An Electronic Patch for wearable health monitoring by reflectance pulse oximetry

Evolution of nanostructured skin patches towards multifunctional wearable platforms for biomedical applications

Recent advances in the field of skin patches have promoted the development of wearable and implantable bioelectronics for long-term, continuous healthcare management and targeted therapy. However, the design of electronic skin (e-skin) patches with stretchable components is still challenging and requires an in-depth understanding of the skin-attachable substrate layer, functional biomaterials and advanced self-powered electronics. In this comprehensive review, we present the evolution of skin patches from functional nanostructured materials to multi-functional and stimuli-responsive patches towards flexible substrates and emerging biomaterials for e-skin patches, including the material selection, structure design and promising applications. Stretchable sensors and self-powered e-skin patches are also discussed, ranging from electrical stimulation for clinical procedures to continuous health monitoring and integrated systems for comprehensive healthcare management. Moreover, an integrated energy harvester with bioelectronics enables the fabrication of self-powered electronic skin patches, which can effectively solve the energy supply and overcome the drawbacks induced by bulky battery-driven devices. However, to realize the full potential offered by these advancements, several challenges must be addressed for next-generation e-skin patches. Finally, future opportunities and positive outlooks are presented on the future directions of bioelectronics. It is believed that innovative material design, structure engineering, and in-depth study of fundamental principles can foster the rapid evolution of electronic skin patches, and eventually enable self-powered close-looped bioelectronic systems to benefit mankind.

On the development of low power wearable devices for assessment of physiological vital parameters: a systematic review

Aim

Smart wearable devices for continuous monitoring of health conditions have bbecome very important in the healthcare sector to acquire and assess the different physiological parameters. This paper reviews the nature of physiological signals, desired vital parameters, role of smart wearable devices, choices of wearable devices and design considerations for wearable devices for early detection of health conditions.

Subject and methods

This article provides designers with information to identify and develop smart wearable devices based on the data extracted from a literature survey on previously published research articles in the field of wearable devices for monitoring vital parameters.

Results

The key information available in this article indicates that quality signal acquisition, processing and longtime monitoring of vital parameters requires smart wearable devices. The development of smart wearable devices with the listed design criteria supports the developer to design a low power wearable device for continuous monitoring of patient health conditions.

Conclusion

The wide range of information gathered from the review indicates that there is a huge demand for smart wearable devices for monitoring health conditions at home. It further supports tracking heath status in the long term via monitoring the vital parameters with the support of wireless communication principles.

Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis

The HeartPy Python toolkit for analysis of noisy signals from heart rate measurements is an excellent tool to use in conjunction with novel wearable sensors. Nevertheless, most of the work to date has focused on applying the toolkit to data measured with commercially available sensors. We demonstrate the application of the HeartPy functions to data obtained with a novel graphene-based heartbeat sensor. We produce the sensor by laser-inducing graphene on a flexible polyimide substrate. Both graphene on the polyimide substrate and graphene transferred onto a PDMS substrate show piezoresistive behavior that can be utilized to measure human heartbeat by registering median cubital vein motion during blood pumping. We process electrical resistance data from the graphene sensor using HeartPy and demonstrate extraction of several heartbeat parameters, in agreement with measurements taken with independent reference sensors. We compare the quality of the heartbeat signal from graphene on different substrates, demonstrating that in all cases the device yields results consistent with reference sensors. Our work is a first demonstration of successful application of HeartPy to analysis of data from a sensor in development.

Recent advances in wearable medical diagnostic sensors and new therapeutic dosage forms for fever in children

Fever in children is one of the most common symptoms of pediatric diseases and the most common complaint in pediatric clinics, especially in the emergency department. Diseases such as pneumonia, sepsis, and meningitis are leading causes of death in children, and the early manifestations of these diseases are accompanied by fever symptoms. Accurate diagnosis and real-time monitoring of the status of febrile children, rapid and effective identification of the cause, and treatment can have a positive impact on relieving their symptoms and improving their quality of life. In recent years, wearable diagnostic sensors have attracted special attention for their high flexibility, real-time monitoring, and sensitivity. Temperature sensors and heart rate sensors have provided new advances in detecting children's body temperature and heart rate. Furthermore, some novel formulations have also received wide attention for addressing bottlenecks in medication administration for febrile children, such as difficulty in swallowing and inaccurate dosing. In this context, the present review provides recent advances of novel wearable medical sensor devices for diagnosing fever. Moreover, the application progress of innovative dosage forms of classical antipyretic drugs for children is presented. Finally, challenges and prospects of wearable sensor-based diagnostics and novel agent-based treatment of fever in children are discussed in brief.

