Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition

Development of a wearable belt with integrated sensors for measuring multiple physiological parameters related to heart failure

Heart failure is a chronic disease, the symptoms of which occur due to a lack of cardiac output. It can be better managed with continuous and real time monitoring. Some efforts have been made in the past for the management of heart failure. Most of these efforts were based on a single parameter for example thoracic impedance or heart rate alone. Herein, we report a wearable device that can provide monitoring of multiple physiological parameters related to heart failure. It is based on the sensing of multiple parameters simultaneously including thoracic impedance, heart rate, electrocardiogram and motion activity. These parameters are measured using different sensors which are embedded in a wearable belt for their continuous and real time monitoring. The healthcare wearable device has been tested in different conditions including sitting, standing, laying, and walking. Results demonstrate that the reported wearable device keeps track of the aforementioned parameters in all conditions.

Respiratory rate monitoring in healthy volunteers by central photoplethysmography compared to capnography

Monitoring of respiration is a central task in clinical medicine, crucial to patient safety. Despite the uncontroversial role of altered respiratory frequency as an important sign of impending or manifest deterioration, reliable measurement methods are mostly lacking outside of intensive care units and operating theaters. Photoplethysmography targeting the central blood circulation in the sternum could offer accurate and inexpensive monitoring of respiration. Changes in blood flow related to the different parts of the respiratory cycle are used to identify the respiratory pattern. The aim of this observational study was to compare photoplethysmography at the sternum to standard capnography in healthy volunteers. Bland Altman analysis showed good agreement (bias -0.21, SD 1.6, 95% limits of agreement -3.4 to 2.9) in respiratory rate values. Photoplethysmography provided high-quality measurements of respiratory rate comparable to capnographic measurements. This suggests that photoplethysmography may become a precise, cost-effective alternative for respiratory monitoring.

Agreement between respiratory rate measurement using a combined electrocardiographic derived method versus impedance from pneumography

BACKGROUND

Impedance pneumography (IP) is the current device-driven method used to measure respiratory rate (RR) in hospitalized patients. However, RR alarms are common and contribute to alarm fatigue. While RR derived from electrocardiographic (ECG) waveforms hold promise, they have not been compared to the IP method.

PURPOSE

Study examined the agreement between the IP and combined-ECG derived (EDR) for normal RR (≥12 or ≤20 breaths/minute [bpm]); low RR (≤5 bpm); and high RR (≥30 bpm).

METHODOLOGY

One-hundred intensive care unit patients were included by RR group: (1) normal RR (n = 50; 25 low RR and 25 high RR); (2) low RR (n = 50); and (3) high RR (n = 50). Bland-Altman analysis was used to evaluate agreement.

RESULTS

For normal RR, a significant bias difference of -1.00 + 2.11 (95% CI -1.60 to -0.40) and 95% limit of agreement (LOA) of -5.13 to 3.13 was found. For low RR, a significant bias difference of -16.54 + 6.02 (95% CI: -18.25 to -14.83) and a 95% LOA of -28.33 to - 4.75 was found. For high RR, a significant bias difference of 17.94 + 12.01 (95% CI: 14.53 to 21.35) and 95% LOA of -5.60 to 41.48 was found.

CONCLUSION

Combined-EDR method had good agreement with the IP method for normal RR. However, for the low RR, combined-EDR was consistently higher than the IP method and almost always lower for the high RR, which could reduce the number of RR alarms. However, replication in a larger sample including confirmation with visual assessment is warranted.

Sensors for Context-Aware Smart Healthcare: A Security Perspective

The advances in the miniaturisation of electronic devices and the deployment of cheaper and faster data networks have propelled environments augmented with contextual and real-time information, such as smart homes and smart cities. These context-aware environments have opened the door to numerous opportunities for providing added-value, accurate and personalised services to citizens. In particular, smart healthcare, regarded as the natural evolution of electronic health and mobile health, contributes to enhance medical services and people's welfare, while shortening waiting times and decreasing healthcare expenditure. However, the large number, variety and complexity of devices and systems involved in smart health systems involve a number of challenging considerations to be considered, particularly from security and privacy perspectives. To this aim, this article provides a thorough technical review on the deployment of secure smart health services, ranging from the very collection of sensors data (either related to the medical conditions of individuals or to their immediate context), the transmission of these data through wireless communication networks, to the final storage and analysis of such information in the appropriate health information systems. As a result, we provide practitioners with a comprehensive overview of the existing vulnerabilities and solutions in the technical side of smart healthcare.

