver can be reconfigured, providing a wide range of power-resolution trade-off. At a minimum power consumption of 87 μW, the LDC still achieves 95 dB DR. The LDC is also validated with on-body PPG and NIRS measurement by using a photodiode (PD) and a silicon photomultiplier (SIPM), respectively.

3D Printing Silicone Elastomer for Patient-Specific Wearable Pulse Oximeter

Commercial pulse oximeters are used clinically to measure heart rate and blood oxygen saturation and traditionally made from rigid materials. However, these devices are unsuitable for continuous monitoring due to poor fit and mechanical mismatch. Soft materials that match the elastic properties of biological tissue provide improved comfort and signal-to-noise but typically require molding to manufacture, limiting the speed and ease of customizing for patient-specific anatomy. Here, freeform reversible embedding (FRE) 3D printing is used to create polydimethylsiloxane (PDMS) elastomer cuffs for use on the hand and foot. FRE enables printing liquid PDMS prepolymer in 3D geometries within a sacrificial hydrogel bath that provides support during cure. This serves as proof-of-concept for fabricating patient-specific pulse oximeters with pressure sensing, termed P³ -wearable. A sizing analysis establishes dimensional accuracy of FRE-printed PDMS compared to anatomical computer-aided design models. The P³ -wearable successfully outputs photoplethysmography (PPG) and pressure amplitude signals wirelessly to a tablet in real time and the PPG is used to calculate heart rate, blood oxygen content, and activity state. The results establish that FRE printing of PDMS can be used to fabricate patient-specific wearable devices and measure heart rate and blood oxygenation on par with commercial devices.

A Real-Time Vital-Sign Monitoring in the Physical Domain on a Mixed-Signal Reconfigurable Platform

This work presents a mixed-signal physical-compu-tation-electronics for monitoring three vital signs; namely heart rate, blood pressure, and blood oxygen saturation; from electrocardiography, arterial blood pressure, and photoplethysmography signals in real-time. The computational circuits are implemented on a reconfigurable and programmable signal-processing platform, namely field-programmable analog array (FPAA). The design leverages the core enabling technology of FPAA, namely floating-gate CMOS devices, and an on-chip low-power microcontroller to achieve energy-efficiency while not compromising accuracy. The custom physical-computation-electronics operating in CMOS subthreshold region, performs low-level (i.e., physiologically-relevant feature extraction) and high-level (i.e., detecting arrhythmia) signal processing in an energy-efficient manner. The on-chip microcontroller is used (1) in the programming mode for controlling the charge storage at the analog-memory elements to introduce patient-dependency into the system and (2) in the run mode to quantify the vital signs. The system has been validated against digital computation results from MATLAB using datasets collected from three healthy subjects and datasets from the MIT/BIH open source database. Based on all recordings in the MIT/BIH database, ECG R-peak detection sensitivity is 94.2%. The processor detects arrhythmia in three MIT/BIH recordings with an average sensitivity of 96.2%. The cardiac processor achieves an average percentage mean error bounded by 3.75%, 6.27%, and 7.3% for R-R duration, systolic blood pressure, and oxygen saturation level calculations; respectively. The power consumption of the ECG, blood-pressure and photo-plethysmography processing circuitry are 126 nW, 251 nW and 1.44 μW respectively in a 350 nm process. Overall, the cardiac processor consumes 1.82 μW.

Kinetic Energy Harvesting for Wearable Medical Sensors

The process of collecting low-level kinetic energy, which is present in all moving systems, by using energy harvesting principles, is of particular interest in wearable technology, especially in ultra-low power devices for medical applications. In fact, the replacement of batteries with innovative piezoelectric energy harvesting devices can result in mass and size reduction, favoring the miniaturization of wearable devices, as well as drastically increasing their autonomy. The aim of this work is to assess the power requirements of wearable sensors for medical applications, and address the intrinsic problem of piezoelectric kinetic energy harvesting devices that can be used to power them; namely, the narrow area of optimal operation around the eigenfrequencies of a specific device. This is achieved by using complex numerical models comprising modal, harmonic and transient analyses. In order to overcome the random nature of excitations generated by human motion, novel excitation modalities are investigated with the goal of increasing the specific power outputs. A solution embracing an optimized harvester geometry and relying on an excitation mechanism suitable for wearable medical sensors is hence proposed. The electrical circuitry required for efficient energy management is considered as well.