Neonatal wearable device for colorimetry-based real-time detection of jaundice with simultaneous sensing of vitals

Neonatal jaundice occurs in >80% of newborns in the first week of life owing to physiological hyperbilirubinemia. Severe hyperbilirubinemia could cause brain damage owing to its neurotoxicity, a state commonly known as kernicterus. Therefore, periodic bilirubin monitoring is essential to identify infants at-risk and to initiate treatment including phototherapy. However, devices for continuous measurements of bilirubin have not been developed yet. Here, we established a wearable transcutaneous bilirubinometer that also has oxygen saturation (SpO2) and heart rate (HR) sensing functionalities. Clinical experiments with neonates demonstrated the possibility of simultaneous detection of bilirubin, SpO2, and HR. Moreover, our device could consistently measure bilirubin during phototherapy. These results demonstrate the potential for development of a combined treatment approach with an automatic link via the wearable bilirubinometer and phototherapy device for optimization of the treatment of neonatal jaundice.

Wearable Sensing and Telehealth Technology with Potential Applications in the Coronavirus Pandemic

Coronavirus disease 2019 (COVID-19) has emerged as a pandemic with serious clinical manifestations including death. A pandemic at the large-scale like COVID-19 places extraordinary demands on the world's health systems, dramatically devastates vulnerable populations, and critically threatens the global communities in an unprecedented way. While tremendous efforts at the frontline are placed on detecting the virus, providing treatments and developing vaccines, it is also critically important to examine the technologies and systems for tackling disease emergence, arresting its spread and especially the strategy for diseases prevention. The objective of this article is to review enabling technologies and systems with various application scenarios for handling the COVID-19 crisis. The article will focus specifically on 1) wearable devices suitable for monitoring the populations at risk and those in quarantine, both for evaluating the health status of caregivers and management personnel, and for facilitating triage processes for admission to hospitals; 2) unobtrusive sensing systems for detecting the disease and for monitoring patients with relatively mild symptoms whose clinical situation could suddenly worsen in improvised hospitals; and 3) telehealth technologies for the remote monitoring and diagnosis of COVID-19 and related diseases. Finally, further challenges and opportunities for future directions of development are highlighted.

Recent Progress in Wearable Biosensors: From Healthcare Monitoring to Sports Analytics

Recent advances in lab-on-a-chip technology establish solid foundations for wearable biosensors. These newly emerging wearable biosensors are capable of non-invasive, continuous monitoring by miniaturization of electronics and integration with microfluidics. The advent of flexible electronics, biochemical sensors, soft microfluidics, and pain-free microneedles have created new generations of wearable biosensors that explore brand-new avenues to interface with the human epidermis for monitoring physiological status. However, these devices are relatively underexplored for sports monitoring and analytics, which may be largely facilitated by the recent emergence of wearable biosensors characterized by real-time, non-invasive, and non-irritating sensing capacities. Here, we present a systematic review of wearable biosensing technologies with a focus on materials and fabrication strategies, sampling modalities, sensing modalities, as well as key analytes and wearable biosensing platforms for healthcare and sports monitoring with an emphasis on sweat and interstitial fluid biosensing. This review concludes with a summary of unresolved challenges and opportunities for future researchers interested in these technologies. With an in-depth understanding of the state-of-the-art wearable biosensing technologies, wearable biosensors for sports analytics would have a significant impact on the rapidly growing field-microfluidics for biosensing.

