Pulse oximetry-derived respiratory rate in general care floor patients

A two-phased study on the use of remote photoplethysmography (rPPG) in paediatric care

Background

Advancements in medical technologies have led to the development of contact-free methods of haemodynamic monitoring such as remote photoplethysmography (rPPG). rPPG uses video cameras to interpret variations in skin colour related to blood flow, which are analysed to generate vital signs readings. rPPG potentially ameliorates problems like fretfulness and fragile skin contact associated with conventional probes in children. While rPPG has been validated in adults, no prior validation has been performed in children.

Methods

A two-phased prospective cross-sectional single-centre study was conducted from January to April 2023 to evaluate the feasibility, acceptability, and accuracy of obtaining heart rate (HR), respiratory rate (RR) and oxygen saturation (SpO2) using rPPG in children, compared to the current standard of care. In Phase 1, we recruited patients ≤16 years from the neonatal and paediatric wards. We excluded preterm neonates with gestational age <35 weeks and newborns <24 hours old. The rPPG webcam was positioned 30 cm from the face. After 1 minute of facial scanning, readings generated were compared with pulse oximetry for HR and SpO2, and manual counting for RR. Correlation and Bland-Altman analyses were performed. In Phase 2, we focused on the population in whom there was potential correlation between rPPG and the actual vital signs.

Results

Ten neonates and 28 children aged 5 to 16 years were recruited for Phase 1 (765 datapoints). All patients were haemodynamically stable and normothermic. Patients and caregivers showed high acceptability to rPPG. rPPG values were clinically discrepant for children <10 years. For those ≥10 years, moderate correlation was observed for HR, with Spearman's correlation coefficient (Rs) of 0.50 [95% confidence intervals (CI): 0.42, 0.57]. We performed Phase 2 on 23 patients aged 12 to 16 years (559 datapoints). Strong correlation was observed for HR with Rs=0.82 (95% CI: 0.78, 0.85). There was weak correlation for SpO2 and RR (Rs=-0.25 and -0.02, respectively).

Conclusions

Our study showed that rPPG is acceptable and feasible for neonates and children aged 5 to 16 years, and HR values in older children aged 12 to 16 years correlated well with the current standard. The rPPG algorithms need to be further refined for younger children, and for obtaining RR and SpO2 in all children. If successful, rPPG will provide a viable contact-free alternative for assessing paediatric vital signs, with potential use in remote monitoring and telemedicine.

Predictors of intensive care unit admission in adult cancer patients presenting to the emergency department with COVID-19 infection: A retrospective study

BACKGROUND

Adult cancer patients with COVID-19 were shown to be at higher risk of Intensive Care Unit (ICU) admission. Previously published prediction models showed controversy and enforced the importance of heterogeneity among different populations studied. Therefore, this study aimed to identify predictors of ICU admission (demographic, clinical, and COVID-19 targeted medications) in cancer patients with active COVID-19 infection presenting to the Emergency Department (ED).

METHODS

This is a retrospective cohort study. It was conducted on adult cancer patients older than 18 years who presented to the American University of Beirut Medical Center ED from February 21, 2020, till February 21, 2021, and were found to have COVID-19 infection. Relevant data were extracted from electronic medical records. The association between different variables and ICU admission was tested. Logistic regression was done to adjust for confounding variables. A p-value less than 0.05 was considered significant.

RESULTS

Eighty-nine distinct patients were included. About 37% were admitted to the ICU (n = 33). Higher ICU admission was seen in patients who had received chemotherapy within one month, had a respiratory rate at triage above 22 breaths per minute, oxygen saturation less than 95%, and a higher c-reactive protein upon presentation to the ED. After adjusting for confounding variables, only recent chemotherapy and higher respiratory rate at triage were significantly associated with ICU admission.

CONCLUSION

Physicians need to be vigilant when taking care of COVID-19 infected cancer patients. Patients who are tachypneic at presentation and those who have had chemotherapy within one month are at high risk for ICU admission.

Methods for calculating ventilation rates during resuscitation from out-of-hospital cardiac arrest

OBJECTIVE

Ventilation control is important during resuscitation from out-of-hospital cardiac arrest (OHCA). We compared different methods for calculating ventilation rates (VR) during OHCA.

METHODS

We analyzed data from the Pragmatic Airway Resuscitation Trial, identifying ventilations through capnogram recordings. We determined VR by: 1) counting the number of breaths within a time epoch ("counted" VR), and 2) calculating the mean of the inverse of measured time between breaths within a time epoch ("measured" VR). We repeated the VR estimates using different time epochs (10, 20, 30, 60 sec). We defined hypo- and hyperventilation as VR <6 and >12 breaths/min, respectively. We assessed differences in estimated hypo- and hyperventilation with each VR measurement technique.

RESULTS

Of 3,004 patients, data were available for 1,010. With the counted method, total hypoventilation increased with longer time epochs ([10-s epoch: 75 sec hypoventilation] to [60-s epoch: 97 sec hypoventilation]). However, with the measured method, total hypoventilation decreased with longer time epochs ([10-s epoch: 223 sec hypoventilation] to [60-s epoch: 150 sec hypoventilation]). With the counted method, the total duration of hyperventilation decreased with longer time epochs ([10-s epochs: 35 sec hyperventilation] to [60-s epoch: 0 sec hyperventilation]). With the measured method, total hyperventilation decreased with longer time epochs ([10-s epoch: 78 sec hyperventilation] to [60-s epoch: 0 sec hyperventilation]). Differences between the measured and counted estimates were smallest with a 60-s time epoch.

CONCLUSIONS

Quantifications of hypo- and hyperventilation vary with the applied measurement methods. Measurement methods are important when characterizing ventilation rates in OHCA.

Towards real-time thermal stress prediction systems for workers

Exposure to extreme temperatures in workplaces implies serious physical hazards to workers. In addition, a poorly acclimatized worker can have reduced performance and alertness. It may therefore be more vulnerable to the risk of accidents and injuries. Due to the incompatibility of standards and regulations with some work environments and a lack of thermal exchange in many personal protective equipment, heat stress remains among the most common physical risks in many industrial sectors. Furthermore, conventional methods of measuring physiological parameters in order to calculate personal thermophysiological constraints are not practical to use during work tasks. However, the emergence of wearable technologies can contribute to real-time measurement of body temperature and the biometric signals needed to assess thermophysiological constraints while actively working. Thus, the present study was carried out in order to scrutinize the current knowledge of these types of technologies by analyzing the available systems and the advances made in previous studies, as well as to discuss the efforts required to develop devices for the prevention of the occurrence of heat stress in real time.