Respiration Monitoring via Forcecardiography Sensors

In the last few decades, a number of wearable systems for respiration monitoring that help to significantly reduce patients’ discomfort and improve the reliability of measurements have been presented. A recent research trend in biosignal acquisition is focusing on the development of monolithic sensors for monitoring multiple vital signs, which could improve the simultaneous recording of different physiological data. This study presents a performance analysis of respiration monitoring performed via forcecardiography (FCG) sensors, as compared to ECG-derived respiration (EDR) and electroresistive respiration band (ERB), which was assumed as the reference. FCG is a novel technique that records the cardiac-induced vibrations of the chest wall via specific force sensors, which provide seismocardiogram-like information, along with a novel component that seems to be related to the ventricular volume variations. Simultaneous acquisitions were obtained from seven healthy subjects at rest, during both quiet breathing and forced respiration at higher and lower rates. The raw FCG sensor signals featured a large, low-frequency, respiratory component (R-FCG), in addition to the common FCG signal. Statistical analyses of R-FCG, EDR and ERB signals showed that FCG sensors ensure a more sensitive and precise detection of respiratory acts than EDR (sensitivity: 100% vs. 95.8%, positive predictive value: 98.9% vs. 92.5%), as well as a superior accuracy and precision in interbreath interval measurement (linear regression slopes and intercepts: 0.99, 0.026 s (R² = 0.98) vs. 0.98, 0.11 s (R² = 0.88), Bland–Altman limits of agreement: ±0.61 s vs. ±1.5 s). This study represents a first proof of concept for the simultaneous recording of respiration signals and forcecardiograms with a single, local, small, unobtrusive, cheap sensor. This would extend the scope of FCG to monitoring multiple vital signs, as well as to the analysis of cardiorespiratory interactions, also paving the way for the continuous, long-term monitoring of patients with heart and pulmonary diseases.

A Wrist-worn Respiration Monitoring Device using Bio-Impedance

In the US alone, 22 million individuals suffer from obstructive sleep apnea (OSA), with 80% of the cases symptoms undiagnosed. Hence, there is an unmet need to continuously and unobtrusively monitor respiration and detect possible occurrences of apnea. Recent advancements in wearable biomedical technology can enable the capture of the periodicity of the heart pressure pulse from a wrist-worn device. In this paper, we propose a bio-impedance (Bio-Z)-based respiration monitoring system. We establish close contact with the skin using gold e-tattoos with a 35 mm by 5 mm active sensing area. We extracted the respiration from the wrist Bio-Z signal leveraging three different techniques and showed that we can detect the start of each respiration beat with an average root mean square error (RMSE) less than 13% and mean error of 0.3% over five subjects.

ImpediBands: Body Coupled Bio-Impedance Patches for Physiological Sensing Proof of Concept

Continuous and robust monitoring of physiological signals is essential in improving the diagnosis and management of cardiovascular and respiratory diseases. The state-of-the-art systems for monitoring vital signs such as heart rate, heart rate variability, respiration rate, and other hemodynamic and respiratory parameters use often bulky and obtrusive systems or depend on wearables with limited sensing methods based on repetitive properties of the signals rather than the morphology. Moreover, multiple devices and modalities are typically needed for capturing various vital signs simultaneously. In this paper, we introduce ImpediBands: small-sized distributed smart bio-impedance (Bio-Z) patches, where the communication between the patches is established through the human body, eliminating the need for electrical wires that would create a common potential point between sensors. We use ImpediBands to collect instantaneous measurements from multiple locations over the chest at the same time. We propose a blind source separation (BSS) technique based on the second-order blind identification (SOBI) followed by signal reconstruction to extract heart and lung activities from the Bio-Z signals. Using the separated source signals, we demonstrate the performance of our system via providing strong confidence in the estimation of heart and respiration rates with low RMSE (HR_RMSE = 0.579 beats per minute, RR_RMSE = 0.285 breaths per minute), and high correlation coefficients (r_HR = 0.948, r_RR = 0.921).

