A clip-free eyeglasses-based wearable monitoring device for measuring photoplethysmograhic signals

Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network

Assessing vital signs such as heart rate (HR) by wearable devices in a lifestyle-related environment provides widespread opportunities for public health related research and applications. Commonly, consumer wearable devices assessing HR are based on photoplethysmography (PPG), where HR is determined by absorption and reflection of emitted light by the blood. However, methodological differences and shortcomings in the validation process hamper the comparability of the validity of various wearable devices assessing HR. Towards Intelligent Health and Well-Being: Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives towards developing best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice validation protocol for consumer wearables assessing HR by PPG. The recommendations were developed through the following multi-stage process: (1) a systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, (2) an unstructured review of the wider literature pertaining to factors that may introduce bias during the validation of these devices and (3) evidence-informed expert opinions of the INTERLIVE Network. A total of 44 articles were deemed eligible and retrieved through our systematic literature review. Based on these studies, a wider literature review and our evidence-informed expert opinions, we propose a validation framework with standardised recommendations using six domains: considerations for the target population, criterion measure, index measure, testing conditions, data processing and the statistical analysis. As such, this paper presents recommendations to standardise the validity testing and reporting of PPG-based HR wearables used by consumers. Moreover, checklists are provided to guide the validation protocol development and reporting. This will ensure that manufacturers, consumers, healthcare providers and researchers use wearables safely and to its full potential.

A Novel Analog Front End with Voltage-Dependent Input Impedance and Bandpass Amplification for Capacitive Biopotential Measurements

This paper proposes a novel analogue front end (AFE) that has three features: voltage-dependent input impedance, bandpass amplification, and stray capacitance reduction. With a view to applying the AFE to capacitive biopotential measurements (CBMs), the three features were investigated separately in a schematic and mathematical manner. Capacitive electrocardiogram (cECG) or capacitive electromyogram (cEMG) measurements using the AFE were performed in low-humidity conditions (below 35% relative humidity) for a total of seven human subjects. Performance evaluation of the AFE revealed the following: (1) the proposed AFE in cECG measurement with 1.70-mm thick clothing reduced the baseline recovery time and root mean square voltage of respiratory interference in subjects with healthy-weight body mass index (BMI), and increased R-wave amplitude for overweight-BMI subjects; and (2) the proposed AFE in cEMG measurement of biceps brachii muscle yielded stable electromyographic waveforms without the marked DC component for all subjects and a significant (p < 0.01) increase in the signal-to-noise ratio. These results indicate that the proposed AFE can provide a feasible balance between sensitivity and stability in CBMs, and it could be a versatile replacement for the conventional voltage follower used in CBMs.

Wearable System for Biosignal Acquisition and Monitoring Based on Reconfigurable Technologies

Wearable monitoring devices are now a usual commodity in the market, especially for the monitoring of sports and physical activity. However, specialized wearable devices remain an open field for high-risk professionals, such as military personnel, fire and rescue, law enforcement, etc. In this work, a prototype wearable instrument, based on reconfigurable technologies and capable of monitoring electrocardiogram, oxygen saturation, and motion, is presented. This reconfigurable device allows a wide range of applications in conjunction with mobile devices. As a proof-of-concept, the reconfigurable instrument was been integrated into ad hoc glasses, in order to illustrate the non-invasive monitoring of the user. The performance of the presented prototype was validated against a commercial pulse oximeter, while several alternatives for QRS-complex detection were tested. For this type of scenario, clustering-based classification was found to be a very robust option.

Increasing accuracy of pulse transit time measurements by automated elimination of distorted photoplethysmography waves

Photoplethysmography (PPG) is a widely available non-invasive optical technique to visualize pressure pulse waves (PWs). Pulse transit time (PTT) is a physiological parameter that is often derived from calculations on ECG and PPG signals and is based on tightly defined characteristics of the PW shape. PPG signals are sensitive to artefacts. Coughing or movement of the subject can affect PW shapes that much that the PWs become unsuitable for further analysis. The aim of this study was to develop an algorithm that automatically and objectively eliminates unsuitable PWs. In order to develop a proper algorithm for eliminating unsuitable PWs, a literature study was conducted. Next, a '7Step PW-Filter' algorithm was developed that applies seven criteria to determine whether a PW matches the characteristics required to allow PTT calculation. To validate whether the '7Step PW-Filter' eliminates only and all unsuitable PWs, its elimination results were compared to the outcome of manual elimination of unsuitable PWs. The '7Step PW-Filter' had a sensitivity of 96.3% and a specificity of 99.3%. The overall accuracy of the '7Step PW-Filter' for detection of unsuitable PWs was 99.3%. Compared to manual elimination, using the '7Step PW-Filter' reduces PW elimination times from hours to minutes and helps to increase the validity, reliability and reproducibility of PTT data.