On-Device Reliability Assessment and Prediction of Missing Photoplethysmographic Data Using Deep Neural Networks

Photoplethysmographic (PPG) measurements from ambulatory subjects may suffer from unreliability due to body movements and missing data segments due to loosening of sensor. This paper describes an on-device reliability assessment from PPG measurements using a stack denoising autoencoder (SDAE) and multilayer perceptron neural network (MLPNN). The missing segments were predicted by a personalized convolutional neural network (CNN) and long-short term memory (LSTM) model using a short history of the same channel data. Forty sets of volunteers' data, consisting of equal share of healthy and cardiovascular subjects were used for validation and testing. The PPG reliability assessment model (PRAM) achieved over 95% accuracy for correctly identifying acceptable PPG beats out of total 5000 using expert annotated data. Disagreement with experts' annotation was nearly 3.5%. The missing segment prediction model (MSPM) achieved a root mean square error (RMSE) of 0.22, and mean absolute error (MAE) of 0.11 for 40 missing beats prediction using only four beat history from the same channel PPG. The two models were integrated in a standalone device based on quad-core ARM Cortex-A53, 1.2 GHz, with 1 GB RAM, with 130 MB memory requirement and latency ∼0.35 s per beat prediction with a 30 s frame. The present method also provides improved performance with published works on PPG quality assessment and missing data prediction using two public datasets, CinC and MIMIC-II under PhysioNet.

Wearable and flexible electronics for continuous molecular monitoring

Wearable biosensors have received tremendous attention over the past decade owing to their great potential in predictive analytics and treatment toward personalized medicine. Flexible electronics could serve as an ideal platform for personalized wearable devices because of their unique properties such as light weight, low cost, high flexibility and great conformability. Unlike most reported flexible sensors that mainly track physical activities and vital signs, the new generation of wearable and flexible chemical sensors enables real-time, continuous and fast detection of accessible biomarkers from the human body, and allows for the collection of large-scale information about the individual's dynamic health status at the molecular level. In this article, we review and highlight recent advances in wearable and flexible sensors toward continuous and non-invasive molecular analysis in sweat, tears, saliva, interstitial fluid, blood, wound exudate as well as exhaled breath. The flexible platforms, sensing mechanisms, and device and system configurations employed for continuous monitoring are summarized. We also discuss the key challenges and opportunities of the wearable and flexible chemical sensors that lie ahead.

Recent Developments in Printing Flexible and Wearable Sensing Electronics for Healthcare Applications

Wearable biosensors attract significant interest for their capabilities in real-time monitoring of wearers' health status, as well as the surrounding environment. Sensor patches are embedded onto the human epidermis accompanied by data readout and signal conditioning circuits with wireless communication modules for transmitting data to the computing devices. Wearable sensors designed for recognition of various biomarkers in human epidermis fluids, such as glucose, lactate, pH, cholesterol, etc., as well as physiological indicators, i.e., pulse rate, temperature, breath rate, respiration, alcohol, activity monitoring, etc., have potential applications both in medical diagnostics and fitness monitoring. The rapid developments in solution-based nanomaterials offered a promising perspective to the field of wearable sensors by enabling their cost-efficient manufacturing through printing on a wide range of flexible polymeric substrates. This review highlights the latest key developments made in the field of wearable sensors involving advanced nanomaterials, manufacturing processes, substrates, sensor type, sensing mechanism, and readout circuits, and ends with challenges in the future scope of the field. Sensors are categorized as biological and fluidic, mounted directly on the human body, or physiological, integrated onto wearable substrates/gadgets separately for monitoring of human-body-related analytes, as well as external stimuli. Special focus is given to printable materials and sensors, which are key enablers for wearable electronics.

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 flexible organic reflectance oximeter array

The optical method to determine oxygen saturation in blood is limited to only tissues that can be transilluminated. The status quo provides a single-point measurement and lacks 2D oxygenation mapping capability. We use organic printed optoelectronics in a flexible array configuration that senses reflected light from tissue. Our reflectance oximeter is used beyond conventional sensing locations and accurately measures oxygen saturation on the forehead. In a full system implementation, coupled with a mathematical model, we create 2D oxygenation maps of adult forearms under pressure-cuff–induced ischemia. Our skin-like flexible sensor system has the potential to transform oxygenation monitoring of tissues, wounds, skin grafts, and transplanted organs.

