Chest Vibration Research Articles

Estimation of Speech Features Using a Wearable Inertial Sensor

Speech features have been investigated as novel digital biomarkers for many psychiatric and neurocognitive diseases. Microphones are the most used devices for speech recording but inevitably suffering from several disadvantages such as privacy leakage and environmental noises, limiting their clinical applications particularly for long-term ambulatory monitoring. The aim of the present study is therefore to explore the feasibility of extracting speech features from the acceleration recorded on the sternum. Ten healthy subjects volunteered in our study. Two speech tasks, i.e., repeating one sentence 20 times and reading 20 different sentences, were performed by each subject, with each task repeated 8 times under different speech rate and loudness. Voice signals and speech-caused chest vibrations were simultaneously recorded by a microphone and an accelerometer placed on the sternum. 42 acoustic features and 6 time-related prosodic features were extracted from both signals using a standard toolbox, and then compared by a linear fit and correlation analysis. Good agreement between the acceleration features and microphone features is observed in all 6 time-related prosodic features for both tasks, but only in 19 and 17 acoustic features for task 1 and 2, respectively, with most of them loudness- or pitch-related. Our results suggest the sternum acceleration to track time-related speech prosody, loudness, and pitch very well, demonstrating the feasibility of deriving digital biomarkers from the acceleration signal for diseases strongly related to time-related prosodic and loudness features.

Variation of Seismocardiogram-Derived Cardiac Time Intervals and Heart Rate Variability Metrics Across the Sternum

Abstract Cardiac time intervals (CTIs) are vital indicators of cardiac health and can be noninvasively assessed using a combination of electrocardiography (ECG) and seismocardiography (SCG), a method of capturing cardiac-induced chest vibrations via accelerometers. SCG signals can be measured from different chest locations. However, more investigations are needed to evaluate the impact of sensor placement on SCG-derived cardiac parameters. This study investigates the effect of accelerometer placement along the sternum on SCG-derived CTI estimations and heart rate variability (HRV) parameters. A semi-automated algorithm was developed to detect SCG fiducial points and seven CTIs from thirteen healthy individuals. Comparative analysis with manually selected peaks and gold-standard ECG was conducted to assess fiducial point detection accuracy. Results indicate the highest recall and precision in aortic valve opening (0.84–1.00 and 0.96–1.00, respectively) and mitral valve closure (0.77–1.00 and 0.93–1.00, respectively) detection. Aortic valve closure (0.43–1.00 and 0.61–1.00, respectively) and mitral valve opening (0.64–1.00 and 0.91–1.00, respectively) detection, although slightly less accurate due to signal intensity variations, demonstrated overall effectiveness compared to manually selected peaks. Furthermore, SCG-derived heart rates showed a high correlation coefficient (r > 0.9) with the gold-standard ECG heart rates. Single-factor ANOVA revealed significant differences (p < 0.05) in SCG-derived CTI estimations based on sensor locations on the sternum, highlighting the importance of sensor placement for accurate assessments.

Cardiac Time Intervals under Motion Using Bimodal Chest E-Tattoos and Multistage Processing.

We present a thin, soft, and chest conformable bimodal sensor, known as the chest e-tattoo, coupled with an advanced signal processing framework to accurately identify various cardiac events, and thereby extract cardiac time intervals even during body motion. We built a wireless electronic tattoo that features synchronous electrocardiography (ECG) and seismocardiography (SCG). The SCG measures chest vibrations due to heartbeat, providing information on cardiovascular health that is complementary to the ECG. However, the efficacy of the SCG is compromised by motion-induced artifacts. The slim and stretchy design of the e-tattoo allows it to be strategically placed near the xiphoid process, facilitating high-quality monitoring of the ECG and SCG for increased signal quality. Nine participants were measured during walking and cycling. We propose a multistage signal processing framework, integrating an adaptive Normalized Least Mean Squares (NLMS) filter, ensemble averaging, and Empirical Mode Decomposition (EMD), together named the FAD framework, to accurately extract cardiac time intervals (CTIs).

