Wearable devices for continuous monitoring of arterial pulse waves have the potential to improve the diagnosis, prognosis, and management of cardiovascular diseases. These pulse wave signals are often affected by the contact pressure between the wearable device and the skin, limiting the accuracy and reliability of hemodynamic parameter quantification. Here, a continuous hemodynamic monitoring device that enables the simultaneous recording of dual‐channel bioimpedance and quantification of pulse wave velocity (PWV) and blood pressure (BP) is reported. The investigations demonstrate the effect of contact pressure on bioimpedance and PWV. The pulsatile bioimpedance magnitude reached its maximum when the contact pressure approximated the mean arterial pressure of the subject. PWV is employed to continuously quantify BP while maintaining comfortable contact pressure for prolonged wear. The mean absolute error and standard deviation of the error compared to the reference value are determined to be 0.1 ± 3.3 mmHg for systolic BP, 1.3 ± 3.7 mmHg for diastolic BP, and −0.4 ± 3.0 mmHg for mean arterial pressure when measurements are conducted in the lying down position. This research demonstrates the potential of wearable dual‐bioimpedance sensors with contact pressure guidance for reliable and continuous hemodynamic monitoring.

Robust sensing is one of the main challenges for wearable physiological monitoring because of the high dependency on the placement of electrodes on the body, retaining suitable contact between electrodes and skin, and the effect of motion artifacts. In this paper, we present a wrist-worn strap that includes a 2-D array of 48 miniature electrodes covering the bottom side of the wrist with good contact with the skin. Good skin contact directly impacts the sensing robustness. The array provides local measurements between adjacent electrodes that span the whole bottom side of the wrist with an area of 6.25×4.60 cm for robust sensing. The array allows for the automatic selection of the correct electrodes at the right location regardless of changes in the device placement on the wrist. In addition, using a large number of electrodes over a large area on the wrist ensures continuous contact of some electrodes with the skin during motion since all of the electrodes will not lose contact with the skin at the same time. We measured the electrode-skin impedance of the fabricated electrodes versus frequency and compared to other types of electrodes. We demonstrated good contact between all electrodes of the array and the skin by measuring electrode-skin impedance less than 10 kΩ at 16 kHz for all locations on the wrist strap. We also conducted measurements of impedance while the wearer was bending the wrist to validate the continuous contact of at least a subset of electrodes with the skin during such movements.

Continuous monitoring of arterial blood pressure is clinically important for diagnosing and managing cardiovascular diseases. Soft electronic devices with skin‐like properties show promise in various applications, including the human‐machine interface, the Internet of Things, and health monitoring. Herein, the use of add‐on soft electronic interfaces addresses the connection challenges between soft electrodes and rigid data acquisition circuitry for bioimpedance monitoring of cardiac signals, including heart rate and cuffless blood pressure is reported. Nanocomposite films in add‐on electrodes provide robust electrical and mechanical contact with the skin and the rigid circuitry. Bioimpedance sensors composed of add‐on electrodes offer continuous blood pressure monitoring with high accuracy. Specifically, the bioimpedance collected with add‐on nanocomposite electrodes shows a signal‐to‐noise ratio of 37.0 dB, higher than the ratio of 25.9 dB obtained with standard silver/silver chloride (Ag/AgCl) gel electrodes. Although the sample set is low, the continuously measured systolic and diastolic blood pressure offer accuracy of −2.0 ± 6.3 mmHg and −4.3 ± 3.9 mmHg, respectively, confirming the grade A performance based on the IEEE standard. These results show promise in bioimpedance measurements with add‐on soft electrodes for cuffless blood pressure monitoring.