Nano-scale transistors for interfacing with brain: design criteria, progress and prospect

According to the World Health Organization, one quarter of the world's population suffers from various neurological disorders ranging from depression to Alzheimer's disease. Thus, understanding the operation mechanism of the brain enables us to help those who are suffering from these diseases. In addition, recent clinical medicine employs electronic brain implants, despite the fact of being invasive, to treat disorders ranging from severe coronary conditions to traumatic injuries. As a result, the deaf could hear, the blind could see, and the paralyzed could control robotic arms and legs. Due to the requirement of high data management capability with a power consumption as low as possible, designing nanoscale transistors as essential I/O electronics is a complex task. Herein, we review the essential design criteria for such nanoscale transistors, progress and prospect for implantable brain-machine-interface electronics. This article also discusses their technological challenges for practical implementation.

Analysis of Simple Half-Shared Transimpedance Amplifier for Picoampere Biosensor Measurements

High-throughput recordings of small current are becoming more common in biosensor applications, including in vivo dopamine measurements, single-cell electrophysiology, photoplethysmography, pulse oximetry, and nanopore recordings. Thus, a highly scalable transimpedance amplifier design is in demand. Half-shared amplifier design is one way to improve the scalability by sharing the non-inverting side of the operational amplifier design for many inverting halves. This method reduces silicon area and power by nearly half compared to using independent operational amplifiers. In this paper, we analyze the scalability of a simple half-shared amplifier structure while investigating the tradeoff of increasing the number of inverting half amplifiers sharing a single non-inverting half. A transimpedance amplifier is designed using the half-shared structure to minimize the size per amplifier. The transimpedance amplifier is based on a current integration of a capacitor. The noise analysis of the integration amplifier is a challenging task because it does not reach a steady-state, thus, being a non-stationary circuit. For frequency analysis, a conversion method is discussed to estimate the noise characteristic in the simulation. The array design of 1024 transimpedance amplifiers is fabricated using a standard 0.35 μm process and is tested to confirm the validity of above analysis. The amplifier array exhibits high linearity in transimpedance gain (7.00 mV/pA for high gain and 0.86 mV/pA for low gain), low mismatch of 1.65 mV across the entire 1024 amplifier array, and extremely low noise. The technique will be crucial in enabling the fabrication of larger arrays to enable higher throughput measurement tools for biosensor applications.

Comparative Design Study for Power Reduction in Organic Optoelectronic Pulse Meter Sensor

This paper demonstrated a new design structure for minimizing the power consumption of a pulse meter. Monolithic devices composed of a red (625 nm) organic light-emitting diode (OLED) and an organic photodiode (OPD) were fabricated on the same substrate. Two organic devices were designed differently. One had a circle-shaped OLED in the center of the device and was surrounded by the OPD, while the other had the opposite structure. The external quantum efficiency (EQE) of the OLED and the OPD were 7% and 37%, respectively. We evaluated and compared the signal-to-noise ratio (SNR) of the photoplethysmogram (PPG) signal on different parts of the body and successfully acquired clear PPG signals at those positions, where the best signal was obtained from the fingertip at a SNR of about 62 dB. The proposed organic pulse meter sensor was operated successfully with a power consumption of 0.1 mW. Eventually, the proposed organic biosensor reduced the power consumption and improved the capability of the pulse meter for long-term use.