Smartphone-Derived Seismocardiography: Robust Approach for Accurate Cardiac Energy Assessment in Patients with Various Cardiovascular Conditions.

Seismocardiography (SCG), a method for measuring heart-induced chest vibrations, is gaining attention as a non-invasive, accessible, and cost-effective approach for cardiac pathologies, diagnosis, and monitoring. This study explores the integration of SCG acquired through smartphone technology by assessing the accuracy of metrics derived from smartphone recordings and their consistency when performed by patients. Therefore, we assessed smartphone-derived SCG's reliability in computing median kinetic energy parameters per record in 220 patients with various cardiovascular conditions. The study involved three key procedures: (1) simultaneous measurements of a validated hardware device and a commercial smartphone; (2) consecutive smartphone recordings performed by both clinicians and patients; (3) patients' self-conducted home recordings over three months. Our findings indicate a moderate-to-high reliability of smartphone-acquired SCG metrics compared to those obtained from a validated device, with intraclass correlation (ICC) > 0.77. The reliability of patient-acquired SCG metrics was high (ICC > 0.83). Within the cohort, 138 patients had smartphones that met the compatibility criteria for the study, with an observed at-home compliance rate of 41.4%. This research validates the potential of smartphone-derived SCG acquisition in providing repeatable SCG metrics in telemedicine, thus laying a foundation for future studies to enhance the precision of at-home cardiac data acquisition.

BIOWISH: Biometric Recognition Using Wearable Inertial Sensors Detecting Heart Activity

Wearable devices have been recently proposed to perform biometric recognition, leveraging on the uniqueness of the collectable physiological traits to generate discriminative identifiers. Most of the studies conducted on this topic have exploited heart-related signals, sensing the cardiac activity either through electrical measurements using electrocardiography, or with optical recordings employing photoplethysmography. In this paper we instead propose a system performing BIOmetric recognition using Wearable Inertial Sensors detecting Heart activity (BIOWISH). In more detail, we investigate the feasibility of exploiting mechanical measurements obtained through seismocardiography and gyrocardiography to verify the identity of a subject. Several feature extractors and classifiers, including deep learning techniques relying on siamese training, are employed to derive distinctive characteristics from the considered signals, so as to differentiate between legitimate users and impostors. A multi-session database, comprising acquisitions taken from subjects performing different activities, is employed to perform experimental tests. The obtained results testify that identifiers derived from measurements of chest vibrations, collected by wearable inertial sensors, could be employed to guarantee high recognition performance, even when considering short-time recordings. Explainability methods have been also employed to derive some insights about the aspects relevant to perform predictions for both people and activity recognition tasks.

Effect of mechanical chest vibration during chest physiotherapy on ventilator parameters and oxygen saturation in mechanically ventilated patients

Effect of mechanical chest vibration during chest physiotherapy on ventilator parameters and oxygen saturation in mechanically ventilated patients

Effect of Mechanical Chest Vibration during Chest Physiotherapy on Ventilator Parameters and Oxygen Saturation in Mechanically Ventilated Patients

Effect of Mechanical Chest Vibration during Chest Physiotherapy on Ventilator Parameters and Oxygen Saturation in Mechanically Ventilated Patients

Vibroacoustic therapy in the treatment of patients with COVID-19 complicated by respiratory failure: a pilot randomized controlled trial.

