Oximeter Sensor Research Articles

1805 Oxygen Saturation Monitoring at Birth: Feasibility of the 2010 Neonatal Resuscitation Guidelines

BackgroundThe 2010 Neonatal Resuscitation Guidelines recommend preductal transcutaneous oxygen saturation (SpO2) monitoring at birth.ObjectiveTo verify the feasibility of SpO2 monitoring at birth by determining the time to get the first...

An assessment of the accuracy of pulse oximeters

Peripheral pulse oximetry has become a core monitoring modality in most fields of medicine. Pulse oximeters are used ubiquitously in operating theatres, hospital wards, outpatient clinics and general practice surgeries. This study used a portable spectrometer (Lightman(®), The Electrode Co. Ltd., Monmouthshire, UK) to measure the emission spectra of the two light emitting diodes within the pulse oximeter sensor and to determine the accuracy of 847 pulse oximeters currently in use in 29 NHS hospitals in the UK. The standard manufacturing claim of accuracy for pulse oximeters is ± 2-3% over the range of 70-100% S(p)O(2). Eighty-nine sensors (10.5%) were found to have a functional error of their electrical circuitry that could cause inaccuracy of measurement. Of the remaining 758 sensors, 169 (22.3%) were found to have emission spectra different from the manufacturers' specification that would cause an inaccuracy in saturation estimation of > 4% in the range of 70-100% saturation. This study has demonstrated that a significant proportion of pulse oximeter sensors may be inaccurate.

Determining the best method of Nellcor pulse oximeter sensor application in neonates

To identify the optimal sensor application method that gave the quickest display of accurate heart rate (HR) data using the Nellcor OxiMax N-600x pulse oximeter (PO). Stable infants who were monitored with an electrocardiograph were included. Three sensor application techniques were studied: (i) sensor connected to cable, then applied to infant; (ii) sensor connected to cable, applied to investigator's finger, and then to infant; (iii) sensor applied to infant, then connected to cable. The order of techniques tested was randomized for each infant. Time taken to apply the PO sensor, to display data and to display accurate data (HR(PO) = HR(ECG) ± 3 bpm) were recorded using a stopwatch. Forty infants were studied [mean (SD) birthweight, 1455 (872) g; gestational age, 31 (4) weeks; post-menstrual age, 34 (4) weeks]. Method 3 acquired any data significantly faster than methods 1 (p = 0.013; CI, -9.6 to -3.0 sec) and 2 (p = 0.004; CI, -5.9 to -1.2 sec). Method 3 acquired accurate data significantly faster than method 1 (p = 0.016; CI, -9.4 to -1.0 sec), but not method 2 (p = 0.28). Applying the sensor to the infant before connecting it to the cable yields the fastest acquisition of accurate HR data from the Nellcor PO.

Transferring Infants < 32 Weeks' Gestation from the Delivery Room to the NICU. How Vigilant are we in Avoiding Hypoxia/Hyperoxia During the First “Golden Hour”?

Background: Clinicians know about the dangers of hyperoxia and hypoxia in the delivery room and NICU. Less attention is paid to the period of transport and early stabilisation in the NICU. We aimed to investigate the time spent with SpO2 85-94% during the first hour after birth. Method: A prospective observational study of clinical practice was undertaken. Infants < 32 weeks gestation were enrolled. A pulse oximeter (PO) sensor was applied to the right hand after birth, remaining connected until 60 minutes after birth. Clinical interventions were recorded during this time and matched with PO SpO2 data for analysis. Hyperoxic periods were only analysed when FiO2>0.21. Clinicians were unaware of the aims of the study. Results: 32 infants were studied, mean (SD) birth weight 1101(330)g, gestational age 29(2) weeks. Median(IQR) time spent in the transport cot and NICU were 9(7-11)min and 30(27-33)min respectively, and time babies spent with SpO2>94% if receiving supplemental oxygen was 2.6(1.5-4.6)min and 5.4(2.1-9.1)min respectively. Table The proportion of time with SpO2>94% during Transport and NICU was similar. Babies managed with CPAP compared to intubated infants had a greater proportion of time with SpO2>94% in transport and the NICU setting. Conclusions: SpO2 measurements often fell outside the target range during the early postnatal period. Clinicians tolerate saturations higher than the “safe” range during the first hour after birth