Psycho-Physiological Effects of a Peony-Viewing Program on Middle-Aged and Elderly Individuals at Different Phenological Stages

To address the question of whether the behavior of humans to view different phenological peony flowers has various effects on their physical and mental parameters, we investigated psycho-physiological responses of 74 participants (61.3 ± 10.78 years old) to environments of pre- and post-viewing tree peonies at four stages, including the exhibition leaf stage (ELS), initial bloom stage (IBS), full bloom stage (FBS), and terminal bloom stage (TBS). Physiological factors were examined using systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), fingertip pulse (FP), blood oxygen saturation (SpO₂), and psychological evaluation, which was carried out using the Profile of Mood States (POMS) and State–Trait Anxiety Inventory (STAI). The results indicated that the SBP, DBP, HR, and FP levels of participants were significantly reduced after viewing tree peonies, whereas no remarkable alterations in SpO₂ were found. The POMS scores of anger–hostility (A–H), fatigue–inertia (F–I), tension–anxiety (T–A), confusion–bewilderment (C–B), and depression–dejection (D–D) were significantly lower, but of vigor–activity (V–A) was higher post-viewing than pre-viewing. Furthermore, participants exhibited markedly decreased anxiety levels according to the STAI. Notably, the changes in measurement indices were more pronounced at the FBS. Our studies demonstrated that a short peony-viewing program, especially at the FBS with completely opened and large tree peony flowers, would be a promising therapeutic method for improving physiological functions as well as an effective psychological relaxation strategy for middle-aged and elderly individuals.

A Low Power and Fast Tracking Light-to-Frequency Converter With Adaptive Power Scaling for Blood SpO 2 Sensing

This paper presents a monolithic low power and fast tracking light-to-frequency converter for blood SpO ₂ sensing. Normally, the tracking speed and the power consumption are two contradictory characteristics. However, different gain-bandwidth specifications for various ambient light intensities allow the dynamic optimization of the power consumption according to the light intensity. In this paper, the amplifier power consumption is adaptively scaled by the generated light-intensity-positively-correlated control voltage. Thus, the chip total power consumption at low light intensity is significantly decreased. Moreover, the proposed adaptive power scaling is achieved with a continuous analog domain, which does not introduce extra switching noise. The proposed light-to-frequency sensor chip is fabricated by using 0.35  μm CMOS technology with a die area of 1 × 0.9 mm ². The measurement results show that the pulse light response for any light intensity is no longer than two new output square-wave cycles. The maximum total current consumption is 1.9 mA from a 3.3 V supply voltage, which can be adaptively scaled down to only 0.7 mA if the output frequency is about 25 KHz or lower. The minimum operational supply voltage of the proposed sensor chip is 2.5 V in the temperature range of -25 to 80  ^°C with 4 KV ESD level (human-body model).

A Low-Power Photoplethysmogram-Based Heart Rate Sensor Using Heartbeat Locked Loop

In this paper, we present an ultralow power heart rate (HR) monitoring photoplethysmography (PPG) sensor using a heartbeat locked loop (HBLL). The HBLL generates a narrow window that turns on the LED and analog-front-end only when a peak is expected in the PPG signal. The prototype PPG sensor implemented in 0.18  μm CMOS has an effective duty-cycle of 0.01% and consumes only 43.4  μW at a HR of 60 b/m, which is the lowest power consumption compared with previous state-of-the-art PPG sensors. The HR error of the proposed sensor is less than 2.1 b/m for HR below 180 b/m.

A Low-Power Dynamic-Range Relaxed Analog Front End for Photoplethysmogram Acquisition

This paper presents a low-power analog front-end that enables photoplethysmographic signals acquisition, the dynamic range for AC component exaction is relaxed with simple high-pass implementation. The chopping modulation ensures the low-noise operation. The circuit is fabricated in a 0.18-um CMOS technology. Measurements show that the consuming current is approximately 72 uA at a supply of 2.5 V. The circuit achieves a input noise of 6.45 $\mathrm{pA}/\sqrt{Hz}$. The calibred algorithm is implemented by means of MCU, and the demonstration that is compared with the Fluck Simulator used as the reference shows the heart rate is accurately detected, and the error of the measured blood oxygen saturation is less than 1.5%.