Coronavirus infection is a dangerous airborne disease that can lead to serious lung damage. Data on the effectiveness of low-frequency chest vibrations in the treatment of lung diseases are available; however, not so many of them exist. Vibroacoustic pulmonary therapy is a component of physiotherapy that improves lung perfusion and drainage without requiring active patient participation. This study aimed to increase statistical efficiency through maximizing the relevant information obtained from the clinical data. Calculating the sample size to determine the power of subsequent studies was also necessary. A pilot randomized parallel trial involving 60 patients was conducted. The patients were divided into two equal groups, where they received sessions of vibroacoustic pulmonary therapy using the "VibroLung" device in two modes "acute respiratory distress syndrome (ARDS)" and "Pneumonia," with identical treatment. The patients were > 18 years old with detected COVID-19 by PCR and grade 2 and 3 lung lesions detected by computer tomography (CT). Blood sampling was performed in the morning at the same time before and after the hardware massage to determine PaO2, PaCO2, and P/F. As a result of the test, the following data were obtained: on the first day in the group using the "ARDS" mode, PaO2 indicators averaged 65, CI 95% [58.6-73.2] and on average 77.5, CI 95% [69.8-85.2], "before" and "after," respectively, which indicates improved oxygenation after the procedure. However, in the second group with the "Pneumonia" mode after its use, PaCO2 was higher after the session, on average 48.7, CI 95% [40.8-56.6], whereas before that, the following indicators had, on average 43.6, CI 95% [37.2-50]. Thus, the data obtained yielded ambiguous results, which are the basis for further study in future randomized controlled trials. As the treatment of coronavirus infection has no etiological treatment, even small shifts in the therapy of this category of patients can be significant. ClinicalTrials.gov, identifier NCT05143372.

НОВЫЙ ПРИБОР «СИСТЕМА ОЧИСТКИ ДЫХАТЕЛЬНЫХ ПУТЕЙ YANG KUN YK-800» В КИНЕЗИТЕРАПИИ ДЕТЕЙ С ХРОНИЧЕСКИМИ ЗАБОЛЕВАНИЯМИ ЛЕГКИХ

Cystic fibrosis (CF) and primary ciliary dyskinesia (PCD) in children are both accompanied by copious amounts of infected sputum. Kinesitherapy (KT) eliminates mucostasis by providing bronchial drainage. KT methods are being constantly improved. The purpose of this research was to determine the effectiveness and safety of the new vest airway clearance system (ACS) chest vibration therapy machine model YK800 by Zhengzhou Yangkun Medical Instrument Co., Ltd. (Zhengzhou, China) in children with CF and PCD. The ACS consists of a compressor and a vest and creates high-frequency oscillation of the chest promoting drainage of problematic parts of the respiratory tract, small- and medium-caliber bronchi. Materials and methods used: in a study based on the National Medical Research Center for Children’s Health (Moscow, Russia) the KT included 5 sessions with the Yangkun YK800 in 15 patients aged 5 to 17 y/o: 8 with CF and 7 with PCD. Objective criteria: measurement of external respiratory function (ERF) and saturation, monitoring of chest excursion, and the 6-minute walk test. Subjective criteria: complaints, well-being, comfort. Results: objective criteria - improved ERF indicators in % (FVC p=0.004; r=0.829; FEV1 p=0.023; r=0.973; FEF25% p=0.018; r=0.840; FEF50% p=0.016; r=0.827; FEF75% p=0.015; r=0.867), especially high-speed indicators (FEF25%, FEF50%, FEF75%) that indicate the cleansing of mucus in the medium and small respiratory tracts; saturation improved (p=0.020; r=0.548); chest excursion increased (p=0.002; r=0.779). According to the 6-minute walk test, there was a significant increase in the distance traveled (p=0.000; r=0.535), 13 (86.6%) patients at the end of the course rated it as easier. Subjective criteria - 80% of patients noted sen-sations of productive coughing, easier expectoration of sputum: improvement in general condi-tion - 15, reduction in fatigue - 12, increased physical activity - 12, easier expectoration of phlegm - 13, reduction in episodes of paroxysmal cough - 13. Comfort in the use of the vest was rated at 4.4 points, noting mild vibration. Conclusion: the Yangkun YK800 vest airway clearance system as part of the KT has shown its effectiveness and safety in children with CF and PCD.

