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Routine monitoring of blood pressure during general anaesthesia relies on intermittent measurements with a non-invasive brachial cuff every five minutes. This manuscript provides first experimental evidence that a physiology-based pulse wave analysis algorithm applied to optical data (as provided by a standard fingertip pulse oximeter) is capable of accurately estimating blood pressure changes in-between cuff readings. Combined with the routine use of oscillometric cuffs, the presented novel approach is a candidate technology to increase patient safety by providing beat-to-beat hemodynamic measurements without the need of invasive monitoring procedures.
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Current Directions in Biomedical Engineering 2016; 2(1): 267–271
Open Access
Josep Solà*, Martin Proença, Fabian Braun, Nicolas Pierrel, Yan Degiorgis, Christophe Verjus,
Mathieu Lemay, Mattia Bertschi and Patrick Schoettker
Continuous non-invasive monitoring of blood
pressure in the operating room: a culess optical
technology at the ngertip
DOI 10.1515/cdbme-2016-0060
Abstract: Routine monitoring of blood pressure during
general anaesthesia relies on intermittent measurements
with a non-invasive brachial cu every ve minutes. This
manuscript provides rst experimental evidence that a
physiology-based pulse wave analysis algorithm applied
to optical data (as provided by a standard ngertip pulse
oximeter) is capable of accurately estimating blood pres-
sure changes in-between cu readings. Combined with
the routine use of oscillometric cus, the presented novel
approach is a candidate technology to increase patient
safety by providing beat-to-beat hemodynamic measure-
ments without the need of invasive monitoring proce-
Keywords: beat-to-beat; blood pressure; cuess; general
anesthesia; operating room; pulse wave analysis.
Blood pressure and heart rate monitoring belong to the
minimal standards for basic anaesthetic monitoring [1].
Still today, the non-invasive measurement of blood pres-
sure is performed with brachial ination cus placed
around the arm. However, these devices only provide
intermittent measurements of blood pressure during the
interventions, i.e. every 2–5 min. For patient safety rea-
sons, beat-to-beat blood pressure readings are manda-
tory in critical patients during long and complex inter-
ventions. Unfortunately, the routine procedure to obtain
*Corresponding author: Josep Solà, CSEM Centre Suisse
d’Electronique et Microtechnique, Jacquet-Droz 1, CH-2002
Neuchâtel, Switzerland, E-mail:
Martin Proença, Fabian Braun, Christophe Verjus, Mathieu Lemay
and Mattia Bertschi: CSEM Centre Suisse d’Electronique et
Microtechnique, Jacquet-Droz 1, CH-2002 Neuchâtel, Switzerland
Nicolas Pierrel, Yan Degiorgis and Patrick Schoettker: CHUV
Centre Hospitalier Universitaire Vaudois, Rue du Bugnon 46,
CH-1011 Lausanne, Switzerland
reliable continuous blood pressure readings relies on
arterial invasive catheters, with their non-negligible asso-
ciated morbidity issues [2]. Non-invasive and continuous
blood pressure measurement devices have been tested
in the past, but their accuracy and reliability have been
repeatedly questioned [3], in particular when aiming at
replacing existing procedures. Even more, high costs and
cumbersomeness of existing non-invasive beat-by-beat
devices impede their introduction into daily anaesthesia
This manuscript presents rst experimental evidence
on the feasibility of tracking beat-by-beat changes of blood
pressure in humans during induction of general anaes-
thesia by simple optical means. The presented technol-
ogy relies on the physiological analysis of transmission
photoplethysmographic signals measured at the ngertip.
Such signals are recorded by commercial pulse oxime-
ters, which are routinely applied to almost every patient.
While the presented approach does not aim at replacing
oscillometric gold-standard monitoring, it introduces an
appealing approach to continuously estimate blood pres-
sure measurements in-between two cu inations, thus
allowing the detection of sudden blood pressure changes
and thereby increasing the patient’s safety.
Because no additional monitoring equipment is
required in the operating room, this optical technology
appears as an appealing candidate to improve non-
invasive monitoring capabilities during general anaesthe-
sia. Figure 1 illustrates the status of the novel technology
within the constellation of existing monitoring means in
the operating room.
The clinical study ( NCT02651558)
described in this section is compliant with all relevant
Swiss ethics, regulations and institutional policies and
in accordance with the tenets of the Helsinki Declaration.
©2016 Josep Solà et al., licensee De Gruyter.