Comparison of Oxygen Saturation and Heart Rate (HR) Measurements from Masimo and Nellcor Pulse Oximeters in Newly Born Infants

Background: Pulse oximetry is increasingly used in delivery rooms (DRs). Little is known about the newest generation of Nellcor oximeters, the Nellcor Oximax N-600x. We compared:□ HR measurements from Nellcor (HRNellcor) and Masimo oximeters (HRMasimo), against HR measured via three-lead electrocardiogram (ECG) (HRECG)□ Oxygen saturation (SpO2) measurements between the Nellcor (SpO2Nellcor) and Masimo (SpO2Masimo) oximetersMethods: Infants born via elective caesarean section were studied. ECG leads were placed on the infant's chest. Masimo and Nellcor oximeter sensors were randomly allocated to each foot. Measurements were collected for 10mins. Screens from the oximeters and ECG monitor were video recorded. Data was extracted by pausing the video every 2s to record HR and SpO2 measurements, and signal quality. The Bland-Altman method was used to determine agreement between HR measurements from the ECG and oximeters, and between SpO2 measurements from each oximeter.Results: We studied 44 infants of mean(SD) gestational age 38(1) weeks, birth weight 3246(527) grams, and median(IQR) Apgar scores of 9(9) at 1 and 5 minutes. Four infants received resuscitation. The numbers of paired observations were: ECG and Nellcor PO: 9422; ECG and Masimo PO: 8694; Nellcor and Masimo POs: 8382.The mean difference (± 2SD) between HRECG and HRNellcor was -0.8bpm (±11bpm); between HRECG and HRMasimo was 0.2bpm (±9bpm); and between HRMasimo and HRNellcor was -0.8bpm (±9bpm). The mean (±2SD) difference between SpO2Masimo and SpO2Nellcor was -3% (±15%).Conclusion: Both oximeters measure HR accurately, i.e. within 1bpm of HRECG. There was good agreement between HR and SpO2 measurements of the oximeters.

Influence of the site of measurement on the ability of plethysmographic variability index to predict fluid responsiveness

Plethysmographic variability index (PVI) is an accurate predictor of fluid responsiveness in mechanically ventilated patients. However, the site of measurement of the plethysmographic waveform impacts its morphology and its respiratory variation. The goal of this study was to investigate the ability of PVI to predict fluid responsiveness at three sites of measurement (the forehead, ear, and finger) in mechanically ventilated patients under general anaesthesia. We studied 28 subjects after induction of general anaesthesia. Subjects were monitored with a pulmonary artery catheter and three pulse oximeter sensors (the finger, ear, and forehead). Pulse pressure variation, central venous pressure, cardiac index (CI), and PVI measured at the forehead, ear, and finger (PVI(forehead), PVI(ear), and PVI(finger)) were recorded before and after fluid loading (FL). Subjects were responders to volume expansion if CI increased >15% after FL. Areas under the receiver-operating curves to predict fluid responsiveness were 0.906, 0.880, and 0.836 for PVI(forehead), PVI(ear), and PVI(finger), respectively (P<0.05). PVI(forehead), PVI(ear), and PVI(finger) had a threshold value to predict fluid responsiveness of 15%, 16%, and 12% with sensitivities of 89%, 74%, and 74% and specificities of 78%, 74%, and 67%, respectively. PVI can predict fluid responsiveness in anaesthetized and ventilated subjects at all three sites of measurement. However, the threshold values for predicting fluid responsiveness differ with the site of measurement. These results support the use of this plethysmographic dynamic index in the cephalic region when the finger is inaccessible or during states of low peripheral perfusion.

