Biosensors for cardiac biomarkers detection: a review

The cardiovascular disease (CVD) is considered as a major threat to global health. Therefore, there is a growing demand for a range of portable, rapid and low cost biosensing devices for the detection of CVD. Biosensors can play an important role in the early diagnosis of CVD without having to rely on hospital visits where expensive and time-consuming laboratory tests are recommended. Over the last decade, many biosensors have been developed to detect a wide range of cardiac marker to reduce the costs for healthcare. One of the major challenges is to find a way of predicting the risk that an individual can suffer from CVD. There has been considerable interest in finding diagnostic and prognostic biomarkers that can be detected in blood and predict CVD risk. Of these, C-reactive protein (CRP) is the best known biomarker followed by cardiac troponin I or T (cTnI/T), myoglobin, lipoprotein-associated phospholipase A(2), interlukin-6 (IL-6), interlukin-1 (IL-1), low-density lipoprotein (LDL), myeloperoxidase (MPO) and tumor necrosis factor alpha (TNF-α) has been used to predict cardiovascular events. This review provides an overview of the available biosensor platforms for the detection of various CVD markers and considerations of future prospects for the technology are addressed

Fog Computing in Medical Internet-of-Things: Architecture, Implementation, and Applications

In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting one's health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex, 2) The data, when communicated, are vulnerable to security and privacy issues, 3) The communication of the continuously collected data is not only costly but also energy hungry, 4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks. This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a service-oriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection.Comment: 29 pages, 30 figures, 5 tables. Keywords: Big Data, Body Area Network, Body Sensor Network, Edge Computing, Fog Computing, Medical Cyberphysical Systems, Medical Internet-of-Things, Telecare, Tele-treatment, Wearable Devices, Chapter in Handbook of Large-Scale Distributed Computing in Smart Healthcare (2017), Springe

Magnetic resonance imaging compatible non-invasive fibre-optic sensors based on the Bragg gratings and interferometers in the application of monitoring heart and respiration rate of the human body: A comparative study

The publication presents a comparative study of two fibre-optic sensors in the application of heart rate (HR) and respiratory rate (RR) monitoring of the human body. After consultation with clinical practitioners, two types of non-invasive measuring and analysis systems based on fibre Bragg grating (FBG) and fibre-optic interferometer (FOI) have been designed and assembled. These systems use probes (both patent pending) that have been encapsulated in the bio-compatible polydimethylsiloxane (PMDS). The main advantage of PDMS is that it is electrically non-conductive and, as well as optical fibres, has low permeability. The initial verification measurement of the system designed was performed on four subjects in a harsh magnetic resonance (MR) environment under the supervision of a senior radiology assistant. A follow-up comparative study was conducted, upon a consent of twenty volunteers, in a laboratory environment with a minimum motion load and discussed with a head doctor of the Radiodiagnostic Institute. The goal of the laboratory study was to perform measurements that would simulate as closely as possible the environment of harsh MR or the environment of long-term health care facilities, hospitals and clinics. Conventional HR and RR measurement systems based on ECG measurements and changes in the thoracic circumference were used as references. The data acquired was compared by the objective Bland-Altman (B-A) method and discussed with practitioners. The results obtained confirmed the functionality of the designed probes, both in the case of RR and HR measurements (for both types of B-A, more than 95% of the values lie within the +/- 1.96 SD range), while demonstrating higher accuracy of the interferometric probe (in case of the RR determination, 95.66% for the FOI probe and 95.53% for the FBG probe, in case of the HR determination, 96.22% for the FOI probe and 95.23% for the FBG probe).Web of Science1811art. no. 371

Monitoring Cardiovascular Physiology using Bio-compatible AlN Piezoelectric Skin Sensors