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License.
268 |J. Solà et al.: Continuous non-invasive monitoring of blood pressure in the operating room
Figure 1: Summary of available blood pressure (BP) monitoring
technologies in the operating room.
Informed consent was obtained from all individuals before
enrolment at CHUV University Hospital of Lausanne.
Patients were placed on the operating table and mon-
itoring was carried out via the Philips monitor IntelliVue
MX800. Monitoring consisted of a 3-lead electrocardio-
gram, non-invasive blood pressure cu measurements
at the left arm and oxygen ngertip saturation readings
at the right index. Under local anaesthesia, a dedicated
catheter (BD Arterial Cannula 20G/1.1 mm ×45 mm, Bec-
ton Dickinson Infusion Therapy Syst. Inc., UT, USA) was
inserted into the right radial artery, allowing beat-to-beat
continuous blood pressure monitoring. General anaesthe-
sia was then provided by the anaesthetist in charge of
the patient, in accordance with the standard practice of
the department: propofol (2 mg/kg) for induction, fen-
tanyl (3 µg/kg) for analgesia, and rocuronium (0.6 mg/kg)
for neuromuscular blockade; endotracheal intubation
Recording of continuous invasive blood pressure
signals, non-invasive ngertip photoplethysmographic
signals (i.e. Pleth Wave), and electrocardiogram was per-
formed at 500 Hz by ixTrend® software for Philips In-
telliVue monitors. As the clinical study is ongoing, only
the rst three patients showing good raw signal quality
(by an unsupervised quality index) were used to show rst
experimental evidence.
3.1 Overall methodology
The novel optical technology relies on the extraction of
physiology-based pulse wave analysis (PWA) features from
raw transmission photoplethysmographic signals. These
physiological features are later projected into blood pres-
sure values by means of intermittent oscillometric mea-
surements provided by a brachial cu (see Figure 2).
3.2 Extraction of PWA features
Raw photo-plethysmographic signals are acquired by a
ngertip pulse oximetry probe. While for the current study
a commercial transmission probe is used, any other means
to acquire a surrogate measure for peripheral arterial pul-
satility is adapted for this methodology.
After a pre-processing and denoising procedure, a
PWA technique is applied to each arterial pulse [4]. The
implemented PWA algorithm extracts features from each
pulse based on the wave reection theory of the arterial
system [5]. The algorithm assumes that arterial pulses
propagate along the arterial tree being reected at each ar-
terial branching. The resulting arterial pulses are thus the
superposition of forward and backward waves interfering
at various locations of the arterial tree.
Given the arterial topology of a particular patient,
changes in blood pressure modify the velocity at which
arterial pulses propagate, reshaping the individual mix-
ture of incident and reected waves. These morphological
changes are quantied via the implemented PWA algo-
rithm as modications of the patients’ arterial pulsatility
patterns. Pulsatility pattern changes are indirect indica-
tors of the underlying changes in propagation charac-
teristics, and thus, of the underlying changes of central
blood pressure. Therefore the outcome of the implemented
PWA algorithm is a vector of physiologically meaningful
Figure 2: Overall methodology: blood pressure estimates
interpolate patient’s hemodynamic changes in-between two
oscillometric measurement.
J. Solà et al.: Continuous non-invasive monitoring of blood pressure in the operating room |269
features containing information on the patient’s central
blood pressure status.
3.3 Calibration to brachial cu values
While containing meaningful physiological information,
the feature vector extracted from the PWA algorithm does
not yet relate to blood pressure values in mm Hg.
In the context of a methodology to extract beat-
to-beat blood pressure estimates in-between two cu
measurements a dedicated (re-)calibration algorithm is
thus needed. The aim of this algorithm is to map
subject-dependent changes of the PWA feature vector
xiinto actual changes of blood pressure. During each
Figure 3: Performance of the culess blood pressure estimation
technique on a particular study patient during induction of
anesthesia. Each data point corresponds a patient’s heart beat.
Temporal evolution of invasive systolic blood pressure is displayed
as ±8 mm Hg range (shaded in grey).
recalibration at instant i, the availability of intermittent
cu-based measurements yiis used as a reference to
re-estimate the parameters
piof a mapping function fas it
is depicted by equation 1. A forgetting factor λcan be used
to smooth pressure estimates in time.
pi1+λargmin piyif(pi,xi)2(1)
4Results and discussion
Based on the previously described methodology, rst ex-
perimental evidence on the performance of the novel cuf-
ess technique is provided here. Figures 3–5 illustrate
Figure 4: Performance of the culess blood pressure estimation
technique on a particular study patient during induction of
anesthesia. Each data point corresponds a patient’s heart beat.