Quadrature Synthetic Aperture Beamforming Front-End for Miniaturized Ultrasound Imaging

A quadrature synthetic aperture front-end receiver for B-mode ultrasound imaging is presented. The receiver targets small-scale imaging applications such as capsule endoscopy and low-cost portable devices. System complexity, area, power consumption, and cost are minimized using synthetic aperture beamforming (SAB), whereby signals are processed in a sequential manner using only a single channel. SAB is combined with quadrature (I/Q) sampling, which further reduces the bandwidth and computational load. I/Q demodulation is carried out using a full custom analog front-end (AFE), which comprises a low-noise, variable gain preamplifier, followed by a passive mixer, programmable gain amplifier (PGA) and active lowpass filter. A novel preamplifier design is proposed, with quasi-exponential time-gain control and low noise (${\text{5.42 nV}}/\sqrt{\text{Hz}}$ input-referred noise). Overall, the AFE consumes ${\text{7.8 mW}}$ (static power) and occupies ${\text{1.5}}\,\text{mm}\times {\text{1.5}}\,\text{mm}$ in AMS ${\text{0.35}}\,\mu \text{m}$ CMOS. Real-time SAB is carried out using a Spartan-6 FPGA, which dynamically apodises and focuses the data by interpolating and applying complex phase rotations to the I/Q samples. For a frame rate of ${\text{7}}\,\text{Hz}$ , the power consumption is ${\text{3.4}}\,\text{mW}/\text{channel}$ across an aperture of 64 elements. B-mode images were obtained using a database of ultrasound signals ( ${\text{2.5}}\,\text{MHz}$ center frequency) derived from a commercial ultrasound machine. The normalized root mean squared error between the quadrature SAB image and the RF reference image was ${\text{13}}\%$. Image quality/frame rate may be tuned by varying the degree of spatial compounding.

Developing a Wireless, High Precision and Processing Speed Pulse Monitoring Headset Using Photoplethysmography

In this paper, thorough improvement of pulse monitoring and analysis equipment with a headset structure is presented. In order to study the most suitable infrared wavelength for the acquisition of the pulse wave at the earlobe, Monte Carlo simulation was adapted. Both high frequency noise and baseline drift, generated in the signal acquisition process, are considered. To further optimize the system design and improve accuracy, for the sensor's dimensional drift, the corresponding compensation was carried on in the software. This paper introduced nonlinear quantization, especially in terms of very weak pulse signal, in the time domain analysis process. A quick extraction method named table look-up combing with interpolation was utilized to obtain frequency domain information whose processing speed can be increased by about 30 times compared with fast Fourier transformation setting the sampling point as 300. The results demonstrated the sensor's excellent performance in pulse signal acquisition whose maximum residual is less than 0.004 mV. The test on a random sample of 300 people indicates that the system had high correlation with reference, validating the system accuracy is extremely high. Overall, this paper provides a practical pulse monitoring and analysis system with high precision and processing speed that can be widely applied in the field of health management or medical measurement.

A novel hardware implementation for detecting respiration rate using photoplethysmography

Asthma is a serious public health problem. Continuous monitoring of breathing may offer an alternative way to assess disease status. In this paper we present a novel hardware implementation for the capture and storage of a photoplethysmography (PPG) signal. The LED duty cycle was altered to determine the effect on respiratory rate accuracy. The oximeter was mounted to the left index finger of ten healthy volunteers. The breathing rate derived from the oximeter was validated against a nasal airflow sensor. The duty cycle of a pulse oximeter was changed between 5%, 10% and 25% at a sample rate of 500 Hz. A PPG signal and reference signal was captured for each duty cycle. The PPG signals were post processed in Matlab to derive a respiration rate using an existing Matlab toolbox. At a 25% duty cycle the RMSE was <;2 breaths per minute for the top performing algorithm. The RMSE increased to over 5 breaths per minute when the duty cycle was reduced to 5%. The power consumed by the hardware for a 5%, 10% and 25% duty cycle was 5.4 mW, 7.8 mW, and 15 mW respectively. For clinical assessment of respiratory rate, a RSME of <;2 breaths per minute is recommended. Further work is required to determine utility in asthma management. However for non-clinical applications such as fitness tracking, lower accuracy may be sufficient to allow a reduced duty cycle setting.