Arterial pulse waves contain a wealth of parameters indicative of cardiovascular disease. As such, monitoring them continuously and unobtrusively can provide health professionals with a steady stream of cardiovascular health indices, allowing for the development of efficient, individualized treatments and early cardiovascular disease diagnosis solutions. Blood pulsations in superficial arteries cause skin surface deformations, typically undetectable to the human eye; therefore, Microelectromechanical systems (MEMS) can be used to measure these deformations and thus create unobtrusive pulse wave monitoring devices. Miniaturized ultrathin and flexible Aluminium Nitride (AlN) piezoelectric MEMS are highly sensitive to minute mechanical deformations, making them suitable for detecting the skin deformations caused by cardiac events and consequently providing multiple biomarkers useful for monitoring cardiovascular health and assessing cardiovascular disease risk. Conventional wearable continuous pulse wave monitoring solutions are typically large and based on technologies limiting their versatility. Therefore, we propose the adoption of 29.5 μm-thick biocompatible, skin-conforming devices on piezoelectric AlN to create versatile, multipurpose arterial pulse wave monitoring devices. In our initial trials, the devices are placed over arteries along the wrist (radial artery), neck (carotid artery), and suprasternal notch (on the chest wall and close to the ascending aorta). We also leverage the mechano-acoustic properties of the device to detect heart muscle vibrations corresponding to heart sounds S1 and S2 from the suprasternal notch measurement site. Finally, we characterize the piezoelectric device outputs observed with the cardiac cycle events using synchronized electrocardiogram (ECG) reference signals and provide information on heart rate, breathing rate, and heart sounds. The extracted parameters strongly agree with reference values as illustrated by minimum Pearson correlation coefficients (r) of 0.81 for pulse rate and 0.95 for breathing rate

The utility of eccentricity index as a measure of right ventricular function in a lung resection cohort

Context: Right ventricular (RV) dysfunction occurs after lung resection and is associated with postoperative morbidity. Noninvasive evaluation of the RV is challenging, particularly in the postoperative period. A reliable measure of RV function would have value in this population. Aims: This study compares eccentricity index (EI) obtained by transthoracic echocardiography (TTE) with cardiovascular magnetic resonance (CMR) determined measures of RV function in a lung resection cohort. CMR is the reference method for noninvasive assessment of RV function. Design and Setting: Prospective observational cohort study at a single tertiary hospital. Materials and Methods: Twenty-eight patients scheduled for elective lung resection underwent contemporaneous TTE and CMR imaging preoperatively, on postoperative day (POD) 2 and at 2-month. Systolic and diastolic EI was measured offline from anonymized and randomized TTE and CMR images. Statistical Analysis: Bland–Altman analysis was performed to determine agreement between EITTE and EICMR. Changes over time and comparison with CMR determined RV ejection fraction (RVEFCMR) was assessed. Results: Bland–Altman analysis showed a negligible mean difference between EITTE and EICMR, but limits of agreement were wide (SD 0.24 and 0.28). There were no significant changes in EITTE and EICMR over time (P > 0.35). We found no association between EITTE with RVEFCMR at all-time points (P > 0.22). Systolic and diastolic EICMR on POD 2 demonstrated moderate association with RVEFCMR (r = −0.54 and r = −0.59, P ≤ 0.01). At 2-month, only diastolic EICMR correlated with RVEFCMR (r = −0.43, P = 0.03). There were no meaningful associations between EITTE and EICMR with TTE-derived RV systolic pressure (P > 0.31). Conclusions: TTE determined EI is not useful as a noninvasive method of assessing RV function following lung resection

Heart rate variability predicts older adults’ avoidance of negativity

Objectives The ability to produce situation-appropriate cognitive and emotional responses is dependent on autonomic nervous system (ANS) functionality. Heart rate variability (HRV) is an index of ANS functionality, and resting HRV levels have been associated with cognitive control and inhibitory capacity in young adults, particularly when faced with emotional information. As older adults’ greater preference for positive and avoidance of negative stimuli (positivity effect) is thought to be dependent on cognitive control, we hypothesized that HRV could predict positivity-effect magnitude in older adults. Method We measured resting-level HRV and gaze preference for happy and angry (relative to neutral) faces in 63 young and 62 older adults. Results Whereas young adults showed no consistent preference for happy or angry faces, older adults showed the expected positivity effect, which predominantly manifested as negativity avoidance rather than positivity preference. Crucially, older but not young adults showed an association between HRV and gaze preference, with higher levels of HRV being specifically associated with stronger negativity avoidance. Discussion This is the first study to demonstrate a link between older adults’ ANS functionality and their avoidance of negative information. Increasing the efficiency of the cardiovascular system might selectively improve older adults’ ability to disregard negative influences