Transducer Technologies for Biosensors and Their Wearable Applications

The development of new biosensor technologies and their active use as wearable devices have offered mobility and flexibility to conventional western medicine and personal fitness tracking. In the development of biosensors, transducers stand out as the main elements converting the signals sourced from a biological event into a detectable output. Combined with the suitable bio-receptors and the miniaturization of readout electronics, the functionality and design of the transducers play a key role in the construction of wearable devices for personal health control. Ever-growing research and industrial interest in new transducer technologies for point-of-care (POC) and wearable bio-detection have gained tremendous acceleration by the pandemic-induced digital health transformation. In this article, we provide a comprehensive review of transducers for biosensors and their wearable applications that empower users for the active tracking of biomarkers and personal health parameters.

Wearable sensor derived decompensation index for continuous remote monitoring of COVID-19 diagnosed patients

The COVID-19 pandemic has accelerated the adoption of innovative healthcare methods, including remote patient monitoring. In the setting of limited healthcare resources, outpatient management of individuals newly diagnosed with COVID-19 was commonly implemented, some taking advantage of various personal health technologies, but only rarely using a multi-parameter chest-patch for continuous monitoring. Here we describe the development and validation of a COVID-19 decompensation index (CDI) model based on chest patch-derived continuous sensor data to predict COVID-19 hospitalizations in outpatient-managed COVID-19 positive individuals, achieving an overall AUC of the ROC Curve of 0.84 on 308 event negative participants, and 22 event positive participants, out of an overall study cohort of 400 participants. We retrospectively compare the performance of CDI to standard of care modalities, finding that the machine learning model outperforms the standard of care modalities in terms of both numbers of events identified and with a lower false alarm rate. While only a pilot phase study, the CDI represents a promising application of machine learning within a continuous remote patient monitoring system.

Comparisons of the efficiency of respiratory rate monitoring devices and acoustic respiratory sound during endoscopic submucosal dissection

During moderate sedation for gastrointestinal endoscopic submucosal dissection (ESD), monitoring of ventilatory function is recommended. We compared the following techniques of respiratory rate (RR) measurement with respiratory sound (RRa): capnography (RRc), thoracic impedance (RRi), and plethysmograph (RRp). This study enrolled patients aged ≥ 20 years who underwent esophageal (n = 19) and colorectal (n = 5) ESDs. RRc, RRi, RRp, and RRa were measured by Capnostream™ 20P, BSM-2300, Nellcor™ PM1000N, and Radical-7^®, respectively. In total, 413 RR data were collected from the esophageal ESD group and 114 RR data were collected from the colorectal ESD group. Compared with RRa during colorectal ESD, that during esophageal ESD had larger bias [95% limit of agreement (LOA)] with RRc [1.9 (- 11.0-14.8) vs. - 0.4 (- 2.9-2.2)], RRi [9.4 (- 16.8-9.4) vs. - 1.5 (- 12.0-8.9)], and RRp [0.3 (- 5.7-6.4) vs. 0.2 (- 3.2-3.6)]. Of the correct RR values displayed during esophageal ESD, > 90% were measured as RRa and RRp. Moreover, RRc was a useful parameter during colorectal ESD. To maximize patient safety during ESD under sedation, endoscopists and medical staff should know the feature and principle of the devices used for RR measurement. During esophageal ESD, RRa and RRp may be a good parameter to detect bradypnea or apnea. RRc, RRa and RRp are useful for reliable during colorectal ESD.Trial registration UMIN-CTR (UMIN000025421).

Smart Recognition COVID-19 System to Predict Suspicious Persons Based on Face Features

The coronavirus (COVID-19) is identified at first in Wuhan in December 2019. The apparition of the COVID-19 virus is widely spread to concern all countries worldwide. The World Health Organization (WHO) on March 11 declare COVID-19 a pandemic. This Virus causes a serious infection of the respiratory system. Its high transmission constitutes great problems and challenges. The WHO proposes many actions to limit the spread of the virus such as quarantine and decrease or halt flights between states. The actions taken by states in airports are to detect suspicious persons with COVID-19. We aimed to provide a Computer-Aided Diagnosis (CAD) framework to predict suspicious COVID-19 person. This prediction identifies suspicious persons who suffer from shortness breath which is the main symptom of this disease. Extract shortness breath anomaly through the estimated heart rate from face based-video is the main contribution of the present paper. We developed a Smart Recognition COVID-19 (SRC) system to estimate the breath score. In conclusion, our study achieves an accurate breath score. The error is about 1 breath per minute. The proposed solution is of great importance because it helps managers in the airport to predict suspicious COVID-19 passengers.

Non-invasive continuous respiratory monitoring using temperature-based sensors

Respiratory rate (RR) is a key vital sign that has been traditionally employed in the clinical assessment of patients and in the prevention of respiratory compromise. Despite its relevance, current practice for monitoring RR in non-intubated patients strongly relies on visual counting, which delivers an intermittent and error-prone assessment of the respiratory status. Here, we present a novel non-invasive respiratory monitor that continuously measures the RR in human subjects. The respiratory activity of the user is inferred by sensing the thermal transfer between the breathing airflow and a temperature sensor placed between the nose and the mouth. The performance of the respiratory monitor is assessed through respiratory experiments performed on healthy subjects. Under spontaneous breathing, the mean RR difference between our respiratory monitor and visual counting was 0.4 breaths per minute (BPM), with a 95% confidence interval equal to [- 0.5, 1.3] BPM. The robustness of the respiratory sensor to the position is assessed by studying the signal-to-noise ratio in different locations on the upper lip, displaying a markedly better performance than traditional thermal sensors used for respiratory airflow measurements.

Evaluation of Remote Monitoring Device for Monitoring Vital Parameters against Reference Standard: A Diagnostic Validation Study for COVID-19 Preparedness

CONTEXT

Vital parameters including blood oxygen level, respiratory rate, pulse rate, and body temperature are crucial for triaging patients to appropriate medical care. Advances in remote health monitoring system and wearable health devices have created a new horizon for delivery of efficient health care from a distance.

MATERIALS AND METHODS

This diagnostic validation study included patients attending the outpatient department of the institute. The accuracy of device under study was compared against the gold standard patient monitoring systems used in intensive care units.

STATISTICAL ANALYSIS

The statistical analysis involved computation of intraclass correlation coefficient. Bland-Altman graphs with limits of agreement were plotted to assess agreement between methods. P <0.05 was considered statistically significant.

RESULTS

A total of 200 patients, including 152 males and 48 females in the age range of 2-80 years, formed the study group. A strong correlation (intraclass correlation coefficient; r > 0.9) was noted between the two devices for all the investigated parameters with significant P value (<0.01). Bland-Altman plot drawn for each vital parameter revealed observations in agreement from both the devices.