A 172 $\mu$W Compressively Sampled Photoplethysmographic (PPG) Readout ASIC With Heart Rate Estimation Directly From Compressively Sampled Data

A compressive sampling (CS) photoplethysmographic (PPG) readout with embedded feature extraction to estimate heart rate (HR) directly from compressively sampled data is presented. It integrates a low-power analog front end together with a digital back end to perform feature extraction to estimate the average HR over a 4 s interval directly from compressively sampled PPG data. The application-specified integrated circuit (ASIC) supports uniform sampling mode (1x compression) as well as CS modes with compression ratios of 8x, 10x, and 30x. CS is performed through nonuniformly subsampling the PPG signal, while feature extraction is performed using least square spectral fitting through Lomb-Scargle periodogram. The ASIC consumes 172  μ W of power from a 1.2 V supply while reducing the relative LED driver power consumption by up to 30 times without significant loss of relevant information for accurate HR estimation.

A Low-Power Wide Dynamic-Range Current Readout Circuit for Ion-Sensitive FET Sensors

This paper presents an amplifier-less and digital-intensive current-to-digital converter for ion-sensitive FET sensors. Capacitance on the input node is utilized as a residue accumulator, and a clocked comparator is followed for quantization. Without any continuous-time feedback circuit, the converter performs a first-order noise shaping of the quantization error. In order to minimize static power consumption, the proposed circuit employs a single-ended current-steering digital-to-analog converter which flows only the same current as the input. By adopting a switching noise averaging algorithm, our dynamic element matching not only mitigates mismatch of current sources in the current-steering DAC, but also makes the effect of dynamic switching noise become an input-independent constant. The implemented circuit in 0.35 μm CMOS converts the current input with a range of 2.8 μ A to 15 b digital output in about 4 ms, showing a DNL of +0.24/-0.25 LSB and an INL of + 1.98/-1.98 LSB while consuming 16.8 μW.

Wearable Sensors for Remote Health Monitoring

Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant  burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed.

Wearable Sensors for Remote Health Monitoring

Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant  burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed.

Ambient light cancellation in photoplethysmogram application using alternating sampling and charge redistribution technique

To overcome a large DC offset, ambient light interference, and optical path variation, a robust PPG readout chip is fabricated using 0.13-μm CMOS process. Against the large DC offset, a saturation detection and current feedback method can compensate a current of up to 30 μA. To be robust against optical path variation, an automatic emitting light compensation method is adopted. To remove the ambient light interference, we propose an alternating sampling and charge redistribution technique, in which no additional power is consumed, and only three differential switches and one capacitor are required. The PPG readout channel consumes 26 μW and has a input referred current noise of 260 pArms.

Interference Resilient Sigma Delta-Based Pulse Oximeter

Ambient light and optical interference can severely affect the performance of pulse oximeters. The deployment of a robust modulation technique to drive the pulse oximeter LEDs can reduce these unwanted effects and increases the resilient of the pulse oximeter against artificial ambient light. The time division modulation technique used in conventional pulse oximeters can not remove the effect of modulated light coming from surrounding environment and this may cause huge measurement error in pulse oximeter readings. This paper presents a novel cross-coupled sigma delta modulator which ensures that measurement accuracy will be more robust in comparison with conventional fixed-frequency oximeter modulation technique especially in the presence of pulsed artificial ambient light. Moreover, this novel modulator gives an extra control over the pulse oximeter power consumption leading to improved power management.

