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Brandwood BM, Naik GR, Gunawardana U, Gargiulo GD. Combined Cardiac and Respiratory Monitoring from a Single Signal: A Case Study Employing the Fantasia Database. SENSORS (BASEL, SWITZERLAND) 2023; 23:7401. [PMID: 37687857 PMCID: PMC10490584 DOI: 10.3390/s23177401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 08/16/2023] [Accepted: 08/22/2023] [Indexed: 09/10/2023]
Abstract
This study proposes a novel method for obtaining the electrocardiogram (ECG) derived respiration (EDR) from a single lead ECG and respiration-derived cardiogram (RDC) from a respiratory stretch sensor. The research aims to reconstruct the respiration waveform, determine the respiration rate from ECG QRS heartbeat complexes data, locate heartbeats, and calculate a heart rate (HR) using the respiration signal. The accuracy of both methods will be evaluated by comparing located QRS complexes and inspiration maxima to reference positions. The findings of this study will ultimately contribute to the development of new, more accurate, and efficient methods for identifying heartbeats in respiratory signals, leading to better diagnosis and management of cardiovascular diseases, particularly during sleep where respiration monitoring is paramount to detect apnoea and other respiratory dysfunctions linked to a decreased life quality and known cause of cardiovascular diseases. Additionally, this work could potentially assist in determining the feasibility of using simple, no-contact wearable devices for obtaining simultaneous cardiology and respiratory data from a single device.
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Affiliation(s)
- Benjamin M. Brandwood
- School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia;
| | - Ganesh R. Naik
- Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, SA 5042, Australia;
| | - Upul Gunawardana
- School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia;
| | - Gaetano D. Gargiulo
- School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia;
- The MARCS Institute, Westmead, NSW 2145, Australia
- Translational Research Health Institute, Westmead, NSW 2145, Australia
- The Ingam Institute for Medical Research, Liverpool, NSW 2170, Australia
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Naik GR, Breen PP, Jayarathna T, Tong BK, Eckert DJ, Gargiulo GD. Morphic Sensors for Respiratory Parameters Estimation: Validation against Overnight Polysomnography. BIOSENSORS 2023; 13:703. [PMID: 37504102 PMCID: PMC10377422 DOI: 10.3390/bios13070703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 06/19/2023] [Accepted: 06/26/2023] [Indexed: 07/29/2023]
Abstract
Effective monitoring of respiratory disturbances during sleep requires a sensor capable of accurately capturing chest movements or airflow displacement. Gold-standard monitoring of sleep and breathing through polysomnography achieves this task through dedicated chest/abdomen bands, thermistors, and nasal flow sensors, and more detailed physiology, evaluations via a nasal mask, pneumotachograph, and airway pressure sensors. However, these measurement approaches can be invasive and time-consuming to perform and analyze. This work compares the performance of a non-invasive wearable stretchable morphic sensor, which does not require direct skin contact, embedded in a t-shirt worn by 32 volunteer participants (26 males, 6 females) with sleep-disordered breathing who performed a detailed, overnight in-laboratory sleep study. Direct comparison of computed respiratory parameters from morphic sensors versus traditional polysomnography had approximately 95% (95 ± 0.7) accuracy. These findings confirm that novel wearable morphic sensors provide a viable alternative to non-invasively and simultaneously capture respiratory rate and chest and abdominal motions.