Temporal evolution of invasive systolic blood pressure is displayed
as ±8 mm Hg range (shaded in grey).
270 |J. Solà et al.: Continuous non-invasive monitoring of blood pressure in the operating room
Figure 5: Performance of the culess blood pressure estimation
technique on a particular study patient during induction of
anesthesia. Each data point corresponds a patient’s heart beat.
Temporal evolution of invasive systolic blood pressure is displayed
as ±8 mm Hg range (shaded in grey).
the results of cuess systolic blood pressure estimations
compared to invasive reference measurements. Each gure
corresponds to data recorded during induction of anaes-
thesia on one patient. Each data point in these gures cor-
responds to a single heartbeat. Calibration with reference
measurement was performed every 5 min.
The rst row in each gure depicts correlation plots
between invasive systolic blood pressure values and heart
rate estimates (left plot) or cuess blood pressure esti-
mates (right plot), respectively. Note that in current clinical
practice, when only intermittent blood pressure measure-
ments are available, anaesthetists fully rely on heart rate
measurements to infer blood pressure changes.
The second row in each gure depicts Bland-Altman
plots when comparing invasive systolic blood pressure
values against cuess blood pressure estimates. Due to
the re-calibration procedures, overall bias are within a
reasonable range (|µ|<4 mm Hg). Standard errors of the
estimates σare all smaller than 8 mm Hg, and thus comply
with the specications of the AAMI standard [6].
The third row in each gure depicts the tempo-
ral evolution of invasive systolic blood pressure during
anesthesia induction (±8 mm Hg range shaded in grey),
and simultaneous cuess estimates. Note that calibration
periods are illustrated by black boxes marked as “CAL”.
It is important to note that the novel cuess method
was able to detect blood pressure changes in between
calibration periods for all the three patients analyzed.
This manuscript presented rst experimental evidence for
the feasibility of estimating blood pressure changes in the
operating room by means of a simple optical probe at the
ngertip, which is routinely applied to every patient.
During all anaesthetic procedures and surgeries, the
patient’s oxygenation, ventilation, circulation and tem-
perature must be continuously monitored. To cope with
these requirements, and in order to increase patients’
safety, international standards for safe practice of anaes-
thesia have been implemented and consist of cumbersome
While comprehensive statistical analysis of the perfor-
mances of the novel approach will be presented at nalisa-
tion of the ongoing clinical study, these preliminary results
support the hypothesis that physiology-based PWA algo-
rithms applied to standard photo-plethysmographic sig-
nals might contain sucient information to deduce blood
pressure changes during general anaesthesia, without the
need of additional monitoring equipment.
Technological advances such as the one herein pre-
sented appear as an interesting alternative, aiming at sim-
plifying patient access, and potentially decreasing mor-
bidity associated to invasive monitoring in the operating
Authors’ Statement
Research funding: The author state no funding involved.
Conict of interest: Authors state no conict of interest.
Material and Methods: Informed consent: Informed con-
sent is not applicable. Ethical approval: The conducted
research is not related to either human or animal use.
J. Solà et al.: Continuous non-invasive monitoring of blood pressure in the operating room |271
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Monitoring, 2015.
[2] Polanco PM, Pinsky MR. Practical Issues of hemodynamic
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[3] Kim SH, Lilot M, Sidhu KS, Rinehart J, Yu Z, Canales C, et al.
Accuracy and precision of continuous noninvasive arterial
pressure monitoring compared with invasive arterial pressure.
Anesthesiology. 2014;120:1080–97.
[4] Proença M, Solà J, Lemay M, Verjus C. CSEM. Method,
apparatus and computer program for determining a blood
pressure value. PCT/EP 2015/063765. 2015.
[5] Nichols W, O’Rourke M, Vlachopoulos C. McDonald’s blood flow
in arteries: theoretical, experimental and clinical principles.
CRC Press; 2011, ISBN 9780340985014.