Application of Modern Multi-Sensor Holter in Diagnosis and Treatment

Modern Holter devices are very trendy tools used in medicine, research, or sport. They monitor a variety of human physiological or pathophysiological signals. Nowadays, Holter devices have been developing very fast. New innovative products come to the market every day. They have become smaller, smarter, cheaper, have ultra-low power consumption, do not limit everyday life, and allow comfortable measurements of humans to be accomplished in a familiar and natural environment, without extreme fear from doctors. People can be informed about their health and 24/7 monitoring can sometimes easily detect specific diseases, which are normally passed during routine ambulance operation. However, there is a problem with the reliability, quality, and quantity of the collected data. In normal life, there may be a loss of signal recording, abnormal growth of artifacts, etc. At this point, there is a need for multiple sensors capturing single variables in parallel by different sensing methods to complement these methods and diminish the level of artifacts. We can also sense multiple different signals that are complementary and give us a coherent picture. In this article, we describe actual interesting multi-sensor principles on the grounds of our own long-year experiences and many experiments.

Human Vital Signs Detection Methods and Potential Using Radars: A Review

Continuous monitoring of vital signs, such as respiration and heartbeat, plays a crucial role in early detection and even prediction of conditions that may affect the wellbeing of the patient. Sensing vital signs can be categorized into: contact-based techniques and contactless based techniques. Conventional clinical methods of detecting these vital signs require the use of contact sensors, which may not be practical for long duration monitoring and less convenient for repeatable measurements. On the other hand, wireless vital signs detection using radars has the distinct advantage of not requiring the attachment of electrodes to the subject's body and hence not constraining the movement of the person and eliminating the possibility of skin irritation. In addition, it removes the need for wires and limitation of access to patients, especially for children and the elderly. This paper presents a thorough review on the traditional methods of monitoring cardio-pulmonary rates as well as the potential of replacing these systems with radar-based techniques. The paper also highlights the challenges that radar-based vital signs monitoring methods need to overcome to gain acceptance in the healthcare field. A proof-of-concept of a radar-based vital sign detection system is presented together with promising measurement results.

Measurement of Chest Physiological Signals using Wirelessly Coupled Bio-Impedance Patches

Continuous monitoring of respiration and heart pressure pulse waves generated by lung and heart movements is essential in the diagnosis and management of cardiovascular and lung diseases. Traditional methods in measuring these physiological signals are not convenient for long-term monitoring during daily activities and sleeping due to their use of long wires and/or face masks, and leading to patients having to spend long duration in clinics while undergoing supervised monitoring. In this paper, we present a new method to measure global chest physiological signals using small-sized smart band-age like patches placed at different locations of the chest. The introduced patches communicate with each other using human body and detect small variations in the bio-Impedance (Bio-Z) depending on the mechanical heart and lung movements, where one patch injects an AC current from one side of the chest and several Bio-Z sensors measure the voltage difference across different locations of the chest. In order to prevent usage of long wires and increase convenience for wearable applications, electrical connection between current injection and Bio-Z sensing patches are eliminated. Independent component analysis is used to separate sources of physiological observations and improve accuracy of the system. We show that the presented system can successfully detect respiration rate and heart rate with an average error of 4.86% (less than 1 breath per minute) and 1.86% (less than 2 beats per minute) respectively tested on 6 healthy subjects over 6 minutes of data collection for each subject.

Sleep apnea assessment using declination duration-based global metrics from unobtrusive fiber optic sensors

OBJECTIVE

Sufficient sleep helps to restore the immune, nervous and cardiovascular systems, but is sometimes disturbed by sleep apnea (SA). The early diagnosis of sleep apnea is beneficial for the prevention of diseases. Polysomnography (PSG) recording provides comprehensive data for such assessment, but is not suitable for use at home due to discomfort during measurement and the difficulty of identification. This study proposes an unobtrusive measurement process by placing fiber optic sensors (FOSs) in a pillow (head-neck) or a bed mattress (thoracic-dorsal).

APPROACH

We test two approaches: drop degrees from the baseline to validate the capability of catching respiratory drops, and linear regression models based on a new global measure, the percentage of the total duration of respiratory declination (PTDRD), to estimate the hand-scored apnea/hypopnea index (AHI).

MAIN RESULTS

Based on data recorded from 63 adults, the drop degrees derived from respiratory signals exhibited statistical differences among central sleep apnea (CSA), obstructive sleep apnea (OSA) and normal breathing. The regression models based on the PTDRDs derived from head-neck FOS and thoracic-dorsal FOS also achieved good agreement with manually scored AHIs in Bland-Altman plots as well as oronasal airflow and thoracic wall movement.