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Affiliation(s)
- Ganesh R Naik
- Adelaide Institute for Sleep Health (Flinders Health and Medical Research Institute: Sleep Health), College of Medicine and Public Health, Flinders University, Bedford Park, SA 5042, Australia
- College of Science and Engineering, Flinders University, Bedford Park, SA 5042, Australia
| | - Paul P Breen
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
| | - Titus Jayarathna
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
| | - Benjamin K Tong
- Neuroscience Research Australia, Randwick, NSW 2031, Australia
- Sleep Research Group, Charles Perkins Centre, School of Medicine, University of Sydney, Camperdown, NSW 2006, Australia
| | - Danny J Eckert
- Adelaide Institute for Sleep Health (Flinders Health and Medical Research Institute: Sleep Health), College of Medicine and Public Health, Flinders University, Bedford Park, SA 5042, Australia
- Neuroscience Research Australia, Randwick, NSW 2031, Australia
| | - Gaetano D Gargiulo
- The MARCS Institute, Western Sydney University, Westmead, NSW 2145, Australia
- School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia
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A BLE-Connected Piezoresistive and Inertial Chest Band for Remote Monitoring of the Respiratory Activity by an Android Application: Hardware Design and Software Optimization. FUTURE INTERNET 2022. [DOI: 10.3390/fi14060183] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Breathing is essential for human life. Issues related to respiration can be an indicator of problems related to the cardiorespiratory system; thus, accurate breathing monitoring is fundamental for establishing the patient’s condition. This paper presents a ready-to-use and discreet chest band for monitoring the respiratory parameters based on the piezoresistive transduction mechanism. In detail, it relies on a strain sensor realized with a pressure-sensitive fabric (EeonTex LTT-SLPA-20K) for monitoring the chest movements induced by respiration. In addition, the band includes an Inertial Measurement Unit (IMU), which is used to remove the motion artefacts from the acquired signal, thereby improving the measurement reliability. Moreover, the band comprises a low-power conditioning and acquisition section that processes the signal from sensors, providing a reliable measurement of the respiration rate (RR), in addition to other breathing parameters, such as inhalation (TI) and exhalation (TE) times, inhalation-to-exhalation ratio (IER), and flow rate (V). The device wirelessly transmits the extracted parameters to a host device, where a custom mobile application displays them. Different test campaigns were carried out to evaluate the performance of the designed chest band in measuring the RR, by comparing the measurements provided by the chest band with those obtained by breath count. In detail, six users, of different genders, ages, and physical constitutions, were involved in the tests. The obtained results demonstrated the effectiveness of the proposed approach in detecting the RR. The achieved performance was in line with that of other RR monitoring systems based on piezoresistive textiles, but which use more powerful acquisition systems or have low wearability. In particular, the inertia-assisted piezoresistive chest band obtained a Pearson correlation coefficient with respect to the measurements based on breath count of 0.96 when the user was seated. Finally, Bland–Altman analysis demonstrated that the developed system obtained 0.68 Breaths Per Minute (BrPM) mean difference (MD), and Limits of Agreement (LoAs) of +3.20 and −1.75 BrPM when the user was seated.
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Wearable Bluetooth Triage Healthcare Monitoring System. SENSORS 2021; 21:s21227586. [PMID: 34833659 PMCID: PMC8619240 DOI: 10.3390/s21227586] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 11/09/2021] [Accepted: 11/11/2021] [Indexed: 11/17/2022]
Abstract
Triage is the first interaction between a patient and a nurse/paramedic. This assessment, usually performed at Emergency departments, is a highly dynamic process and there are international grading systems that according to the patient condition initiate the patient journey. Triage requires an initial rapid assessment followed by routine checks of the patients’ vitals, including respiratory rate, temperature, and pulse rate. Ideally, these checks should be performed continuously and remotely to reduce the workload on triage nurses; optimizing tools and monitoring systems can be introduced and include a wearable patient monitoring system that is not at the expense of the patient’s comfort and can be remotely monitored through wireless connectivity. In this study, we assessed the suitability of a small ceramic piezoelectric disk submerged in a skin-safe silicone dome that enhances contact with skin, to detect wirelessly both respiration and cardiac events at several positions on the human body. For the purposes of this evaluation, we fitted the sensor with a respiratory belt as well as a single lead ECG, all acquired simultaneously. To complete Triage parameter collection, we also included a medical-grade contact thermometer. Performances of cardiac and respiratory events detection were assessed. The instantaneous heart and respiratory rates provided by the proposed sensor, the ECG and the respiratory belt were compared via statistical analyses. In all considered sensor positions, very high performances were achieved for the detection of both cardiac and respiratory events, except for the wrist, which provided lower performances for respiratory rates. These promising yet preliminary results suggest the proposed wireless sensor could be used as a wearable, hands-free monitoring device for triage assessment within emergency departments. Further tests are foreseen to assess sensor performances in real operating environments.