FisioLung: A System for Training and Monitoring of Respiratory Physiotherapy Sessions

The chest vibration technique is considered a good alternative for bronchial hygiene. However, this technique is difficult to perform because it needs a chest on exact range frequency. We built a tool to analyze its execution that helped professionals to learn him. It is possible to monitor the evolution of the patient with a monitoring system based on the record of sessions and observe the application of the vibration techniques as well. This work proposed the developed system integrating hardware and software named Fisiolung. The architecture has a glove with an accelerometer to capture the vibration data and a NodeMCU ESP32 board used to process them. The Flutter mobile application receives the collected data and manages the session. The system can record physiotherapy sessions by registering the patient’s and the professional’s data, anamnesis information, techniques used, and analysis of the manual chest vibration technique stored. On the analysis screen, it is possible to note the graphs of peak frequency versus time and the average of peak frequency versus time, as well as session information such as analysis time, anamnesis data, and applicable techniques. The researchers conducted some experiments using the system, and the initial feedback indicated that physiotherapists could adopt the system and benefit from utilizing the Vibrocompression technique.

Experimental demonstration of noncontact vital-sign measurement using pulse radar.

Recently, monitoring the vital-sign with the noncontact method is a popular technology. In this work, we present a fully pulse radar system including front-end sensing and back-end data processing. A series of ultra-wide band sensing pulses is generated and radiated to detect the subject's chest vibration which in turn obtains the required vital-sign signals. An artificial plywood with 3 centimeter thickness is placed between a transmitting/receiving antenna of the radar and subject to demonstrate the characteristic of noncontact sensing. The firmware and digital signal processing are also presented in this paper to optimize physiological data quality. The experimental results show that the continuous heart rate and breathing rate can be monitored by this customized system radar module. A fully customized ultra-wide band radar for vital-sign application is presented. The radar system plan with wall parameter is also incorporated into the design consideration to meet the FCC requirement and SNR.

Safety use of high frequency oscillatory ventilation in transport of newborn infants affected by severe respiratory failure: preliminary data in central Tuscany

BackgroundNeonatal Emergency Transport Services play a fundamental role in neonatal care. Stabilization before transport of newborns suffering from severe respiratory failure is often a challenging problem and some critically ill infants may benefit from High Frequency Oscillatory Ventilation (HFOV) as rescue treatment. In these cases, transition to conventional ventilation for transport may cause a deterioration in clinical conditions. HFOV during neonatal transport has been only exceptionally used, due to technical difficulties. Since May 2018, a new neonatal transport unit is available at the Neonatal Protected Transport Service of the Meyer University Hospital in Florence, equipped with a pulmonary ventilator capable of delivering HFOV. Therefore, we conducted an analysis on patients transferred in HFOV to Neonatal Intensive Care Unit (NICU), in order to evaluate the safety and feasibility of its use during neonatal transport.MethodsA retrospective analysis was performed reviewing medical records of the neonates transported by Meyer Children Hospital’s Neonatal Transport Service between May 2018 and December 2020, and newborns treated with HFOV during ground neonatal transport were identified. Safety was assessed by the comparison of vital signs, hemogas-analysis values and pulmonary ventilator parameters, at the time of departure and upon arrival in NICU. The dose of inotropes, the main respiratory complications (air leak, dislocation or obstruction of the endotracheal tube, loss of chest vibrations) and the number of deaths and transfer failures were recorded.ResultsOut of the approximate 400 newborns transported during the analysis period, 9 were transported in HFOV. We did not find any statistically significant difference in vital parameters, hemogas-analytical values and pulmonary ventilator settings recorded before and after neonatal transport of the nine patients’ parameters (p > 0,05). No patient required additional inotropes during transport. No transport-related deaths or significant complications occurred during transport.ConclusionsThe interest of our report is in the possibility of using HFOV during inter-hospital neonatal transfer. As far as our experience has shown, HFOV appears to be safe for the transportation of newborns with severe respiratory failure. Nevertheless, further larger, prospective and multicentre studies are needed to better evaluate the safety and efficacy of HFOV during neonatal transport.