Low-Power Photoplethysmogram Acquisition Integrated Circuit with Robust Light Interference Compensation

To overcome light interference, including a large DC offset and ambient light variation, a robust photoplethysmogram (PPG) readout chip is fabricated using a 0.13-μm complementary metal–oxide–semiconductor (CMOS) process. Against the large DC offset, a saturation detection and current feedback circuit is proposed to compensate for an offset current of up to 30 μA. For robustness against optical path variation, an automatic emitted light compensation method is adopted. To prevent ambient light interference, an alternating sampling and charge redistribution technique is also proposed. In the proposed technique, no additional power is consumed, and only three differential switches and one capacitor are required. The PPG readout channel consumes 26.4 μW and has an input referred current noise of 260 pArms.

Noncontact Monitoring of Blood Oxygen Saturation Using Camera and Dual-Wavelength Imaging System

We present a noncontact method to monitor blood oxygen saturation (SpO2). The method uses a CMOS camera with a trigger control to allow recording of photoplethysmography (PPG) signals alternatively at two particular wavelengths, and determines the SpO2 from the measured ratios of the pulsatile to the nonpulsatile components of the PPG signals at these wavelengths. The signal-to-noise ratio (SNR) of the SpO2 value depends on the choice of the wavelengths. We found that the combination of orange (λ = 611 nm) and near infrared (λ = 880 nm) provides the best SNR for the noncontact video-based detection method. This combination is different from that used in traditional contact-based SpO 2 measurement since the PPG signal strengths and camera quantum efficiencies at these wavelengths are more amenable to SpO2 measurement using a noncontact method. We also conducted a small pilot study to validate the noncontact method over an SpO2 range of 83%-98%. This study results are consistent with those measured using a reference contact SpO2 device ( r = 0.936, ). The presented method is particularly suitable for tracking one's health and wellness at home under free-living conditions, and for those who cannot use traditional contact-based PPG devices.

A Low-Power, Dual-Wavelength Photoplethysmogram (PPG) SoC With Static and Time-Varying Interferer Removal

This paper presents a low-power, reflectance-mode photoplethysmogram (PPG) front end with up to 100 μA of static interferer current removal and 87 dB attenuation of time-varying interferers. The chip nominally consumes 425 μW including signal chain circuits, red and IR LED drive power, clocks, digitization and I/O. Measured data shows the noise of the PPG signal to be dominated by the photodiode sensor photon shot noise.

A Single-Chip CMOS Pulse Oximeter with On-Chip Lock-In Detection

Pulse oximetry is a noninvasive and continuous method for monitoring the blood oxygen saturation level. This paper presents the design and testing of a single-chip pulse oximeter fabricated in a 0.35 µm CMOS process. The chip includes photodiode, transimpedance amplifier, analogue band-pass filters, analogue-to-digital converters, digital signal processor and LED timing control. The experimentally measured AC and DC characteristics of individual circuits including the DC output voltage of the transimpedance amplifier, transimpedance gain of the transimpedance amplifier, and the central frequency and bandwidth of the analogue band-pass filters, show a good match (within 1%) with the circuit simulations. With modulated light source and integrated lock-in detection the sensor effectively suppresses the interference from ambient light and 1/f noise. In a breath hold and release experiment the single chip sensor demonstrates consistent and comparable performance to commercial pulse oximetry devices with a mean of 1.2% difference. The single-chip sensor enables a compact and robust design solution that offers a route towards wearable devices for health monitoring.

Adaptive pulse width control and sampling for low power pulse oximetry

Remote sensing of physiological parameters could be a cost effective approach to improving health care, and low-power sensors are essential for remote sensing because these sensors are often energy constrained. This paper presents a power optimized photoplethysmographic sensor interface to sense arterial oxygen saturation, a technique to dynamically trade off SNR for power during sensor operation, and a simple algorithm to choose when to acquire samples in photoplethysmography. A prototype of the proposed pulse oximeter built using commercial-off-the-shelf (COTS) components is tested on 10 adults. The dynamic adaptation techniques described reduce power consumption considerably compared to our reference implementation, and our approach is competitive to state-of-the-art implementations. The techniques presented in this paper may be applied to low-power sensor interface designs where acquiring samples is expensive in terms of power as epitomized by pulse oximetry.