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Assessing the Tidal Volume through Wearables: A Scoping Review. SENSORS 2021; 21:s21124124. [PMID: 34208468 PMCID: PMC8233785 DOI: 10.3390/s21124124] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 05/28/2021] [Accepted: 06/11/2021] [Indexed: 01/10/2023]
Abstract
The assessment of respiratory activity based on wearable devices is becoming an area of growing interest due to the wide range of available sensors. Accordingly, this scoping review aims to identify research evidence supporting the use of wearable devices to monitor the tidal volume during both daily activities and clinical settings. A screening of the literature (Pubmed, Scopus, and Web of Science) was carried out in December 2020 to collect studies: i. comparing one or more methodological approaches for the assessment of tidal volume with the outcome of a state-of-the-art measurement device (i.e., spirometry or optoelectronic plethysmography); ii. dealing with technological solutions designed to be exploited in wearable devices. From the initial 1031 documents, only 36 citations met the eligibility criteria. These studies highlighted that the tidal volume can be estimated by using different technologies ranging from IMUs to strain sensors (e.g., resistive, capacitive, inductive, electromagnetic, and optical) or acoustic sensors. Noticeably, the relative volumetric error of these solutions during quasi-static tasks (e.g., resting and sitting) is typically ≥10% but it deteriorates during dynamic motor tasks (e.g., walking). As such, additional efforts are required to improve the performance of these devices and to identify possible applications based on their accuracy and reliability.
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Respiration Monitoring via Forcecardiography Sensors. SENSORS 2021; 21:s21123996. [PMID: 34207899 PMCID: PMC8228286 DOI: 10.3390/s21123996] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 06/04/2021] [Accepted: 06/07/2021] [Indexed: 12/26/2022]
Abstract
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.
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El Arja S, Jayarathna T, Naik G, Breen P, Gargiulo G. Characterisation of Morphic Sensors for Body Volume and Shape Applications. SENSORS (BASEL, SWITZERLAND) 2019; 20:E90. [PMID: 31877893 PMCID: PMC6983190 DOI: 10.3390/s20010090] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 12/16/2019] [Accepted: 12/18/2019] [Indexed: 02/01/2023]
Abstract
Stretchable conductive materials are originally conceived as radio frequency (RF) and electromagnetic interference (EMI) shielding materials, and, under stretch, they generally function as distributed strain-gauges. These commercially available conductive elastomers have found their space in low power health monitoring systems, for example, to monitor respiratory and cardiac functions. Conductive elastomers do not behave linearly due to material constraints; hence, when used as a sensor, a full characterisation to identify ideal operating ranges are required. In this paper, we studied how the continuous stretch cycles affected the material electrical and physical properties in different embodiment impressed by bodily volume change. We simulated the stretch associated with breathing using a bespoke stress rig to ensure reproducibility of results. The stretch rig is capable of providing constant sinusoidal waves in the physiological ranges of extension and frequency. The material performances is evaluated assessing the total harmonic distortion (THD), signal-to-noise ratio (SNR), correlation coefficient, peak to peak (P-P) amplitude, accuracy, repeatability, hysteresis, delay, and washability. The results showed that, among the three controlled variables, stretch length, stretch frequency and fabric width, the most significant factor to the signal quality is the stretch length. The ideal working region is within 2% of the original length. The material cut in strips of > 3 show more reliable to handle a variety of stretch parameter without losing its internal characteristics and electrical properties.