Highly sensitive and stretchable piezoelectric strain sensor enabled wearable devices for real-time monitoring of respiratory and heartbeat simultaneously

The World Health Organization has declared COVID-19 a pandemic. The demand for devices or systems to diagnose and track COVID-19 infections noninvasively not only in hospitals but also in home settings has led to increased interest in consumer-grade wearables. A common symptom of COVID-19 is dyspnea, which may manifest as an increase in respiratory and heart rates. In this paper, a novel piezoelectric strain sensor is presented for real-time monitoring of respiratory and heartbeat signals. A highly sensitive and stretchable piezoelectric strain sensor is fabricated using a piezoelectric film with a serpentine layout. The thickness of the patterned PVDF flexible piezoelectric strain sensor is only 168 μm, and the voltage sensitivity reaches 0.97 mV/μɛ. The effective modulus is 13.5 MPa, which allows the device to fit to the skin and detect the small strain exhibited by the human body. Chest vibrations are captured by the piezoelectric sensor, which produces an electrical output voltage signal conformally mapped with respiratory–cardiac activities. The separate heart activity and respiratory signals are extracted from the mixed respiratory–cardiac signal by an empirical mode decomposition data processing algorithm. By detecting vital signals such as respiratory and heart rates, the proposed device can aid early diagnosis and monitoring of respiratory diseases such as COVID-19.

Discrete Wavelet Transforms-Based Analysis of Accelerometer Signals for Continuous Human Cardiac Monitoring

Measuring cardiac activity from the chest using an accelerometer is commonly referred to as seismocardiography. Unfortunately, it cannot provide clinically valid data because it is easily corrupted by motion artefacts. This paper proposes two methods to improve peak detection from noisy seismocardiography data. They rely on discrete wavelet transform analysis using either biorthogonal 3.9 or reverse biorthogonal 3.9. The first method involves slicing chest vibrations for each cardiac activity, and then detecting the peak location, whereas the other method aims at detecting the peak directly from chest vibrations without segmentation. Performance evaluations were conducted on signals recorded from small children and adults based on missing and additional peaks. Both algorithms showed a low error rate (15.4% and 2.1% for children/infants and adults, respectively) for signals obtained in resting state. The average error for sitting and breathing tasks (adults only) was 14.4%. In summary, the first algorithm proved more promising for further exploration.

Measurement of micro-harmonic vibration frequency from the modulated self-mixed interferometric signal using dynamic time warping method

The vibration frequency is one of the key factors that contains vital information about the subjects/machines and offers major analytical support. The contactless measurement of vibration frequency is the crucial requirement of many industrial, scientific, and biomedical applications like predictive maintenance, non-destructive testing, and reverse engineering, chest vibration, etc. The paper presents a self-mixed optical feedback interferometry (SM-OFI) sensor to measure the vibration frequency of the micro-harmonic vibrating surface. The method employs a Dynamic Time Warping algorithm (DTW) to compute the Euclidian distance between the locally generated reference signal and the SM interferometric signal obtained from a vibrating target. The method is tested experimentally on a customized SM-OFI emitting a wavelength of 650 nm under weak feedback conditions. The proposed method was able to measure the unknown frequency with 98% accuracy in all sets of experiments. The method also exhibits an R-squared value of 0.99 with a relative error of less than unity. The comprehensive analysis of the experimental results concludes that the proposed method provides an accurate and precise vibration frequency measurement scheme for the low bandwidth range. This low bandwidth range measurement promises a non-contact measurement in industries and biomedical applications during the COVID-19 scenario.