[6] AAMI. Non-invasive sphygmomanometers part 2: clinical
investigation of automated measurement type, ANSI/AAMI/ISO
... De nombreux modèles basés sur un apprentissage à partir d'un jeu de données ont été proposés comme dans [93,102] où une régression linéaire (LR) a été utilisée afin de prédire la pression artérielle. Les caractéristiques temporelles utilisées par [108] et [102] ne semblent pas être liées linéairement à la pression artérielle. ...
... En outre, malgré le protocole bien établi des dispositifs médicaux actuels dédiés à l'estimation de la PA, les nouvelles possibilités de mesure de celle-ci par la technique de photolethysmographie ont été prises en considération récemment ( [58],IEEE Std 1708™ [60]). On peut remarquer que [93] n'avait aucun moyen de certifier ses résultats car c'est un travail précurseur sur l'estimation de la PA en continu. Dans le contexte de l'IdO, il y a une phase importante dans le traitement du signal qui a souvent été ignorée. ...
La Société Européenne de Cardiologie a mis en avant l’intérêt d’observer l’activité chronique de la fréquence cardiaque, de la rigidité artérielle et de la pression artérielle afin de diagnostiquer le plus tôt possible les maladies cardiovasculaires qui représentent une cause majeure de décès dans le monde. Dans ce contexte, les travaux présentés dans ce manuscrit se proposent d’apporter un éclairage particulier sur la possibilité de l’estimation de la pression artérielle à partir du signal d’onde de pouls délivré par un capteur photopléthysmographique (PPG) présent sur un bracelet ou montre connectée. Quatre contributions originales de ce travail de recherche méritent d’être mentionnées brièvement ci-après : la première porte sur une étude comparative objective des caractéristiques temporelles du signal PPG recensées dans la littérature scientifique pour la prédiction de la pression artérielle mais aussi de nouvelles caractéristiques que l’on a proposé dans ce mémoire à partir de différentes considérations. La deuxième contribution concerne l’utilisation d’un algorithme de prédiction linéaire exploitant le modèle PLS (Projection in Latent Structures) ce qui a permis d’avoir un aperçu plus détaillé de l’apport des différentes caractéristiques temporelles du signal PPG à la prédiction de la pression artérielle que ce soit dans un contexte expérimental (mesures de pression artérielle en invasif) ou applicatif (mesures de pression artérielle en non-invasif). La troisième contribution est représentée par une base de données que l’on a créé spécifiquement pour avoir des variations significatives de pression artérielle et qui pourrait devenir, on l’espère, une base de données de type benchmark afin d’évaluer la capacité du système de prédiction à capturer ces fluctuations. La quatrième contribution porte sur l’élaboration d’un nouveau protocole expérimental permettant d’induire une assez forte variation de la pression artérielle sur une relativement courte période de temps afin de mettre en évidence l’essentiel de la dynamique des caractéristiques hémodynamiques spécifiques au sujet considéré et ainsi de mieux calibrer les modèles d’estimation de la pression artérielle.
... Contact PPG sensors have been widely used for PWA-based BP monitoring. The form factors used include a finger clip (Xing et al., 2019;Ruiz-Rodríguez et al., 2013;Xing and Sun, 2016;Watanabe et al., 2017;Solà et al., 2016;, wristwatch (Atomi et al., 2017;Radha et al., 2019), and smartphone camera (Schoettker et al., 2020) to list a few. Infrared PPG devices may offer the most robust waveform but at the cost of limited availability, whereas green PPG devices on the backside of smartwatches may be most convenient but at the cost of low signal quality. ...
... In some studies, morphological and characteristic features in the PPG waveform were used to classify BP (e.g., to determine hypertension vs. normotension) based on techniques such as logistic regression, AdaBoost tree, bagged tree, LSTM, and K nearest neighbors (KNN) Khalid et al., 2020;Tjahjadi et al., 2020). One study examined the recalibration of the mapping by way of a recursive estimation technique (Solà et al., 2016). However, the time period required for recalibration of the hybrid method with a cuff BP measurement is largely unknown. ...
Clinical management of hypertension and hypotension has been hindered by current cuff blood pressure (BP) measurement devices, which are not always readily available or continuous and can be disruptive to the user. Photoplethysmography (PPG) is a simple yet effective tool for tracking pulsatile arterial blood volume changes that can improve BP measurement. Volume clamping via finger cuff-PPG devices is a proven continuous method, whereas oscillometry via PPG-force sensor units, pulse transit time detected via PPG waveform(s), and PPG waveform feature extraction are potential cuff-less methods. The objective of this chapter is to facilitate the advancement of PPG-based BP monitoring. First, the clinical BP measurement methods and their limitations are explained. Then, the PPG principle and available sensors are reviewed. Next, the four PPG-based BP measurement methods are described including principles, embodiments, and empirical evidence. Finally, these methods are compared, future research directions are pinpointed, and a brief outlook on the approach is provided.