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Affiliation(s)
- Sami El Arja
- School of Computing, Engineering and Mathematics, Western Sydney University, Penrith, NSW 2751, Australia;
| | - Titus Jayarathna
- MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Milperra, NSW 2560, Australia; (G.N.); (P.B.)
| | - Ganesh Naik
- MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Milperra, NSW 2560, Australia; (G.N.); (P.B.)
| | - Paul Breen
- MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Milperra, NSW 2560, Australia; (G.N.); (P.B.)
- Translational Health Research Institute, Western Sydney University, Campbelltown, NSW 2560, Australia
| | - Gaetano Gargiulo
- School of Computing, Engineering and Mathematics, Western Sydney University, Penrith, NSW 2751, Australia;
- MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Milperra, NSW 2560, Australia; (G.N.); (P.B.)
- Translational Health Research Institute, Western Sydney University, Campbelltown, NSW 2560, Australia
- School of Psychiatry and Ingham Institute of Applied Medical Research, University of New South Wales, Liverpool, NSW 2052, Australia
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Naik GR, Gargiulo GD, Serrador JM, Breen PP. Groundtruth: A Matlab GUI for Artifact and Feature Identification in Physiological Signals. Front Physiol 2019; 10:850. [PMID: 31481893 PMCID: PMC6710362 DOI: 10.3389/fphys.2019.00850] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 06/20/2019] [Indexed: 12/03/2022] Open
Abstract
Groundtruth is a Matlab Graphical User Interface (GUI) developed for the identification of key features and artifacts within physiological signals. The ultimate aim of this GUI is to provide a simple means of assessing the performance of new sensors. Secondary, to this is providing a means of providing marked data, enabling assessment of automated artifact rejection and feature identification algorithms. With the emergence of new wearable sensor technologies, there is an unmet need for convenient assessment of device performance, and a faster means of assessing new algorithms. The proposed GUI allows interactive marking of artifact regions as well as simultaneous interactive identification of key features, e.g., respiration peaks in respiration signals, R-peaks in Electrocardiography signals, etc. In this paper, we present the base structure of the system, together with an example of its use for two simultaneously worn respiration sensors. The respiration rates are computed for both original as well as artifact removed data and validated using Bland–Altman plots. The respiration rates computed based on the proposed GUI (after artifact removal process) demonstrated consistent results for two respiration sensors after artifact removal process. Groundtruth is customizable, and alternative processing modules are easy to add/remove. Groundtruth is intended for open-source use.
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Affiliation(s)
- Ganesh R Naik
- Biomedical Engineering and Neuromorphic Systems, The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, NSW, Australia
| | - Gaetano D Gargiulo
- Biomedical Engineering and Neuromorphic Systems, The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, NSW, Australia
| | - Jorge M Serrador
- Rutgers Biomedical and Health Sciences, Newark, NJ, United States.,Department of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers University, Newark, NJ, United States
| | - Paul P Breen
- Biomedical Engineering and Neuromorphic Systems, The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, NSW, Australia.,Translational Health Research Institute, Western Sydney University, Penrith, NSW, Australia
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A Comparison of Reflective Photoplethysmography for Detection of Heart Rate, Blood Oxygen Saturation, and Respiration Rate at Various Anatomical Locations. SENSORS 2019; 19:s19081874. [PMID: 31010184 PMCID: PMC6514840 DOI: 10.3390/s19081874] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 04/14/2019] [Accepted: 04/17/2019] [Indexed: 01/30/2023]
Abstract
Monitoring of vital signs is critical for patient triage and management. Principal assessments of patient conditions include respiratory rate heart/pulse rate and blood oxygen saturation. However, these assessments are usually carried out with multiple sensors placed in different body locations. The aim of this paper is to identify a single location on the human anatomy whereby a single 1 cm × 1 cm non-invasive sensor could simultaneously measure heart rate (HR), blood oxygen saturation (SpO2), and respiration rate (RR), at rest and while walking. To evaluate the best anatomical location, we analytically compared eight anatomical locations for photoplethysmography (PPG) sensors simultaneously acquired by a single microprocessor at rest and while walking, with a comparison to a commercial pulse oximeter and respiration rate ground truth. Our results show that the forehead produced the most accurate results for HR and SpO2 both at rest and walking, however, it had poor RR results. The finger recorded similar results for HR and SpO2, however, it had more accurate RR results. Overall, we found the finger to be the best location for measurement of all three parameters at rest; however, no site was identified as capable of measuring all parameters while walking.