Acoustic sensing as a novel approach for cardiovascular monitoring at the wrist

Cardiovascular diseases are the number one cause of deaths globally. An increased cardiovascular risk can be detected by a regular monitoring of the vital signs including the heart rate, the heart rate variability (HRV) and the blood pressure. For a user to undergo continuous vital sign monitoring, wearable systems prove to be very useful as the device can be integrated into the user's lifestyle without affecting the daily activities. However, the main challenge associated with the monitoring of these cardiovascular parameters is the requirement of different sensing mechanisms at different measurement sites. There is not a single wearable device that can provide sufficient physiological information to track the vital signs from a single site on the body. This thesis proposes a novel concept of using acoustic sensing over the radial artery to extract cardiac parameters for vital sign monitoring. A wearable system consisting of a microphone is designed to allow the detection of the heart sounds together with the pulse wave, an attribute not possible with existing wrist-based sensing methods. Methods: The acoustic signals recorded from the radial artery are a continuous reflection of the instantaneous cardiac activity. These signals are studied and characterised using different algorithms to extract cardiovascular parameters. The validity of the proposed principle is firstly demonstrated using a novel algorithm to extract the heart rate from these signals. The algorithm utilises the power spectral analysis of the acoustic pulse signal to detect the S1 sounds and additionally, the K-means method to remove motion artifacts for an accurate heartbeat detection. The HRV in the short-term acoustic recordings is found by extracting the S1 events using the relative information between the short- and long-term energies of the signal. The S1 events are localised using three different characteristic points and the best representation is found by comparing the instantaneous heart rate profiles. The possibility of measuring the blood pressure using the wearable device is shown by recording the acoustic signal under the influence of external pressure applied on the arterial branch. The temporal and spectral characteristics of the acoustic signal are utilised to extract the feature signals and obtain a relationship with the systolic blood pressure (SBP) and diastolic blood pressure (DBP) respectively. Results: This thesis proposes three different algorithms to find the heart rate, the HRV and the SBP/ DBP readings from the acoustic signals recorded at the wrist. The results obtained by each algorithm are as follows: 1. The heart rate algorithm is validated on a dataset consisting of 12 subjects with a data length of 6 hours. The results demonstrate an accuracy of 98.78%, mean absolute error of 0.28 bpm, limits of agreement between -1.68 and 1.69 bpm, and a correlation coefficient of 0.998 with reference to a state-of-the-art PPG-based commercial device. A high statistical agreement between the heart rate obtained from the acoustic signal and the photoplethysmography (PPG) signal is observed. 2. The HRV algorithm is validated on the short-term acoustic signals of 5-minutes duration recorded from each of the 12 subjects. A comparison is established with the simultaneously recorded electrocardiography (ECG) and PPG signals respectively. The instantaneous heart rate for all the subjects combined together achieves an accuracy of 98.50% and 98.96% with respect to the ECG and PPG signals respectively. The results for the time-domain and frequency-domain HRV parameters also demonstrate high statistical agreement with the ECG and PPG signals respectively. 3. The algorithm proposed for the SBP/ DBP determination is validated on 104 acoustic signals recorded from 40 adult subjects. The experimental outputs when compared with the reference arm- and wrist-based monitors produce a mean error of less than 2 mmHg and a standard deviation of error around 6 mmHg. Based on these results, this thesis shows the potential of this new sensing modality to be used as an alternative, or to complement existing methods, for the continuous monitoring of heart rate and HRV, and spot measurement of the blood pressure at the wrist.Open Acces