SIGNIFICANCE

The aforementioned performance demonstrates the capability of the FOS measurement and the efficacy of the PTDRD metrics for SA assessment.

An Ultrasound-Based Biomedical System for Continuous Cardiopulmonary Monitoring: A Single Sensor for Multiple Information

Biomedical wearable sensors enable long-term monitoring applications and provide instantaneous diagnostic capabilities. Physiological monitoring can help in both the diagnosis and the ongoing treatment of a vast number of cardiovascular and pulmonary diseases such as hypertension, dysrhythmia, and asthma. In this paper, we present a system capable of monitoring several vital signals and physiological variables that determine the cardiopulmonary activity status. We explore direct measurements of multiple vital parameters with only one sensor and without special constraints. The system employs a PZT-4 piezo transducer stimulated by a suitable analog front end. The system both generates pulsed ultrasound waves at 1 MHz and amplifies reflected echoes to track internal organ motions, mainly that of the heart apex. According to the respiratory motion of the heart, the proposed system provides respiratory and heart cycles information. Promising results were obtained from six subjects with an average accuracy of 96.7% in heartbeats per minute measurement, referenced to a commercial photoplethysmography sensor. It also exhibits 94.5% sensitivity and 94.0% specificity in respiration detection compared to a spirometer signal as a reference.

Estimation of respiratory variables from thoracoabdominal breathing distance: a review of different techniques and calibration methods

The precise measurement of respiratory variables, such as tidal volume, minute ventilation, and respiratory rate, is necessary to monitor respiratory status, overcome several diseases, improve patient health conditions and reduce health care costs. This measurement has conventionally been performed by breathing into a mouthpiece connected to a flow rate measuring device. However, a mouthpiece can be uncomfortable for the subject and is difficult to use for long-term monitoring. Other noninvasive systems and devices have been developed that do not require a mouthpiece to quantitatively measure respiratory variables. These techniques are based on measuring size changes of the rib cage (RC) and abdomen (ABD), as lung volume is known to be a function of these variables. Among these systems, we distinguish respiratory inductive plethysmography (RIP), respiratory magnetometer plethysmography (RMP), and optoelectronic plethysmography devices. However, these devices should be previously calibrated for the correct evaluation of respiratory variables. The most popular calibration methods are isovolume manoeuvre calibration (ISOCAL), qualitative diagnostic calibration (QDC), multiple linear regression (MLR) and artificial neural networks (ANNs). The aim of this review is first to present how thoracoabdominal breathing distances can be used to estimate respiratory variables and second to present the different techniques and calibration methods used for this purpose.

Contact-Based Methods for Measuring Respiratory Rate

There is an ever-growing demand for measuring respiratory variables during a variety of applications, including monitoring in clinical and occupational settings, and during sporting activities and exercise. Special attention is devoted to the monitoring of respiratory rate because it is a vital sign, which responds to a variety of stressors. There are different methods for measuring respiratory rate, which can be classed as contact-based or contactless. The present paper provides an overview of the currently available contact-based methods for measuring respiratory rate. For these methods, the sensing element (or part of the instrument containing it) is attached to the subject's body. Methods based upon the recording of respiratory airflow, sounds, air temperature, air humidity, air components, chest wall movements, and modulation of the cardiac activity are presented. Working principles, metrological characteristics, and applications in the respiratory monitoring field are presented to explore potential development and applicability for each method.

Ultrasound Sensors for Diaphragm Motion Tracking: An Application in Non-Invasive Respiratory Monitoring

This paper introduces a novel respiratory detection system based on diaphragm wall motion tracking using an embedded ultrasound sensory system. We assess the utility and accuracy of this method in evaluating the function of the diaphragm and its contribution to respiratory workload. The developed system is able to monitor the diaphragm wall activity when the sensor is placed in the zone of apposition (ZOA). This system allows for direct measurements with only one ultrasound PZT5 piezo transducer. The system generates pulsed ultrasound waves at 2.2 MHz and amplifies reflected echoes. An added benefit of this system is that due to its design, the respiratory signal is less subject to motion artefacts. Promising results were obtained from six subjects performing six tests per subject with an average respiration detection sensitivity and specificity of 84% and 93%, respectively. Measurements were compared to a gold standard commercial spirometer. In this study, we also compared our measurements to other conventional methods such as inertial and photoplethysmography (PPG) sensors.