CONCLUSION

The wearable device can be reliably used for remote health monitoring. Its regulated use can help mitigate the scarcity of hospital beds and reduce exposure to health-care workers and demand of personal protection equipment.

Insights into postoperative respiration by using continuous wireless monitoring of respiratory rate on the postoperative ward: a cohort study

Change of respiratory rate (RespR) is the most powerful predictor of clinical deterioration. Brady- (RespR ≤ 8) and tachypnea (RespR ≥ 31) are associated with serious adverse events. Simultaneously, RespR is the least accurately measured vital parameter. We investigated the feasibility of continuously measuring RespR on the ward using wireless monitoring equipment, without impeding mobilization. Continuous monitoring of vital parameters using a wireless SensiumVitals® patch was installed and RespR was measured every 2 mins. We defined feasibility of adequate RespR monitoring if the system reports valid RespR measurements in at least 50% of time-points in more than 80% of patients during day- and night-time, respectively. Data from 119 patients were analysed. The patch detected in 171,151 of 227,587 measurements valid data for RespR (75.2%). During postoperative day and night four, the system still registered 68% and 78% valid measurements, respectively. 88% of the patients had more than 67% of valid RespR measurements. The RespR’s most frequently measured were 13–15; median RespR was 15 (mean 16, 25th- and 75th percentile 13 and 19). No serious complications or side effects were observed. We successfully measured electronically RespR on a surgical ward in postoperative patients continuously for up to 4 days post-operatively using a wireless monitoring system. While previous studies mentioned a digit preference of 18–22 for RespR, the most frequently measured RespR were 13–16. However, in the present study we did not validate the measurements against a reference method. Rather, we attempted to demonstrate the feasibility of achieving continuous wireless measurement in patients on surgical postoperative wards. As the technology used is based on impedance pneumography, obstructive apnoea might have been missed, namely in those patients receiving opioids post-operatively.

Flexible graphene photodetectors for wearable fitness monitoring

Wearable health and wellness trackers based on optical detection are promising candidates for public health uses due to their noninvasive tracking of vital health signs. However, so far, the use of rigid technologies hindered the ultimate performance and form factor of the wearable. Here, we demonstrate a new class of flexible and transparent wearables based on graphene sensitized with semiconducting quantum dots (GQD). We show several prototype wearable devices that are able to monitor vital health signs noninvasively, including heart rate, arterial oxygen saturation (SpO2), and respiratory rate. Operation with ambient light is demonstrated, offering low-power consumption. Moreover, using heterogeneous integration of a flexible ultraviolet (UV)-sensitive photodetector with a near-field communication circuit board allows wireless communication and power transfer between the photodetectors and a smartphone, offering battery-free operation. This technology paves the way toward seamlessly integrated wearables, and empowers the user through wireless probing of the UV index.

Recent development of respiratory rate measurement technologies

Respiratory rate (RR) is an important physiological parameter whose abnormality has been regarded as an important indicator of serious illness. In order to make RR monitoring simple to perform, reliable and accurate, many different methods have been proposed for such automatic monitoring. According to the theory of respiratory rate extraction, methods are categorized into three modalities: extracting RR from other physiological signals, RR measurement based on respiratory movements, and RR measurement based on airflow. The merits and limitations of each method are highlighted and discussed. In addition, current works are summarized to suggest key directions for the development of future RR monitoring methodologies.

A pilot study of respiratory rate derived from a wearable biosensor compared with capnography in emergency department patients

Purpose: Respiratory rate is assessed less frequently than other vital signs, and documented respiratory rates are often erroneous. This pilot study compared respiratory rates derived from a wearable biosensor to those derived from capnography. Methods: Emergency department patients with respiratory complaints were enrolled and had capnography via nasal cannula and a wireless, wearable biosensor from Philips applied for approximately one hour. Respiratory rates were obtained from both of these methods. We determined the difference between median respiratory rates obtained from the biosensor and capnography and the proportion of biosensor-derived respiratory rates that were within three breaths/minute of the capnography-derived respiratory rates for each patient. A Spearman correlation coefficient was calculated to assess the strength of the correlation between mean respiratory rates derived from both methods. Plots of minute-by-minute respiratory rates, per patient, for each monitoring method were shown to two physicians. The physicians identified time periods in which the respiratory rates appeared invalid. The proportion of time with invalid respiratory rates for each patient, for each method, was calculated and averaged. Results: We analyzed data for 17 patients. Median biosensor-derived respiratory rate was 20 breaths/minute (range: 7-40 breaths/minute) and median capnography-derived respiratory rate was 25 breaths/minute (range: 0-58 breaths/minute). Overall, 72.8% of biosensor-derived respiratory rates were within three breaths per minute of the capnography-derived respiratory rates. Overall mean difference was 3.5 breaths/minute (±5.2 breaths/minute). Respiratory rates appeared invalid 0.7% of the time for the biosensor and 5.0% of the time for capnography. Conclusion: Our pilot study suggests that the Philips wearable biosensor can continuously obtain respiratory rates that are comparable to capnography-derived respiratory rates among emergency department patients with respiratory complaints.

A Comparison of Reflective Photoplethysmography for Detection of Heart Rate, Blood Oxygen Saturation, and Respiration Rate at Various Anatomical Locations

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.

Acoustic respiration rate and pulse oximetry-derived respiration rate: a clinical comparison study

Respiration rate (RR) is a critical vital sign that provides early detection of respiratory compromise. The acoustic technique of measuring continuous respiration rate (RR_a) interprets the large airway sound envelope to calculate respiratory rate while pulse oximetry-derived respiratory rate (RR_oxi) interprets modulations of the photoplethsymograph in response to hemodynamic changes during the respiratory cycle. The aim of this study was to compare the performance of these technologies to each other and to a capnography-based reference device. Subjects were asked to decrease their RR from 14 to 4 breaths per minute (BPM) and then increase RR from 14 to 24 BPM. The effects of physiological noise, ambient noise, and head movement and shallow breathing on device performance were also evaluated. The test devices were: (1) RR_a, Radical-7 (Masimo Corporation), (2) RR_oxi, Nellcor™ Bedside Respiratory Patient Monitoring System (Medtronic), and (3) reference device, Capnostream20p™ (Medtronic). All devices were configured with their default settings. Twenty-nine healthy adult subjects were included in the study. During abrupt changes in breathing, overall RR_oxi was accurate for longer periods of time than RR_a; specifically, RR_oxi was more accurate during low and normal RR, but not during high RR. RR_oxi also displayed a value for significantly longer time periods than RR_a when the subjects produced physiological sounds and moved their heads, but not during shallow breathing or ambient noise. RR_oxi may be more accurate than RR_a during development of bradypnea. Also, RR_oxi may display a more reliable RR value during routine patient activities.