Blood pressure is a critical risk factor for cardiovascular diseases (CVDs), yet most adults do not monitor it frequently enough to prevent serious complications. This is in part because the traditional cuff-based method is inconvenient, uncomfortable, and does not allow for continuous monitoring. To address these constraints, we developed a unique multi-modal wearable device and used a random forest regression (RFR) algorithm that resulted in a model capable of accurate cuffless blood pressure prediction. This multi-modal device features two photoplethysmography (PPG) sensors and two bioimpedance (BioZ) sensors to measure pulse wave propagation along the radial artery on the wrist. The redundancy in the design enhances prediction accuracy. To validate the device, a novel human subject study protocol was also developed that allows an individual's blood pressure to rise safely and repeatably by more than 40 mmHg (systolic pressure) from baseline measurements. In this study, using multiple pulsatile waveforms from the PPG and BioZ sensors as inputs into the machine learning prediction algorithm, showed that the model had higher accuracy than models using a single sensor. Specifically, the training, validation, and leaving one subject out of data sets all showed mean absolute errors of less than 3.3 mmHg for both systolic and diastolic blood pressures (BPs). While results from this test were promising, a subject-wise evaluation showed variability depending on how well an individual's BP distribution matched the training set. These findings demonstrate the potential for a universal model for cuffless BP estimation, with further validation needed in more diverse populations. Thus, the accompaniment of the RFR model with the multi-modal wearable device offers the potential for robust and continuous blood pressure monitoring, providing a unique and practical solution for long-term cardiovascular health management.

Cardiovascular disease (CVD) is the leading cause of global mortality, with hypertension affecting over one billion people. Current noninvasive blood pressure (BP) systems, like cuffs, suffer from discomfort and placement errors and lack continuous monitoring. Wearable solutions promise improvements, but technologies like photoplethysmography (PPG) and bioimpedance (BIOZ) face usability and clinical accuracy limitations. PPG is sensitive to skin tone and body mass index (BMI) variability, while BIOZ struggles with electrode contact and reusability. We present a novel, strain gauge-based wearable BP device that directly quantifies pressure via a dual transducer system, compensating for tissue deformation and external forces to enable continuous, accurate BP measurement. The reusable, energy-efficient, and compact design suits long-term daily use. A novel leg press protocol across 10 subjects (systolic: 71.04–241.42 mmHg, diastolic: 53.46–123.84 mmHg) validated its performance under dynamic conditions, achieving mean absolute errors of 2.45 ± 3.99 mmHg (systolic) and 1.59 ± 2.08 mmHg (diastolic). The device showed enhanced robustness compared to the Finapres, with less motion-induced noise. This technology significantly advances current methods by delivering continuous, real-time BP monitoring without reliance on electrodes, independent of skin tone, while maintaining a high accuracy and user comfort.

Many commercial wearable sensor systems typically rely on a single continuous cardiorespiratory sensing modality, photoplethysmography (PPG), which suffers from inherent biases (i.e., differences in skin tone) and noise (e.g., motion and pressure artifacts). In this research, we present a wearable device that provides robust estimates of cardiorespiratory variables by combining three physiological signals from the upper arm: multiwavelength PPG, single-sided electrocardiography (SS-ECG), and bioimpedance plethysmography (BioZ), along with an inertial measurement unit (IMU) providing 3-axis accelerometry and gyroscope information. We evaluated the multimodal device on 16 subjects by its ability to estimate heart rate (HR) and breathing rate (BR) in the presence of various static and dynamic noise sources (e.g., skin tone and motion). We proposed a hierarchical approach that considers the subject’s skin tone and signal quality to select the optimal sensing modality for estimating HR and BR. Our results indicate that, when estimating HR, there is a trade-off between accuracy and robustness, with SS-ECG providing the highest accuracy (low mean absolute error; MAE) but low reliability (higher rates of sensor failure), and PPG/BioZ having lower accuracy but higher reliability. When estimating BR, we find that fusing estimates from multiple modalities via ensemble bagged tree regression outperforms single-modality estimates. These results indicate that multimodal approaches to cardiorespiratory monitoring can overcome the accuracy–robustness trade-off that occurs when using single-modality approaches.