Transmission-mode pulse oximetry, the optical method for determining oxygen saturation in blood, is limited to only tissues that can be transilluminated, such as the earlobes and the fingers. The existing sensor configuration provides only single-point measurements, lacking 2D oxygenation mapping capability. Here, we demonstrate a flexible and printed sensor array composed of organic light-emitting diodes and organic photodiodes, which senses reflected light from tissue to determine the oxygen saturation. We use the reflectance oximeter array beyond the conventional sensing locations. The sensor is implemented to measure oxygen saturation on the forehead with 1.1% mean error and to create 2D oxygenation maps of adult forearms under pressure-cuff–induced ischemia. In addition, we present mathematical models to determine oxygenation in the presence and absence of a pulsatile arterial blood signal. The mechanical flexibility, 2D oxygenation mapping capability, and the ability to place the sensor in various locations make the reflectance oximeter array promising for medical sensing applications such as monitoring of real-time chronic medical conditions as well as postsurgery recovery management of tissues, organs, and wounds.

A Self-Calibrated Tissue Viability Sensor for Free Flap Monitoring

In fasciocutaneous free flap surgery, close postoperative monitoring is crucial for detecting flap failure, as around 10% of cases require additional surgery due to compromised anastomosis. Different biochemical and biophysical techniques have been developed for continuous flap monitoring, however, they all have shortcoming in terms of reliability, elevated cost, potential risks to the patient, and inability to adapt to the patient's phenotype. A wearable wireless device based on near infrared spectroscopy has been developed for continuous blood flow and perfusion monitoring by quantifying tissue oxygen saturation (). This miniaturized and low-cost device is designed for postoperative monitoring of flap viability. With self-calibration, the device can adapt itself to the characteristics of the patients' skin such as tone and thickness. An extensive study was conducted with 32 volunteers. The experimental results show that the device can obtain reliable measurements across different phenotypes (age, sex, skin tone, and thickness). To assess its ability to detect flap failure, the sensor was tested in a pilot animal study. Free groin flaps were performed on 16 Sprague Dawley rats. Results demonstrate the accuracy of the sensor in assessing flap viability and identifying the origin of failure (venous or arterial thrombosis).

Multifunctional Smart Skin Adhesive Patches for Advanced Health Care

A skin adhesive patch is the most fundamental and widely used medical device for diverse health-care purposes. Conventional skin adhesive patches have been mainly utilized for routine medical purposes such as wound management, fixation of medical devices, and simple drug release. In contrast to traditional skin adhesive patches, recently developed patches incorporate multiple key functions of bulky medical devices into a thin, flexible patch based on emerging nanomaterials and flexible electronic technologies. Consequently, the meaning of the term "skin adhesive patch" becomes broader and smarter compared to the traditional term. This review summarizes recent efforts undertaken in the development of multifunctional advanced skin adhesive patches, and briefly describes future directions and challenges toward the next generation of smart skin adhesive patches for ubiquitous personalized health care.

Advances in Photopletysmography Signal Analysis for Biomedical Applications

Heart Rate Variability (HRV) is an important tool for the analysis of a patient’s physiological conditions, as well a method aiding the diagnosis of cardiopathies. Photoplethysmography (PPG) is an optical technique applied in the monitoring of the HRV and its adoption has been growing significantly, compared to the most commonly used method in medicine, Electrocardiography (ECG). In this survey, definitions of these technique are presented, the different types of sensors used are explained, and the methods for the study and analysis of the PPG signal (linear and nonlinear methods) are described. Moreover, the progress, and the clinical and practical applicability of the PPG technique in the diagnosis of cardiovascular diseases are evaluated. In addition, the latest technologies utilized in the development of new tools for medical diagnosis are presented, such as Internet of Things, Internet of Health Things, genetic algorithms, artificial intelligence and biosensors which result in personalized advances in e-health and health care. After the study of these technologies, it can be noted that PPG associated with them is an important tool for the diagnosis of some diseases, due to its simplicity, its cost⁻benefit ratio, the easiness of signals acquisition, and especially because it is a non-invasive technique.

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.

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.