Validation of Instantaneous Respiratory Rate Using Reflectance PPG from Different Body Positions

Respiratory rate (RR) is a key parameter used in healthcare for monitoring and predicting patient deterioration. However, continuous and automatic estimation of this parameter from wearable sensors is still a challenging task. Various methods have been proposed to estimate RR from wearable sensors using windowed segments of the data; e.g., often using a minimum of 32 s. Little research has been reported in the literature concerning the instantaneous detection of respiratory rate from such sources. In this paper, we develop and evaluate a method to estimate instantaneous respiratory rate (IRR) from body-worn reflectance photoplethysmography (PPG) sensors. The proposed method relies on a nonlinear time-frequency representation, termed the wavelet synchrosqueezed transform (WSST). We apply the latter to derived modulations of the PPG that arise from the act of breathing.We validate the proposed algorithm using (i) a custom device with a PPG probe placed on various body positions and (ii) a commercial wrist-worn device (WaveletHealth Inc., Mountain View, CA, USA). Comparator reference data were obtained via a thermocouple placed under the nostrils, providing ground-truth information concerning respiration cycles. Tracking instantaneous frequencies was performed in the joint time-frequency spectrum of the (4 Hz re-sampled) respiratory-induced modulation using the WSST, from data obtained from 10 healthy subjects. The estimated instantaneous respiratory rates have shown to be highly correlated with breath-by-breath variations derived from the reference signals. The proposed method produced more accurate results compared to averaged RR obtained using 32 s windows investigated with overlap between successive windows of (i) zero and (ii) 28 s. For a set of five healthy subjects, the averaged similarity between reference RR and instantaneous RR, given by the longest common subsequence (LCSS) algorithm, was calculated as 0.69; this compares with averaged similarity of 0.49 using 32 s windows with 28 s overlap between successive windows. The results provide insight into estimation of IRR and show that upper body positions produced PPG signals from which a better respiration signal was extracted than for other body locations.

Incidence of respiratory depression after epidural administration of morphine for cesarean delivery: findings using a continuous respiratory rate monitoring system

BACKGROUND

Epidural morphine is widely used for postoperative analgesia after cesarean delivery. However, respiratory depression can occur after neuraxial administration of morphine. Previous reports describing respiratory depression in obstetric patients have relied on intermittent visual counting of the respiratory rate. In this study, we estimated the incidence of respiratory depression in patients who had received epidural morphine after cesarean delivery, using a continuous respiratory rate monitoring system with a finger sensor.

METHODS

One hundred patients scheduled to undergo elective cesarean delivery and receive intraoperative neuraxial morphine between April and December 2016 were recruited for this single-center, prospective observational study. Postoperatively, all patients received epidural morphine 3 mg and were equipped with the Nellcor respiratory rate monitoring system. Respiratory depression was defined as both bradypnea (respiratory rate ≤10 breaths/min) and oxygen desaturation (mild ≤95%; moderate ≤90%; severe ≤85%) for longer than one minute. The number of patients with respiratory depression between administration of morphine and first ambulation was recorded hourly.

RESULTS

Complete monitoring was obtained for 89 of 100 women. The median duration of monitoring was 19.0 hours. Forty-six patients (52%) developed mild respiratory depression at least once before ambulation, but only one (1%) developed moderate respiratory depression. None required supplemental oxygen or naloxone.

CONCLUSIONS

Approximately half the women experienced mild respiratory depression, but only one developed moderate respiratory depression. Continuous respiratory rate monitoring until ambulation may assist in early identification of respiratory depression after neuraxial administration of morphine.

Video-based heart rate monitoring across a range of skin pigmentations during an acute hypoxic challenge

The robust monitoring of heart rate from the video-photoplethysmogram (video-PPG) during challenging conditions requires new analysis techniques. The work reported here extends current research in this area by applying a motion tolerant algorithm to extract high quality video-PPGs from a cohort of subjects undergoing marked heart rate changes during a hypoxic challenge, and exhibiting a full range of skin pigmentation types. High uptimes in reported video-based heart rate (HRvid) were targeted, while retaining high accuracy in the results. Ten healthy volunteers were studied during a double desaturation hypoxic challenge. Video-PPGs were generated from the acquired video image stream and processed to generate heart rate. HRvid was compared to the pulse rate posted by a reference pulse oximeter device (HRp). Agreement between video-based heart rate and that provided by the pulse oximeter was as follows: Bias = - 0.21 bpm, RMSD = 2.15 bpm, least squares fit gradient = 1.00 (Pearson R = 0.99, p < 0.0001), with a 98.78% reporting uptime. The difference between the HRvid and HRp exceeded 5 and 10 bpm, for 3.59 and 0.35% of the reporting time respectively, and at no point did these differences exceed 25 bpm. Excellent agreement was found between the HRvid and HRp in a study covering the whole range of skin pigmentation types (Fitzpatrick scales I-VI), using standard room lighting and with moderate subject motion. Although promising, further work should include a larger cohort with multiple subjects per Fitzpatrick class combined with a more rigorous motion and lighting protocol.

Wearable Health Devices-Vital Sign Monitoring, Systems and Technologies

Wearable Health Devices (WHDs) are increasingly helping people to better monitor their health status both at an activity/fitness level for self-health tracking and at a medical level providing more data to clinicians with a potential for earlier diagnostic and guidance of treatment. The technology revolution in the miniaturization of electronic devices is enabling to design more reliable and adaptable wearables, contributing for a world-wide change in the health monitoring approach. In this paper we review important aspects in the WHDs area, listing the state-of-the-art of wearable vital signs sensing technologies plus their system architectures and specifications. A focus on vital signs acquired by WHDs is made: first a discussion about the most important vital signs for health assessment using WHDs is presented and then for each vital sign a description is made concerning its origin and effect on heath, monitoring needs, acquisition methods and WHDs and recent scientific developments on the area (electrocardiogram, heart rate, blood pressure, respiration rate, blood oxygen saturation, blood glucose, skin perspiration, capnography, body temperature, motion evaluation, cardiac implantable devices and ambient parameters). A general WHDs system architecture is presented based on the state-of-the-art. After a global review of WHDs, we zoom in into cardiovascular WHDs, analysing commercial devices and their applicability versus quality, extending this subject to smart t-shirts for medical purposes. Furthermore we present a resumed evolution of these devices based on the prototypes developed along the years. Finally we discuss likely market trends and future challenges for the emerging WHDs area.