... 58 In 2011, Monte-Moreno 31 demonstrated that age, weight, body mass index (BMI), and PPG signal could be used by ML to predict BP in 410 subjects. Similarly, Solà et al. 32 studied the ability of ANN to estimate BP from PPG signal in patients undergoing surgery with general anesthesia, and revealed that ANN could estimate BP with less than 8 mm Hg different from invasive radial artery BP measurement. Miao et al. 33 demonstrated that ML with support vector machine algorithms was able to analyze data from electrocardiogram and PPG signal obtained from 73 subjects for estimating SBP and diastolic blood pressure (DBP) with mean error −0.001 ± 3.102 and −0.004 ± 2.199 mm Hg, respectively. ...
... 27,28 Predicting blood pressure -Predict BP from demographic data, lifestyle (alcohol, smoking, and exercise), 29 and retinal fundus images. 30 Measuring Blood Pressure -Estimate BP by analyzing PPG signal from pulse oximeter with ML algorithms [31][32][33][34][35][36] and DL algorithms. 37,38 -Estimate BP from PPG signal recorded by a smartphone 39 and a smartwatch. ...
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Prevention and treatment of hypertension (HTN) is a challenging public health problem. Recent evidence suggests that artificial intelligence (AI) has potential to be a promising tool for reducing the global burden of HTN, and furthering precision medicine related to cardiovascular (CV) diseases including HTN. Since AI can stimulate human thought processes and learning with complex algorithms and advanced computational power, AI can be applied to multimodal and big data, including genetics, epigenetics, proteomics, metabolomics, CV imaging, socioeconomic, behavioral and environmental factors. AI demonstrates the ability to identify risk factors and phenotypes of HTN, predict the risk of incident HTN, diagnose HTN, estimate blood pressure (BP), develop novel cuffless methods for BP measurement, and comprehensively identify factors associated with treatment adherence and success. Moreover, AI has also been used to analyze data from major randomized controlled trials exploring different BP targets to uncover previously undescribed factors associated with cardiovascular outcomes. Therefore, AI-integrated HTN care has the potential to transform clinical practice by incorporating personalized prevention and treatment approaches, such as determining optimal and patient specific BP goals, identifying the most effective antihypertensive medication regimen for an individual, and developing interventions targeting modifiable risk factors. Although the role of AI in HTN has been increasingly recognized over the past decade, it remains in its infancy, and future studies with big data analysis and N-of-1 study design are needed to further demonstrate the applicability of AI in HTN prevention and treatment.
... The algorithms underlying OptiBP TM were first validated in operating room settings using the sensor lens found on pulse oximeters 11,12 . This BP estimation technique was subsequently migrated onto smartphone camera lenses to facilitate more common use. ...
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Undetected and unmonitored hypertension carries substantial mortality and morbidity, especially during pregnancy. We assessed the accuracy of OptiBP TM , a smartphone application for estimating blood pressure (BP), across diverse settings. The study was conducted in community settings: Gaibandha, Bangladesh and Ifakara, Tanzania for general populations, and Kalafong Provincial Tertiary Hospital, South Africa for pregnant populations. Based on guidance from the International Organization for Standardization (ISO) 81,060–2:2018 for non-invasive BP devices and global consensus statement, we compared BP measurements taken by two independent trained nurses on a standard auscultatory cuff to the BP measurements taken by a research version of OptiBP TM called CamBP. For ISO criterion 1, the mean error was 0.5 ± 5.8 mm Hg for the systolic blood pressure (SBP) and 0.1 ± 3.9 mmHg for the diastolic blood pressure (DBP) in South Africa; 0.8 ± 7.0 mmHg for the SBP and −0.4 ± 4.0 mmHg for the DBP in Tanzania; 3.3 ± 7.4 mmHg for the SBP and −0.4 ± 4.3 mmHg for the DBP in Bangladesh. For ISO criterion 2, the average standard deviation of the mean error per subject was 4.9 mmHg for the SBP and 3.4 mmHg for the DBP in South Africa; 6.3 mmHg for the SBP and 3.6 mmHg for the DBP in Tanzania; 6.4 mmHg for the SBP and 3.8 mmHg for the DBP in Bangladesh. OptiBP TM demonstrated accuracy against ISO standards in study populations, including pregnant populations, except in Bangladesh for SBP (criterion 2). Further research is needed to improve performance across different populations and integration within health systems.