Reduction of Periodic Motion Artifacts in Photoplethysmography

Periodic motion artifacts affect photoplethysmography (PPG) signals in activities of daily living (ADL), cardiopulmonary exercise testing (CPX), and cardiopulmonary resuscitation (CPR). This hampers measurement of interbeat intervals (IBIs) and oxygen saturation (SpO ₂ ). Our objective was to develop a generic algorithm to remove periodic motion artifacts, recovering artifact-reduced PPG signals for beat-to-beat analysis.

METHODS

The algorithm was retrospectively evaluated on forehead PPG signals measured while walking on a treadmill. The step rate was tracked in a motion reference signal via a second-order generalized integrator with a frequency-locked loop. Two reference signals were compared: sensor motion relative to the skin ( ∆x[n]) measured via self-mixing interferometry and head motion ( a_v[n] ) measured via accelerometry. The step rate was used in a quadrature harmonic model to estimate the artifacts. Quadrature components need only two coefficients per frequency leading to a short filter and prevent undesired frequency-shifted components in the artifact estimate. Subtracting the estimate from the measured signal reduced the artifacts.

RESULTS

Compared to ∆x[n] , a_v[n] had a better signal-to-noise ratio and more consistently contained a component at the step rate. Artifact reduction was effective for distinct step rate and pulse rate, since the artifact-reduced signals provided more stable IBI and SpO ₂ measurements.

CONCLUSION

Accelerometry provided a more reliable motion reference signal. The proposed algorithm can be of significance for monitoring in ADL, CPX, or CPR, by providing artifact-reduced PPG signals for improved IBI and SpO ₂ measurements during periodic motion.

A wireless patch for sleep respiratory disorders applications

This paper presents a conformable wireless patch and its mobile application for physical activity, spO2 and pCO2 recording associated to digital biomarkers that aim at providing the clinicians with a reliable computer-aided diagnosis tool for rapid and continuous monitoring of sleep respiratory disorders. Each part of the system is described and results are presented and discussed. The reflectance sp02 sensor has been tested in vivo on several body sites and several subjects then compared to a reference device. The electrochemical tcpO2 sensor has been validated in vitro. Based on these physiological parameters, the proposed algorithms to automatically identifying sleep respiratory events are compared to a reference index.

Heart Rate Assessment Immediately after Birth

BACKGROUND

Heart rate assessment immediately after birth in newborn infants is critical to the correct guidance of resuscitation efforts. There are disagreements as to the best method to measure heart rate.

OBJECTIVE

The aim of this study was to assess different methods of heart rate assessment in newborn infants at birth to determine the fastest and most accurate method.

METHODS

PubMed, EMBASE and Google Scholar were systematically searched using the following terms: 'infant', 'heart rate', 'monitoring', 'delivery room', 'resuscitation', 'stethoscope', 'auscultation', 'palpation', 'pulse oximetry', 'electrocardiogram', 'Doppler ultrasound', 'photoplethysmography' and 'wearable sensors'.

RESULTS

Eighteen studies were identified that described various methods of heart rate assessment in newborn infants immediately after birth. Studies examining auscultation, palpation, pulse oximetry, electrocardiography and Doppler ultrasound as ways to measure heart rate were included. Heart rate measurements by pulse oximetry are superior to auscultation and palpation, but there is contradictory evidence about its accuracy depending on whether the sensor is connected to the infant or the oximeter first. Several studies indicate that electrocardiogram provides a reliable heart rate faster than pulse oximetry. Doppler ultrasound shows potential for clinical use, however future evidence is needed to support this conclusion.

CONCLUSION

Heart rate assessment is important and there are many measurement methods. The accuracy of routinely applied methods varies, with palpation and auscultation being the least accurate and electrocardiogram being the most accurate. More research is needed on Doppler ultrasound before its clinical use.

Photoplethysmography-Based Method for Automatic Detection of Premature Ventricular Contractions

This work introduces a method for detection of premature ventricular contractions (PVCs) in photoplethysmogram (PPG). The method relies on 6 features, characterising PPG pulse power, and peak-to-peak intervals. A sliding window approach is applied to extract the features, which are later normalized with respect to an estimated heart rate. Artificial neural network with either linear and non-linear outputs was investigated as a feature classifier. PhysioNet databases, namely, the MIMIC II and the MIMIC, were used for training and testing, respectively. After annotating the PPGs with respect to synchronously recorded electrocardiogram, two main types of PVCs were distinguished: with and without the observable PPG pulse. The obtained sensitivity and specificity values for both considered PVC types were 92.4/99.9% and 93.2/99.9%, respectively. The achieved high classification results form a basis for a reliable PVC detection using a less obtrusive approach than the electrocardiography-based detection methods.