Respiratory Rate Variability as a Prognostic Factor in Hospitalized Patients Transferred to the Intensive Care Unit

Introduction

Increasing mortality rates within the intensive care unit (ICU) is an ever growing problem, ultimately leading to increases in the cost of healthcare expenditures. Currently, there are attempts to use guidelines in the hospital setting to predict overall mortality in critically ill patients. However, a predictor of subsequent ICU admissions remains to be explored. Recent data has shown the importance of monitoring respiratory rate variability (RRV) as a useful predictor of the deterioration of patients. Respiratory rate, in comparison to blood pressure or pulse rate, is deemed as the better determinant in identifying high-risk patients.

Aim

Our study aims to assess the role of RRV monitoring as a potential prognostic marker predictive of ICU admission.

Results

There was a significant (p = 0.009) increase in RRV between the third and fourth set of respiratory rates prior to ICU admission, such that coefficient of variation percentage (CV%) increased from 0.3% (95% confidence interval (CI): 0.09 - 0.42) to 0.7% (95% CI: 0.04 - 0.9) about 12 hours before admission to the ICU independent from diagnosis.

Conclusion

Using elevated RRV as a signal may be a useful prognostic tool in providing early intervention, thus reducing the incidence of subsequent morbidity and mortality in patients that might necessitate an ICU admission.

A Hybrid Wavelet-Based Method for the Peak Detection of Photoplethysmography Signals

The noninvasive peripheral oxygen saturation (SpO₂) and the pulse rate can be extracted from photoplethysmography (PPG) signals. However, the accuracy of the extraction is directly affected by the quality of the signal obtained and the peak of the signal identified; therefore, a hybrid wavelet-based method is proposed in this study. Firstly, we suppressed the partial motion artifacts and corrected the baseline drift by using a wavelet method based on the principle of wavelet multiresolution. And then, we designed a quadratic spline wavelet modulus maximum algorithm to identify the PPG peaks automatically. To evaluate this hybrid method, a reflective pulse oximeter was used to acquire ten subjects' PPG signals under sitting, raising hand, and gently walking postures, and the peak recognition results on the raw signal and on the corrected signal were compared, respectively. The results showed that the hybrid method not only corrected the morphologies of the signal well but also optimized the peaks identification quality, subsequently elevating the measurement accuracy of SpO₂ and the pulse rate. As a result, our hybrid wavelet-based method profoundly optimized the evaluation of respiratory function and heart rate variability analysis.

Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review

Breathing rate (BR) is a key physiological parameter used in a range of clinical settings. Despite its diagnostic and prognostic value, it is still widely measured by counting breaths manually. A plethora of algorithms have been proposed to estimate BR from the electrocardiogram (ECG) and pulse oximetry (photoplethysmogram, PPG) signals. These BR algorithms provide opportunity for automated, electronic, and unobtrusive measurement of BR in both healthcare and fitness monitoring. This paper presents a review of the literature on BR estimation from the ECG and PPG. First, the structure of BR algorithms and the mathematical techniques used at each stage are described. Second, the experimental methodologies that have been used to assess the performance of BR algorithms are reviewed, and a methodological framework for the assessment of BR algorithms is presented. Third, we outline the most pressing directions for future research, including the steps required to use BR algorithms in wearable sensors, remote video monitoring, and clinical practice.

Video-Based Physiologic Monitoring During an Acute Hypoxic Challenge: Heart Rate, Respiratory Rate, and Oxygen Saturation

BACKGROUND

The physiologic information contained in the video photoplethysmogram is well documented. However, extracting this information during challenging conditions requires new analysis techniques to capture and process the video image streams to extract clinically useful physiologic parameters. We hypothesized that heart rate, respiratory rate, and oxygen saturation trending can be evaluated accurately from video information during acute hypoxia.

METHODS

Video footage was acquired from multiple desaturation episodes during a porcine model of acute hypoxia using a standard visible light camera. A novel in-house algorithm was used to extract photoplethysmographic cardiac pulse and respiratory information from the video image streams and process it to extract a continuously reported video-based heart rate (HRvid), respiratory rate (RRvid), and oxygen saturation (SvidO2). This information was then compared with HR and oxygen saturation references from commercial pulse oximetry and the known rate of respiration from the ventilator.

RESULTS

Eighty-eight minutes of data were acquired during 16 hypoxic episodes in 8 animals. A linear mixed-effects regression showed excellent responses relative to a nonhypoxic reference signal with slopes of 0.976 (95% confidence interval [CI], 0.973-0.979) for HRvid; 1.135 (95% CI, 1.101-1.168) for RRvid, and 0.913 (95% CI, 0.905-0.920) for video-based oxygen saturation. These results were obtained while maintaining continuous uninterrupted vital sign monitoring for the entire study period.

CONCLUSIONS

Video-based monitoring of HR, RR, and oxygen saturation may be performed with reasonable accuracy during acute hypoxic conditions in an anesthetized porcine hypoxia model using standard visible light camera equipment. However, the study was conducted during relatively low motion. A better understanding of the effect of motion and the effect of ambient light on the video photoplethysmogram may help refine this monitoring technology for use in the clinical environment.

Photoplethysmography respiratory rate monitoring in patients receiving procedural sedation and analgesia for upper gastrointestinal endoscopy

The value of capnography during procedural sedation and analgesia (PSA) for the detection of hypoxaemia during upper gastrointestinal (UGI) endoscopic procedures is limited. Photoplethysmography respiratory rate (RRp) monitoring may provide a useful alternative, but the level of agreement with capnography during PSA is unknown. We therefore investigated the level of agreement between the RRp and capnography-based RR (RRc) during PSA for UGI endoscopy. This study included patients undergoing PSA for UGI endoscopy procedures. Pulse oximetry (SpO2) and RRc were recorded in combination with Nellcor 2.0 (RRp) monitoring (Covidien, USA). Bland-Altman analysis was used to evaluate the level of agreement between RRc and RRp. Episodes of apnoea, defined as no detection of exhaled CO2 for minimal 36 s, and hypoxaemia, defined as an SpO2 < 92 %, were registered. A total of 1054 min of data from 26 patients were analysed. Bland-Altman analysis between the RRc and RRp revealed a bias of 2.25 ± 5.41 breath rate per minute (brpm), with limits of agreement from -8.35 to 12.84 brpm for an RR ≥ 4 brpm. A total of 67 apnoea events were detected. In 21 % of all apnoea events, the patient became hypoxaemic. Hypoxaemia occurred 42 times with a median length of 34 (19-141) s, and was preceded in 34 % of the cases by apnoea and in 64 % by an RRc ≥ 8 brpm. In 81 % of all apnoea events, photoplethysmography registered an RRp ≥ 4 brpm. We found a low level of agreement between capnography and the plethysmography respiratory rate during procedural sedation for UGI endoscopy. Moreover, respiratory rate derived from both the capnogram and photoplethysmogram showed a limited ability to provide warning signs for a hypoxaemic event during the sedation procedure.