... Environmental factors, physical activity, and psychological stress all influence BP and HR. With the aim of increasing patient safety in the operating room, WD has also been applied to continuous BP monitoring to detect sudden changes in BP [12]. Although the accuracy of WD for HR during physical activity was presented in some studies, there has not been enough information on the accuracy it for BP. ...
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The aim of this preliminary study was to measure the systolic BP (SBP) and diastolic BP (DBP) and heart rate (HR) of radiological technologists by WD, and evaluate variation among individuals by worktime, day of the week, job, and workplace. Measurements were obtained using a wristwatch-type WD with optical measurement technology that can measure SBP and DBP every 10 minutes and HR every 30 minutes. SBP, DBP, and HR data obtained at baseline and during work time were combined with the hours of work, day of the week, job, and workplace recorded by the participants in 8 consecutive weeks. We calculated the mean, the ratio to baseline and coefficient of variation [CV(%)] for SBP, DBP, and HR. SBP, DBP, and HR values were significantly higher during work hours than at baseline (p<0.03). The ratio to baseline values ranged from 1.02 to 1.26 for SBP and from 1.07 to 1.30 for DBP. The ratio to baseline for SBP and DBP showed CV(%) of approximately 10% according to the day of the week and over the study period. For HR, ratio to baseline ranged from 0.95 to 1.29. The ratio of mean BP to baseline was >1.2 at the time of starting work, middle and after lunch, and at 14:00. The ratio to baseline of SBP were 1.2 or more for irradiation, equipment accuracy control, registration of patient data, dose verification and conference time, and were also working in CT examination room, treatment planning room, linac room, and the office. CV(%) of BP and HR were generally stable for all workplaces. WD measurements of SBP, DBP, and HR were higher during working hours than at baseline and varied by the individuals, work time, job, and workplace. This method may enable evaluation of unconscious workload in individuals.
... In ref. [17], Solà and colleagues report on the use of a physiology-based pulse wave analysis algorithm to optical data coming from a fingertip pulse oximeter. They conclude that this algorithm is able to estimate with good accuracy blood pressure changes in-between cuff readings. ...
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One of the most important physiological parameters of the cardiovascular circulatory system is Blood Pressure. Several diseases are related to long-term abnormal blood pressure, i.e., hypertension; therefore, the early detection and assessment of this condition are crucial. The identification of hypertension, and, even more the evaluation of its risk stratification, by using wearable monitoring devices are now more realistic thanks to the advancements in Internet of Things, the improvements of digital sensors that are becoming more and more miniaturized, and the development of new signal processing and machine learning algorithms. In this scenario, a suitable biomedical signal is represented by the PhotoPlethysmoGraphy (PPG) signal. It can be acquired by using a simple, cheap, and wearable device, and can be used to evaluate several aspects of the cardiovascular system, e.g., the detection of abnormal heart rate, respiration rate, blood pressure, oxygen saturation, and so on. In this paper, we take into account the Cuff-Less Blood Pressure Estimation Data Set that contains, among others, PPG signals coming from a set of subjects, as well as the Blood Pressure values of the latter that is the hypertension level. Our aim is to investigate whether or not machine learning methods applied to these PPG signals can provide better results for the non-invasive classification and evaluation of subjects’ hypertension levels. To this aim, we have availed ourselves of a wide set of machine learning algorithms, based on different learning mechanisms, and have compared their results in terms of the effectiveness of the classification obtained.
Rapid advancements in sensor technology in recent years have resulted in the production of high-performance, sensors for human health monitoring. As human health is of the highest significance, several high-tech tools for continuous health monitoring have been created. The favorable characteristics of sensors make them a suitable option for medical applications. Sensors can monitor and measure specific parameters of a human such as a heartbeat, pressure, glucose level, and temperature. Furthermore, advance sensors can detect severe diseases in their early stages (e.g., cancer) for prompt treatments. To ensure better healthcare, continuous monitoring of health-related parameters is essential. This review aims to summarize the recent developments in sensor technologies for monitoring health-related conditions. Sensors are now influencing health care systems and medicine by providing health monitoring outside of the medical centers and health event prediction. This study examines present and future technological advancements in health condition monitoring-related sensors. Moreover, it discusses research, explains common, commercially accessible sensors and early-phase devices, and briefly outlines recently developed materials and fabrication processes used for sensor development.