High-Accuracy, Unsupervised Annotation of Seismocardiogram Traces for Heart Rate Monitoring

This article presents an unsupervised, automated procedure for the analysis of Seismocardiogram (SCG) signals. SCG is a measure of chest vibrations, induced by the mechanical activity of the heart, which allows extracting relevant parameters, including heart rate (HR) and HR variability (HRV). An initial self-calibration is performed, solely based on the SCG traces, yielding a suitable heartbeat template (personalized for each subject). Then, beat detection and timing annotation are performed in two steps: at first, candidate beats are identified and validated, by means of suitably defined detection signals; then, precise timing annotation is achieved by best aligning such candidate beats to the previously extracted template. The algorithm has been validated on two separate data sets, featuring different acquisition setups: the first one is the publicly available Combined measurement of ECG, Breathing and Seismocardiogram (CEBS) database, reporting SCG signals from the subjects lying in supine position, whereas the second one was acquired using a custom setup, involving the sitting subjects. Results show good sensitivity and precision scores (98.5% and 98.6% for the CEBS database, and 99.1% and 97.9% for the Custom one, respectively). In addition, comparison with electrocardiogram (ECG) gold-standard is given, showing good agreement between the beat-to-beat intervals computed from SCG and the ECG gold-standard: on average, R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> scores of 99.3% and 98.4% are achieved on the CEBS and Custom data sets, respectively. Furthermore, a low rms error is achieved on the CEBS and Custom data sets, amounting to 4.6 and 6.2 ms, respectively (i.e., 2.3 T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> and 3.1 T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> , where T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> is the sampling period): such results are well compared with related literature. Validation on two different data sets indicates the robustness of the proposed methodology.

Continuous-cycle technology of rehabilitation of patients with chronic obstructive pulmonary disease on an outpatient basis

Of this study is to substantiate the effectiveness of continuous-cycle technology of rehabilitation of patients with chronic obstructive pulmonary disease (COPD) on an outpatient basis. 140 patients with moderate to severe (stage II-III) COPD were examined: 82% with chronic bronchitis phenotype and 18% - with emphysema phenotype. 44% of patients had frequent exacerbations. Patients were admitted to outpatient rehabilitation after stages I and II because of the exacerbation of the disease. 2 comparable groups were formed: the primary group included 68 patients who were engaged in active physical rehabilitation according to a continuous-cycle technique for 10-12 months; the comparison group consisted of 72 patients receiving only basic drug therapy. Continuous-cycle technique included: regular exercise therapy, cycling and procedures that improve tolerance to them (hardware chest vibration, chlorpromazine electrophoresis), oxygen cocktail, general ultraviolet radiation in the unfavorable period of the year. Diagnostics of early signs of an exacerbation of the disease and prophylactic prescription of physiotherapeutic procedures were carried out. During the year of observation during treatment, only 4 cases failed to prevent full exacerbation of the disease. During the year, in the patients of the primary group, in contrast to the comparison group, there was a significant improvement in the clinical signs of the disease, an increase in VC, an improvement in bronchial patency, an increase in physical performance and exercise tolerance, and a decrease in the activity of systemic inflammation. A year later, we registered an improvement in the course of the disease n 70% of patients of the primary group, and only stabilization of the process - in 82% of the comparison group. Frequency of exacerbations in the primary group decreased 5.1 times, which was 3.9 times more significant than in the comparison group.

A Computational Framework for Data Fusion in MEMS-Based Cardiac and Respiratory Gating.