Multicenter Study Validating Accuracy of a Continuous Respiratory Rate Measurement Derived From Pulse Oximetry: A Comparison With Capnography

Published ahead of print January 17, 2017.

BACKGROUND:

Intermittent measurement of respiratory rate via observation is routine in many patient care settings. This approach has several inherent limitations that diminish the clinical utility of these measurements because it is intermittent, susceptible to human error, and requires clinical resources. As an alternative, a software application that derives continuous respiratory rate measurement from a standard pulse oximeter has been developed. We sought to determine the performance characteristics of this new technology by comparison with clinician-reviewed capnography waveforms in both healthy subjects and hospitalized patients in a low-acuity care setting.

METHODS:

Two independent observational studies were conducted to validate the performance of the Medtronic Nellcor^TM Respiration Rate Software application. One study enrolled 26 healthy volunteer subjects in a clinical laboratory, and a second multicenter study enrolled 53 hospitalized patients. During a 30-minute study period taking place while participants were breathing spontaneously, pulse oximeter and nasal/oral capnography waveforms were collected. Pulse oximeter waveforms were processed to determine respiratory rate via the Medtronic Nellcor Respiration Rate Software. Capnography waveforms reviewed by a clinician were used to determine the reference respiratory rate.

RESULTS:

A total of 23,243 paired observations between the pulse oximeter-derived respiratory rate and the capnography reference method were collected and examined. The mean reference-based respiratory rate was 15.3 ± 4.3 breaths per minute with a range of 4 to 34 breaths per minute. The Pearson correlation coefficient between the Medtronic Nellcor Respiration Rate Software values and the capnography reference respiratory rate is reported as a linear correlation, R, as 0.92 ± 0.02 (P < .001), whereas Lin’s concordance correlation coefficient indicates an overall agreement of 0.85 ± 0.04 (95% confidence interval [CI] +0.76; +0.93) (healthy volunteers: 0.94 ± 0.02 [95% CI +0.91; +0.97]; hospitalized patients: 0.80 ± 0.06 [95% CI +0.68; +0.92]). The mean bias of the Medtronic Nellcor Respiration Rate Software was 0.18 breaths per minute with a precision (SD) of 1.65 breaths per minute (healthy volunteers: 0.37 ± 0.78 [95% limits of agreement: –1.16; +1.90] breaths per minute; hospitalized patients: 0.07 ± 1.99 [95% limits of agreement: –3.84; +3.97] breaths per minute). The root mean square deviation was 1.35 breaths per minute (healthy volunteers: 0.81; hospitalized patients: 1.60).

CONCLUSIONS:

These data demonstrate the performance of the Medtronic Nellcor Respiration Rate Software in healthy subjects and patients hospitalized in a low-acuity care setting when compared with clinician-reviewed capnography. The observed performance of this technology suggests that it may be a useful adjunct to continuous pulse oximetry monitoring by providing continuous respiratory rate measurements. The potential patient safety benefit of using combined continuous pulse oximetry and respiratory rate monitoring warrants assessment.

A novel hardware implementation for detecting respiration rate using photoplethysmography

Asthma is a serious public health problem. Continuous monitoring of breathing may offer an alternative way to assess disease status. In this paper we present a novel hardware implementation for the capture and storage of a photoplethysmography (PPG) signal. The LED duty cycle was altered to determine the effect on respiratory rate accuracy. The oximeter was mounted to the left index finger of ten healthy volunteers. The breathing rate derived from the oximeter was validated against a nasal airflow sensor. The duty cycle of a pulse oximeter was changed between 5%, 10% and 25% at a sample rate of 500 Hz. A PPG signal and reference signal was captured for each duty cycle. The PPG signals were post processed in Matlab to derive a respiration rate using an existing Matlab toolbox. At a 25% duty cycle the RMSE was <;2 breaths per minute for the top performing algorithm. The RMSE increased to over 5 breaths per minute when the duty cycle was reduced to 5%. The power consumed by the hardware for a 5%, 10% and 25% duty cycle was 5.4 mW, 7.8 mW, and 15 mW respectively. For clinical assessment of respiratory rate, a RSME of <;2 breaths per minute is recommended. Further work is required to determine utility in asthma management. However for non-clinical applications such as fitness tracking, lower accuracy may be sufficient to allow a reduced duty cycle setting.

A Brief Review of Non-invasive Monitoring of Respiratory Condition for Extubated Patients with or at Risk for Obstructive Sleep Apnea after Surgery

Obstructive sleep apnea (OSA) is one of the important risk factors contributing to postoperative airway complications. OSA alters the respiratory physiology and increases the sensitivity of muscle tone of the upper airway after surgery to residual anesthetic medication. In addition, the prevalence of OSA was reported to be much higher among surgical patients than the general population. Therefore, appropriate monitoring to detect early respiratory impairment in postoperative extubated patients with possible OSA is challenging. Based on the comprehensive clinical observation, several equipment have been used for monitoring the respiratory conditions of OSA patients after surgery, including the continuous pulse oximetry, capnography, photoplethysmography (PPG), and respiratory volume monitor (RVM). To date, there has been no consensus on the most suitable device as a recommended standard of care. In this review, we describe the advantages and disadvantages of some possible monitoring strategies under certain clinical conditions. According to the literature, the continuous pulse oximetry, with its high sensitivity, is still the most widely used device. It is also cost-effective and convenient to use but has low specificity and does not reflect ventilation. Capnography is the most widely used device for detection of hypoventilation, but it may not provide reliable data for extubated patients. Even normal capnography cannot exclude the existence of hypoxia. PPG shows the state of both ventilation and oxygenation, but its sensitivity needs further improvement. RVM provides real-time detection of hypoventilation, quantitative precise demonstration of respiratory rate, tidal volume, and MV for extubated patients, but no reflection of oxygenation. Altogether, the sole use of any of these devices is not ideal for monitoring of extubated patients with or at risk for OSA after surgery. However, we expect that the combined use of continuous pulse oximetry and RVM may be promising for these patients due to their complementary function, which need further study.