Purpose of review: Nonoperating room anesthesia (NORA) procedures continue to increase in type and complexity as procedural medicine makes technical advances. Patients presenting for NORA procedures are also older and sicker than ever. Commensurate with the requirements of procedural medicine, anesthetic monitoring must meet the American Society of Anesthesiologists standards for basic monitoring. Recent findings: There have been improvements in the required monitors that are used for intraoperative patient care. Some of these changes have been with new technologies and others have occurred with software refinements. In addition, specialized monitoring devises have also been introduced into NORA locations (depth of hypnosis, respiratory monitoring, point-of care ultrasound). These additions to the monitoring tools available to the anesthesiologist working in the NORA-environment push the boundaries of procedures which may be accomplished in this setting. Summary: NORA procedures constitute a growing percentage of total administered anesthetics. There is no difference in the monitoring standard between that of an anesthetic administered in an operating room and a NORA location. Anesthesiologists in the NORA setting must have the same compendium of monitors available as do their colleagues working in the operating suite.
Arterial blood pressure is one of the most often measured vital parameters in clinical practice. State-of-the-art noninvasive ABP measurement technologies have noticeable limitations and are mainly based on uncomfortable techniques of complete or partial arterial occlusion by cuffs. Most commonplace devices provide only intermittent measurements, and continuous systems are bulky and difficult to apply correctly for nonprofessionals. Continuous cuffless ABP measurements are still an unmet clinical need and a topic of ongoing research, with only few commercially available devices. This paper discusses surrogate-based noninvasive blood pressure measurement techniques. It covers measurement methods of continuously and noninvasively inferring BP from surrogate signals without applying external pressures, except for reference or initialization purposes. The BP is estimated by processing signal features, so called surrogates, which are modulated by variations of BP. Discussed techniques include well-known approaches such as pulse transit time and pulse arrival time techniques, pulse wave analysis or combinations thereof. Despite a long research history, these methods have not found widespread use in clinical and ambulatory practice, in part due to technical limitations and the lack of a standardized regulatory framework. This work summarizes findings from an invited workshop of experts in the fields covering clinical expertise, engineering aspects, commercialization and standardization issues. The goal is to provide an application driven outlook, starting with clinical needs, and extending to technical actuality. It provides an outline of recommended research directions and includes a detailed overview of clinical use case scenarios for these technologies, opportunities, and limitations.
The hemodynamic monitoring of a surgical patient acquires a major relevance in high-risk patients and those suffering from surgical diseases associated with hemodynamic instability, such as hemorrhagic or septic shock. This article reviews the fundamental physiologic principles needed to understand hemodynamic monitoring at the bedside. Monitoring defines stability, instability, and response to therapy. The major hemodynamic parameters measured and derived from invasive hemodynamic monitoring, such as arterial, central venous, and pulmonary catheterization, are discussed, as are its clinical indications, benefits, and complications. The current clinical data relevant to hemodynamic monitoring are reviewed and discussed.
Accuracy and precision of continuous noninvasive arterial pressure monitoring compared with invasive arterial pressure
  • S H Kim
  • M Lilot
  • K S Sidhu
  • J Rinehart
  • Z Yu
  • C Canales
S.H. Kim, et al. Accuracy and Precision of Continuous Noninvasive Arterial Pressure Monitoring Compared with Invasive Arterial Pressure, Anesthesiology 2014;120:1080-97
Verjus. CSEM. Method, apparatus and computer program for determining a blood pressure value
  • M Proença
  • J Solà
  • M Lemay
M. Proença, J. Solà, M. Lemay, C. Verjus. CSEM. Method, apparatus and computer program for determining a blood pressure value. PCT/EP 2015/063765. 2015.
Method, apparatus and computer program for determining a blood pressure value
  • M Proença
  • J Solà
  • M Lemay
  • C Verjus
  • Csem
Non-invasive sphygmomanometers - part 2: clinical investigation of automated measurement type
  • Aami
AAMI. Non-invasive sphygmomanometers -Part 2: Clinical investigation of automated measurement type, ANSI/AAMI/ISO 81060-2:2013