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Towards Ultra Low-Cost Myoactivated Prostheses. BIOMED RESEARCH INTERNATIONAL 2018; 2018:9634184. [PMID: 30402497 PMCID: PMC6193342 DOI: 10.1155/2018/9634184] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Accepted: 09/16/2018] [Indexed: 11/17/2022]
Abstract
In developing countries, due to the high cost involved, amputees have limited access to prosthetic limbs. This constitutes a barrier for this people to live a normal life. To break this barrier, we are developing ultra-low-cost closed-loop myoactivated prostheses that are easy to maintain manufacture and that do not require electrodes in contact with the skin to work effectively. In this paper, we present the implementation for a simple but functional hand prosthesis. Our simple design consists of a low-cost embedded microcontroller (Arduino), a wearable stretch sensor (adapted from electroresistive bands normally used for “insulation of gaskets” against EM fields), to detect residual muscle contraction as direct muscle volumetric shifts and a handful of common, not critical electronic components. The physical prosthesis is a 3D printed claw-style two-fingered hand (PLA plastic) directly geared to an inexpensive servomotor. To make our design easier to maintain, the gears and mechanical parts can be crafted from recovered materials. To implement a closed loop, the amount of closure of prosthesis is fed back to the user via a second stretch sensor directly connected to claw under the form of haptic feedback. Our concept design comprised of all the parts has an overall cost below AUD 30 and can be easily scaled up to more complicated devices suitable for other uses, i.e., multiple individual fingers and wrist rotation.
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Quantification of a Low-Cost Stretchable Conductive Sensor Using an Expansion/Contraction Simulator Machine: A Step towards Validation of a Noninvasive Cardiac and Respiration Monitoring Prototype. MACHINES 2017. [DOI: 10.3390/machines5040022] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Kevat AC, Bullen DVR, Davis PG, Kamlin COF. A systematic review of novel technology for monitoring infant and newborn heart rate. Acta Paediatr 2017; 106:710-720. [PMID: 28199732 DOI: 10.1111/apa.13786] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/24/2016] [Revised: 01/27/2017] [Accepted: 02/10/2017] [Indexed: 11/30/2022]
Abstract
Heart rate (HR) is a vital sign for assessing the need for resuscitation. We performed a systematic review of studies assessing novel methods of measuring HR in newborns and infants in the neonatal unit. Two investigators completed independent literature searches. Identified papers were independently evaluated, and relevant data were extracted and analysed. CONCLUSION This systematic review identified seven new technologies, including camera-based photoplethysmography, reflectance pulse oximetry, laser Doppler methods, capacitive sensors, piezoelectric sensors, electromyography and a digital stethoscope. Clinicians should be aware of several of these, which may become available for clinical use in the near future.
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Affiliation(s)
- Ajay C. Kevat
- Newborn Research Centre; Royal Women's Hospital; Melbourne Vic. Australia
- Department of Obstetrics and Gynaecology; University of Melbourne; Melbourne Vic. Australia
- Monash Health; Monash Medical Centre; Clayton Vic. Australia
| | | | - Peter G. Davis
- Newborn Research Centre; Royal Women's Hospital; Melbourne Vic. Australia
- Department of Obstetrics and Gynaecology; University of Melbourne; Melbourne Vic. Australia
| | - C. Omar F. Kamlin
- Newborn Research Centre; Royal Women's Hospital; Melbourne Vic. Australia
- Department of Obstetrics and Gynaecology; University of Melbourne; Melbourne Vic. Australia
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