Respiratory effort from the photoplethysmogram

The potential for a simple, non-invasive measure of respiratory effort based on the pulse oximeter signal - the photoplethysmogram or 'pleth' - was investigated in a pilot study. Several parameters were developed based on a variety of manifestations of respiratory effort in the signal, including modulation changes in amplitude, baseline, frequency and pulse transit times, as well as distinct baseline signal shifts. Thirteen candidate parameters were investigated using data from healthy volunteers. Each volunteer underwent a series of controlled respiratory effort maneuvers at various set flow resistances and respiratory rates. Six oximeter probes were tested at various body sites. In all, over three thousand pleth-based effort-airway pressure (EP) curves were generated across the various airway constrictions, respiratory efforts, respiratory rates, subjects, probe sites, and the candidate parameters considered. Regression analysis was performed to determine the existence of positive monotonic relationships between the respiratory effort parameters and resulting airway pressures. Six of the candidate parameters investigated exhibited a distinct positive relationship (p<0.001 across all probes tested) with increasing upper airway pressure repeatable across the range of respiratory rates and flow constrictions studied. These were: the three fundamental modulations in amplitude (AM-Effort), baseline (BM-Effort) and respiratory sinus arrhythmia (RSA-Effort); two pulse transit time modulations - one using a pulse oximeter probe and an ECG (P2E-Effort) and the other using two pulse oximeter probes placed at different peripheral body sites (P2-Effort); and baseline shifts in heart rate, (BL-HR-Effort). In conclusion, a clear monotonic relationship was found between several pleth-based parameters and imposed respiratory loadings at the mouth across a range of respiratory rates and flow constrictions. The results suggest that the pleth may provide a measure of changing upper airway dynamics indicative of the effort to breathe.

A Brief Review of Non-invasive Monitoring of Respiratory Condition for Extubated Patients with or at Risk for Obstructive Sleep Apnea after Surgery

Obstructive sleep apnea (OSA) is one of the important risk factors contributing to postoperative airway complications. OSA alters the respiratory physiology and increases the sensitivity of muscle tone of the upper airway after surgery to residual anesthetic medication. In addition, the prevalence of OSA was reported to be much higher among surgical patients than the general population. Therefore, appropriate monitoring to detect early respiratory impairment in postoperative extubated patients with possible OSA is challenging. Based on the comprehensive clinical observation, several equipment have been used for monitoring the respiratory conditions of OSA patients after surgery, including the continuous pulse oximetry, capnography, photoplethysmography (PPG), and respiratory volume monitor (RVM). To date, there has been no consensus on the most suitable device as a recommended standard of care. In this review, we describe the advantages and disadvantages of some possible monitoring strategies under certain clinical conditions. According to the literature, the continuous pulse oximetry, with its high sensitivity, is still the most widely used device. It is also cost-effective and convenient to use but has low specificity and does not reflect ventilation. Capnography is the most widely used device for detection of hypoventilation, but it may not provide reliable data for extubated patients. Even normal capnography cannot exclude the existence of hypoxia. PPG shows the state of both ventilation and oxygenation, but its sensitivity needs further improvement. RVM provides real-time detection of hypoventilation, quantitative precise demonstration of respiratory rate, tidal volume, and MV for extubated patients, but no reflection of oxygenation. Altogether, the sole use of any of these devices is not ideal for monitoring of extubated patients with or at risk for OSA after surgery. However, we expect that the combined use of continuous pulse oximetry and RVM may be promising for these patients due to their complementary function, which need further study.

Elimination of Drifts in Long-Duration Monitoring for Apnea-Hypopnea of Human Respiration

This paper reports a methodology to eliminate an uncertain baseline drift in respiratory monitoring using a thermal airflow sensor exposed in a high humidity environment. Human respiratory airflow usually contains a large amount of moisture (relative humidity, RH > 85%). Water vapors in breathing air condense gradually on the surface of the sensor so as to form a thin water film that leads to a significant sensor drift in long-duration respiratory monitoring. The water film is formed by a combination of condensation and evaporation, and therefore the behavior of the humidity drift is complicated. Fortunately, the exhale and inhale responses of the sensor exhibit distinguishing features that are different from the humidity drift. Using a wavelet analysis method, we removed the baseline drift of the sensor and successfully recovered the respiratory waveform. Finally, we extracted apnea-hypopnea events from the respiratory signals monitored in whole-night sleeps of patients and compared them with golden standard polysomnography (PSG) results.

Determination of saturation, heart rate, and respiratory rate at forearm using a Nellcor™ forehead SpO2-saturation sensor

Alterations in arterial blood oxygen saturation, heart rate (HR), and respiratory rate (RR) are strongly associated with intra-hospital cardiac arrests and resuscitations. A wireless, easy-to-use, and comfortable method for monitoring these important clinical signs would be highly useful. We investigated whether the Nellcor™ OxiMask MAX-FAST forehead sensor could provide data for vital sign measurements when located at the distal forearm instead of its intended location at the forehead to provide improved comfortability and easy placement. In a prospective setting, we recruited 30 patients undergoing surgery requiring postoperative care. At the postoperative care unit, patients were monitored for two hours using a standard patient monitor and with a study device equipped with a Nellcor™ Forehead SpO₂ sensor. The readings were electronically recorded and compared in post hoc analysis using Bland-Altman plots, Spearman's correlation, and root-mean-square error (RMSE). Bland-Altman plot showed that saturation (SpO₂) differed by a mean of -0.2 % points (SD, 4.6), with a patient-weighted Spearman's correlation (r) of 0.142, and an RMSE of 4.2 points. For HR measurements, the mean difference was 0.6 bpm (SD, 2.5), r = 0.997, and RMSE = 1.8. For RR, the mean difference was -0.5 1/min (4.1), r = 0.586, and RMSE = 4.0. The SpO₂ readings showed a low mean difference, but also a low correlation and high RMSE, indicating that the Nellcor™ saturation sensor cannot reliably assess oxygen saturation at the forearm when compared to finger PPG measurements.

Reduction of Periodic Motion Artifacts in Photoplethysmography

Periodic motion artifacts affect photoplethysmography (PPG) signals in activities of daily living (ADL), cardiopulmonary exercise testing (CPX), and cardiopulmonary resuscitation (CPR). This hampers measurement of interbeat intervals (IBIs) and oxygen saturation (SpO ₂ ). Our objective was to develop a generic algorithm to remove periodic motion artifacts, recovering artifact-reduced PPG signals for beat-to-beat analysis.

METHODS

The algorithm was retrospectively evaluated on forehead PPG signals measured while walking on a treadmill. The step rate was tracked in a motion reference signal via a second-order generalized integrator with a frequency-locked loop. Two reference signals were compared: sensor motion relative to the skin ( ∆x[n]) measured via self-mixing interferometry and head motion ( a_v[n] ) measured via accelerometry. The step rate was used in a quadrature harmonic model to estimate the artifacts. Quadrature components need only two coefficients per frequency leading to a short filter and prevent undesired frequency-shifted components in the artifact estimate. Subtracting the estimate from the measured signal reduced the artifacts.