A sub-mW fully-integrated pulse oximeter front-end

This paper presents the implementation of the first fully integrated pulse oximeter front-end with a power consumption lower than 1 mW. This is enabled by system- and block-level noise optimisation, also detailed in the manuscript. The proposed design features an analogue feedback loop that enables fast and accurate regulation of the detected photocurrent level and a serial-to-parallel interface allowing for extensive programmability of several operation parameters. The front-end was fabricated in the AMS 0.35 μm technology and occupies an area of 1.35 mm(2). Extensive measured results, both electrical and physiological from human subjects are reported, demonstrating an estimated SNR of 39 dB and ability to detect 2% changes in SpO2, similar to commercial pulse oximeters. This is despite the constrained power consumption which amounts to 0.31 mW for the LEDs and 0.53 mW for the rest of the front-end from a 3.3 V supply. Statistical results from 20 chips verify good matching across the Red and Infrared channels of the front-end and the accurate operation of the proposed analogue feedback loop.

A wireless reflectance pulse oximeter with digital baseline control for unfiltered photoplethysmograms

Pulse oximeters are central to the move toward wearable health monitoring devices and medical electronics either hosted by, e.g., smart phones or physically embedded in their design. This paper presents a small, low-cost pulse oximeter design appropriate for wearable and surface-based applications that also produces quality, unfiltered photo-plethysmograms (PPGs) ideal for emerging diagnostic algorithms. The design's "filter-free" embodiment, which employs only digital baseline subtraction as a signal compensation mechanism, distinguishes it from conventional pulse oximeters that incorporate filters for signal extraction and noise reduction. This results in high-fidelity PPGs with thousands of peak-to-peak digitization levels that are sampled at 240 Hz to avoid noise aliasing. Electronic feedback controls make these PPGs more resilient in the face of environmental changes (e.g., the device can operate in full room light), and data stream in real time across either a ZigBee wireless link or a wired USB connection to a host. On-board flash memory is available for store-and-forward applications. This sensor has demonstrated an ability to gather high-integrity data at fingertip, wrist, earlobe, palm, and temple locations from a group of 48 subjects (20 to 64 years old).

An Electronic Patch for wearable health monitoring by reflectance pulse oximetry

We report the development of an Electronic Patch for wearable health monitoring. The Electronic Patch is a new health monitoring system incorporating biomedical sensors, microelectronics, radio frequency (RF) communication, and a battery embedded in a 3-dimensional hydrocolloid polymer. In this paper the Electronic Patch is demonstrated with a new optical biomedical sensor for reflectance pulse oximetry so that the Electronic Patch in this case can measure the pulse and the oxygen saturation. The reflectance pulse oximetry solution is based on a recently developed annular backside silicon photodiode to enable low power consumption by the light emitting components. The Electronic Patch has a disposable part of soft adhesive hydrocolloid polymer and a reusable part of hard polylaurinlactam. The disposable part contains the battery. The reusable part contains the reflectance pulse oximetry sensor and microelectronics. The reusable part is 'clicked' into the disposable part when the patch is prepared for use. The patch has a size of 88 mm by 60 mm and a thickness of 5 mm.

High resolution wireless body area network with statistically synchronized sensor data for tracking pulse wave velocity

Wireless body area networks (WBANs) will take on more diverse forms in terms of their sensor combinations and communication protocols as their presence is extended to a greater number of monitoring scenarios. This paper presents an application layer protocol that solves issues caused by sensor nodes that must compete for high speed, real-time communication with the receiver. Such applications emphasize the delivery of large amounts of raw data from different sensor nodes in a time-synchronized manner, rather than channels that experience intermittent operation. An example of tracking pulse wave velocity (PWV) is introduced in this paper, where high-precision PWVs are estimated with the help of timeline recovery and feature extraction processes in MATLAB.