Dual cardiac and respiratory gating is a well-known technique for motion compensation in nuclear medicine imaging. In this study, we present a new data fusion framework for dual cardiac and respiratory gating based on multidimensional microelectromechanical (MEMS) motion sensors. Our approach aims at robust estimation of the chest vibrations, that is, high-frequency precordial vibrations and low-frequency respiratory movements for prospective gating in positron emission tomography (PET), computed tomography (CT), and radiotherapy. Our sensing modality in the context of this paper is a single dual sensor unit, including accelerometer and gyroscope sensors to measure chest movements in three different orientations. Since accelerometer- and gyroscope-derived respiration signals represent the inclination of the chest, they are similar in morphology and have the same units. Therefore, we use principal component analysis (PCA) to combine them into a single signal. In contrast to this, the accelerometer- and gyroscope-derived cardiac signals correspond to the translational and rotational motions of the chest, and have different waveform characteristics and units. To combine these signals, we use independent component analysis (ICA) in order to obtain the underlying cardiac motion. From this cardiac motion signal, we obtain the systolic and diastolic phases of cardiac cycles by using an adaptive multi-scale peak detector and a short-time autocorrelation function. Three groups of subjects, including healthy controls (n = 7), healthy volunteers (n = 12), and patients with a history of coronary artery disease (n = 19) were studied to establish a quantitative framework for assessing the performance of the presented work in prospective imaging applications. The results of this investigation showed a fairly strong positive correlation (average r = 0.73 to 0.87) between the MEMS-derived (including corresponding PCA fusion) respiration curves and the reference optical camera and respiration belt sensors. Additionally, the mean time offset of MEMS-driven triggers from camera-driven triggers was 0.23 to 0.3 ± 0.15 to 0.17 s. For each cardiac cycle, the feature of the MEMS signals indicating a systolic time interval was identified, and its relation to the total cardiac cycle length was also reported. The findings of this study suggest that the combination of chest angular velocity and accelerations using ICA and PCA can help to develop a robust dual cardiac and respiratory gating solution using only MEMS sensors. Therefore, the methods presented in this paper should help improve predictions of the cardiac and respiratory quiescent phases, particularly with the clinical patients. This study lays the groundwork for future research into clinical PET/CT imaging based on dual inertial sensors.

A Chest-Laminated Ultrathin and Stretchable E-Tattoo for the Measurement of Electrocardiogram, Seismocardiogram, and Cardiac Time Intervals.

Seismocardiography (SCG) is a measure of chest vibration associated with heartbeats. While skin soft electronic tattoos (e‐tattoos) have been widely reported for electrocardiogram (ECG) sensing, wearable SCG sensors are still based on either rigid accelerometers or non‐stretchable piezoelectric membranes. This work reports an ultrathin and stretchable SCG sensing e‐tattoo based on the filamentary serpentine mesh of 28‐µm‐thick piezoelectric polymer, polyvinylidene fluoride (PVDF). 3D digital image correlation (DIC) is used to map chest vibration to identify the best location to mount the e‐tattoo and to investigate the effects of substrate stiffness. As piezoelectric sensors easily suffer from motion artifacts, motion artifacts are effectively reduced by performing subtraction between a pair of identical SCG tattoos placed adjacent to each other. Integrating the soft SCG sensor with a pair of soft gold electrodes on a single e‐tattoo platform forms a soft electro‐mechano‐acoustic cardiovascular (EMAC) sensing tattoo, which can perform synchronous ECG and SCG measurements and extract various cardiac time intervals including systolic time interval (STI). Using the EMAC tattoo, strong correlations between STI and the systolic/diastolic blood pressures, are found, which may provide a simple way to estimate blood pressure continuously and noninvasively using one chest‐mounted e‐tattoo.

BioEssence: A Wearable Olfactory Display that Monitors Cardio-respiratory Information to Support Mental Wellbeing.

This work introduces a novel wearable olfactory display that provides just-in-time release of scents based on the physiological state of the wearer. The device can release up to three scents and passively captures subtle chest vibrations associated with the beating of the heart and respiration through clothes.BioEssenceiscontrolledviaacustom-madesmartphone app that allows the creation of physiological rules to trigger different scents (e.g., when the heart rate is above 80 beats per minute, release lavender scent). The device is wireless and lightweight, and it is designed to be used during daily life, clipped on clothes around the sternum area or used as a necklace. We provide a description of the design and implementation of the prototype and potential use cases in the context of mental wellbeing.