RESULTS

Compared to ∆x[n] , a_v[n] had a better signal-to-noise ratio and more consistently contained a component at the step rate. Artifact reduction was effective for distinct step rate and pulse rate, since the artifact-reduced signals provided more stable IBI and SpO ₂ measurements.

CONCLUSION

Accelerometry provided a more reliable motion reference signal. The proposed algorithm can be of significance for monitoring in ADL, CPX, or CPR, by providing artifact-reduced PPG signals for improved IBI and SpO ₂ measurements during periodic motion.

An assessment of algorithms to estimate respiratory rate from the electrocardiogram and photoplethysmogram

Over 100 algorithms have been proposed to estimate respiratory rate (RR) from the electrocardiogram (ECG) and photoplethysmogram (PPG). As they have never been compared systematically it is unclear which algorithm performs the best. Our primary aim was to determine how closely algorithms agreed with a gold standard RR measure when operating under ideal conditions. Secondary aims were: (i) to compare algorithm performance with IP, the clinical standard for continuous respiratory rate measurement in spontaneously breathing patients; (ii) to compare algorithm performance when using ECG and PPG; and (iii) to provide a toolbox of algorithms and data to allow future researchers to conduct reproducible comparisons of algorithms. Algorithms were divided into three stages: extraction of respiratory signals, estimation of RR, and fusion of estimates. Several interchangeable techniques were implemented for each stage. Algorithms were assembled using all possible combinations of techniques, many of which were novel. After verification on simulated data, algorithms were tested on data from healthy participants. RRs derived from ECG, PPG and IP were compared to reference RRs obtained using a nasal-oral pressure sensor using the limits of agreement (LOA) technique. 314 algorithms were assessed. Of these, 270 could operate on either ECG or PPG, and 44 on only ECG. The best algorithm had 95% LOAs of  -4.7 to 4.7 bpm and a bias of 0.0 bpm when using the ECG, and  -5.1 to 7.2 bpm and 1.0 bpm when using PPG. IP had 95% LOAs of  -5.6 to 5.2 bpm and a bias of  -0.2 bpm. Four algorithms operating on ECG performed better than IP. All high-performing algorithms consisted of novel combinations of time domain RR estimation and modulation fusion techniques. Algorithms performed better when using ECG than PPG. The toolbox of algorithms and data used in this study are publicly available.

Journal of Clinical Monitoring and Computing 2015 end of year summary: respiration

This paper reviews 17 papers or commentaries published in Journal of Clinical Monitoring and Computing in 2015, within the field of respiration. Papers were published covering monitoring and training of breathing, monitoring of gas exchange, hypoxemia and acid-base, and CO2 monitoring.

Respiratory modulations in the photoplethysmogram (DPOP) as a measure of respiratory effort

DPOP is a measure of the strength of respiratory modulations present in the pulse oximetry photoplethysmogram (pleth) waveform. It has been proposed as a non-invasive parameter for the prediction of the response to volume expansion in hypovolemic patients. The effect of resistive breathing on the DPOP parameter was studied to determine whether it may have an adjunct use as a measure of respiratory effort. Healthy volunteers were tasked to breathe at fixed respiratory rates over a range of airway resistances generated by a flow resistor inserted within a mouthpiece. Changes in respiratory efforts, effected by the subjects and measured as airway pressures at the mouth, were compared to DPOP values derived from a finger pulse oximeter probe. It was found that the increased effort to breathe manifests itself as an associated increase in DPOP. Further, a relationship between DPOP and percent modulation of the pleth waveform was observed. A version of the DPOP algorithm that corrects for low perfusion was implemented which resulted in an improved relationship between DPOP and PPV. Although a limited cohort of seven volunteers was used, the results suggest that DPOP may be useful as a respiratory effort parameter, given that the fluid level of the patient is maintained at a constant level over the period of analysis.

A Review of Wavelet Transform Time-Frequency Methods for NIRS-Based Analysis of Cerebral Autoregulation

Near-infrared spectroscopy (NIRS) has been proposed as a suitable technique for the analysis of cerebral autoregulation as it provides a simpler acquisition methodology and more artifact-free signal. A number of sophisticated wavelet transform methods have recently emerged to quantify the cerebral autoregulation mechanism using NIRS and blood pressure signals. These provide an enhanced partitioning of signal information via the time-frequency plane, which facilitates improved extraction of the components of interest. This area is reviewed, and enhancements to this form of analysis are suggested.

On better estimating and normalizing the relationship between clinical parameters: comparing respiratory modulations in the photoplethysmogram and blood pressure signal (DPOP versus PPV)

DPOP (ΔPOP or Delta-POP) is a noninvasive parameter which measures the strength of respiratory modulations present in the pulse oximeter waveform. It has been proposed as a noninvasive alternative to pulse pressure variation (PPV) used in the prediction of the response to volume expansion in hypovolemic patients. We considered a number of simple techniques for better determining the underlying relationship between the two parameters. It was shown numerically that baseline-induced signal errors were asymmetric in nature, which corresponded to observation, and we proposed a method which combines a least-median-of-squares estimator with the requirement that the relationship passes through the origin (the LMSO method). We further developed a method of normalization of the parameters through rescaling DPOP using the inverse gradient of the linear fitted relationship. We propose that this normalization method (LMSO-N) is applicable to the matching of a wide range of clinical parameters. It is also generally applicable to the self-normalizing of parameters whose behaviour may change slightly due to algorithmic improvements.

Calculation of the Respiratory Modulation of the Photoplethysmogram (DPOP) Incorporating a Correction for Low Perfusion

DPOP quantifies respiratory modulations in the photoplethysmogram. It has been proposed as a noninvasive surrogate for pulse pressure variation (PPV) used in the prediction of the response to volume expansion in hypovolemic patients. The correlation between DPOP and PPV may degrade due to low perfusion effects. We implemented an automated DPOP algorithm with an optional correction for low perfusion. These two algorithm variants (DPOPa and DPOPb) were tested on data from 20 mechanically ventilated OR patients split into a benign "stable region" subset and a whole record "global set." Strong correlation was found between DPOP and PPV for both algorithms when applied to the stable data set: R = 0.83/0.85 for DPOPa/DPOPb. However, a marked improvement was found when applying the low perfusion correction to the global data set: R = 0.47/0.73 for DPOPa/DPOPb. Sensitivities, Specificities, and AUCs were 0.86, 0.70, and 0.88 for DPOPa/stable region; 0.89, 0.82, and 0.92 for DPOPb/stable region; 0.81, 0.61, and 0.73 for DPOPa/global region; 0.83, 0.76, and 0.86 for DPOPb/global region. An improvement was found in all results across both data sets when using the DPOPb algorithm. Further, DPOPb showed marked improvements, both in terms of its values, and correlation with PPV, for signals exhibiting low percent modulations.