Reflective oxygen saturation monitoring at hypothenar and its validation by human hypoxia experiment

BACKGROUND

Pulse oxygen saturation (SpO2) is an important parameter for healthcare, and wearable sensors and systems for SpO2 monitoring have become increasingly popular. The aim of this paper is to develop a novel SpO2 monitoring system, which detects photoplethysmographic (PPG) signals at hypothenar with a reflection-mode sensor embedded into a glove.

METHODS

A special photo-detector section was designed with two photodiodes arranged symmetrically to the red and infrared light-emitting diodes (LED) to enhance the signal quality. The reflective sensor was placed in a soft silicon substrate sewn in a glove to fit the surface of the hypothenar. To lower the power consumption, the LED driving current was reduced and energy-efficient electronic components were applied. The performance for PPG signal detection and SpO2 monitoring was evaluated by human hypoxia experiments. Accelerometer-based adaptive noise cancellation (ANC) methods applying the least mean squares (LMS) and recursive least squares (RLS) algorithms were studied to suppress motion artifact.

RESULTS

A total of 20 subjects participated in the hypoxia experiment. The degree of comfort for wearing this system was accepted by them. The PPG signals were detected effectively at SpO2 levels from about 100-70%. The experiment validated the accuracy of the system was 2.34%, compared to the invasive measurements. Both the LMS and RLS algorithms improved the performance during motion. The total current consumed by the system was only 8 mA.

CONCLUSIONS

It is feasible to detect PPG signal and monitor SpO2 at the location of hypothenar. This novel system can achieve reliable SpO2 measurements at different SpO2 levels and on different individuals. The system is light-weighted, easy to wear and power-saving. It has the potential to be a solution for wearable monitoring, although more work should be conducted to improve the motion-resistant performance significantly.

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 configurable and low-power mixed signal SoC for portable ECG monitoring applications

This paper describes a mixed-signal ECG System-on-Chip (SoC) that is capable of implementing configurable functionality with low-power consumption for portable ECG monitoring applications. A low-voltage and high performance analog front-end extracts 3-channel ECG signals and single channel electrode-tissue-impedance (ETI) measurement with high signal quality. This can be used to evaluate the quality of the ECG measurement and to filter motion artifacts. A custom digital signal processor consisting of 4-way SIMD processor provides the configurability and advanced functionality like motion artifact removal and R peak detection. A built-in 12-bit analog-to-digital converter (ADC) is capable of adaptive sampling achieving a compression ratio of up to 7, and loop buffer integration reduces the power consumption for on-chip memory access. The SoC is implemented in 0.18 μm CMOS process and consumes 32 μ W from a 1.2 V while heart beat detection application is running, and integrated in a wireless ECG monitoring system with Bluetooth protocol. Thanks to the ECG SoC, the overall system power consumption can be reduced significantly.

A flexible, nonenzymatic glucose biosensor based on Ni-coordinated, vertically aligned carbon nanotube arrays

We evaluated the use of flexible biosensors based on Ni-coordinated, vertically aligned carbon nanotubes on a flexible graphite substrate (Ni/VCNTs/G) for the nonenzymatic electrochemical detection of glucose.

A highly linear fully integrated powerline filter for biopotential acquisition systems

Powerline interference is one of the most dominant problems in detection and processing of biopotential signals. This work presents a new fully integrated notch filter exhibiting high linearity and low power consumption. High filter linearity is preserved utilizing active-RC approach while IC implementation is achieved through replacing passive resistors by R-2R ladders achieving area saving of approximately 120 times. The filter design is optimized for low power operation using an efficient circuit topology and an ultra-low power operational amplifier. Fully differential implementation of the proposed filter shows notch depth of 43 dB (78 dB for 4th-order) with THD of better than -70 dB while consuming about 150 nW from 1.5 V supply.

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.

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.