Pulse Arrival Time Based Cuff-Less and 24-H Wearable Blood Pressure Monitoring and its Diagnostic Value in Hypertension

Ambulatory blood pressure monitoring (ABPM) has become an essential tool in the diagnosis and management of hypertension. Current standard ABPM devices use an oscillometric cuff-based method which can cause physical discomfort to the patients with repeated inflations and deflations, especially during nighttime leading to sleep disturbance. The ability to measure ambulatory BP accurately and comfortably without a cuff would be attractive. This study validated the accuracy of a cuff-less approach for ABPM using pulse arrival time (PAT) measurements on both healthy and hypertensive subjects for potential use in hypertensive management, which is the first of its kind. The wearable cuff-less device was evaluated against a standard cuff-based device on 24 subjects of which 15 have known hypertension. BP measurements were taken from each subject over a 24-h period by the cuff-less and cuff-based devices every 15 to 30 minutes during daily activities. Mean BP of each subject during daytime, nighttime and over 24-h were calculated. Agreement between mean nighttime systolic BP (SBP) and diastolic (DBP) measured by the two devices evaluated using Bland-Altman plot were -1.4 ± 6.6 and 0.4 ± 6.7 mmHg, respectively. Receiver operator characteristics (ROC) statistics was used to assess the diagnostic accuracy of the cuff-less approach in the detection of BP above the hypertension threshold during nighttime (>120/70 mmHg). The area under ROC curves were 0.975/0.79 for nighttime. The results suggest that PAT-based approach is accurate and promising for ABPM without the issue of sleep disturbances associated with cuff-based devices.

Unobtrusive sensing and wearable devices for health informatics

The aging population, prevalence of chronic diseases, and outbreaks of infectious diseases are some of the major challenges of our present-day society. To address these unmet healthcare needs, especially for the early prediction and treatment of major diseases, health informatics, which deals with the acquisition, transmission, processing, storage, retrieval, and use of health information, has emerged as an active area of interdisciplinary research. In particular, acquisition of health-related information by unobtrusive sensing and wearable technologies is considered as a cornerstone in health informatics. Sensors can be weaved or integrated into clothing, accessories, and the living environment, such that health information can be acquired seamlessly and pervasively in daily living. Sensors can even be designed as stick-on electronic tattoos or directly printed onto human skin to enable long-term health monitoring. This paper aims to provide an overview of four emerging unobtrusive and wearable technologies, which are essential to the realization of pervasive health information acquisition, including: 1) unobtrusive sensing methods, 2) smart textile technology, 3) flexible-stretchable-printable electronics, and 4) sensor fusion, and then to identify some future directions of research.

Cuffless blood pressure estimation using only photoplethysmography based on cardiovascular parameters

This study provides cuffless blood pressure estimation. In general, blood pressure changes when the subject's condition changes, and it is important to estimate it continuously and noninvasively. In many previous studies, they used PTT (Pulse Transmission Time) for estimating. However, PTT needs both electrocardiogram and photoplethysmography to be measured. Our method needs only a finger type photoplethysmographic sensor for estimating. We use the features obtained only from photoplethysmography for estimating, instead of PTT obtained from electrocardiogram. The features used are accelerated plethysmography's waveform, Heart Rate Variability and the rate of photoplethysmography's drift. Blood pressure is modeled as the product of CO (Cardiac Output) and TPR (Total Peripheral Resistance) in general. Then, we estimated blood pressure as the product of eCO and eTPR estimated by proposed photoplethysmography's features with Stepwise multiple regression analysis. Therefore, our proposed method provides not only blood pressure, but also CO and TPR. As of result, we estimated blood pressure based on eCO and eTPR, and we obtained r = 0.71. Therefore, we could obtain the result closer to Finometer in accuracy.