Comments on ‘Evaluation of a pulse oximeter sensor tester’

The full extent of the inaccuracy of the inaccurate probes could not be demonstrated in this evaluation [1]; as data was only collected when clinical need required blood gas analysis. Each patient was monitored by a pulse oximeter system separate to a second pulse oximeter system used to gather trial data. The second pulse oximeter system comprised of a monitor, an accurate probe, an under-reading probe, and a high-reading probe. When the clinical need for blood gas analysis arose, the opportunity was taken to compare co-oximeter data with data obtained from the second pulse oximeter system by sequentially installing and taking readings from the accurate, low reading, and high reading probes. Pulse oximeter monitors display a SpO2 value that is a sophisticated average of the data collected over the preceding period. This technique reduces beat to beat variations and reduces the impact of other undesirable factors. When pulse oximeter probes are exchanged in rapid sequence the SpO2 value displayed on the monitor is influenced by the data in the monitor memory obtained by the preceding sensor. On loosing input/changing probes the monitor will have a ‘memory’ of the preceding readings. For sequential probes this results in the monitor displaying a SpO2 value that is calculated partially with data from the previous probe. The change from an ‘accurate’ to a ‘low reading probe’ will result in a SpO2 displayed on the monitor being skewed towards the initial ‘accurate’ data. Similarly the change from a ‘low reading probe’ to a ‘high reading probe’ will result in a SpO2 value displayed on the monitor being skewed towards the ‘low reading’ data. In aiming for ‘near simultaneous’ readings for blood gas and pulse oximetry the trial method could not allow for a time period long enough for full stabilisation each time a probe was changed. If blood gas analysis could have taken place for each independent fully stabilised pulse oximeter probe there would have been an even greater match between predictions and SpO2 accuracy levels. This would have required three times as many arterial blood samples than dictated by clinical need, and was therefore not an option available to the authors.

Comments on ‘evaluation of a pulse oximeter sensor tester’ – Authors’ response

We would like to thank Drs Mathews and Hickson for their comments. They seem to suggest that the accuracy of our SpO2 recordings was affected by the speed of change from one pulse oximeter probe to another during data collection process. Drs Mathews and Hickson suggest in their letter that the readings obtained on one SpO2 probe were affected by the reading from the previous SpO2 probe as the readings are averaged over the preceding period. They, however, did not specify the length of time ‘the preceding period’ refers too. We stated in our paper that the readings were recorded ‘when a stable plethysmograph waveform was obtained’ [1]. We assume that each probe required between 30 and 60 s for the SpO2 trace to stabilise before record of the SpO2 reading was made. All of our patients were stable at the time of data collection, so there was no need to rush. We consider 30 s to be sufficient time for the pulse oximeter monitor to ‘forget’ the data from the preceding SpO2 probe. It is, therefore, quite unlikely that there was contamination of data collected from one probe with the reading from the preceding probe. We stand by the conclusion of our paper: ‘the Lightman can detect faulty probes and predict reasonably accurately the direction of the probe’s error. The Lightman may be considered as a useful tool to assess the accuracy of pulse oximeter probes’.

A comparison of oxygen saturation measurements obtained from a ‘blue sensor’ with a standard sensor

The study aims to investigate pulse oximetry measurements from a 'blue' pulse oximeter sensor against measurements from a 'standard' pulse oximeter sensor in newly born infants. Immediately after birth, both sensors were attached to the infant, one to each foot. SpO₂ measurements were recorded simultaneously from each sensor for 10 min. Agreement between pairs of SpO₂ measurements were calculated using Bland-Altman analysis. Thirty-one infants were studied. There was good correlation between simultaneous SpO₂ measurements from both sensors (r² = 0.75). However, the mean difference between 'blue' and 'standard' sensors was -1.6%, with wide 95% limits of agreement +18.4 to -21.6%. The range of mean difference between sensors from each infant ranged from -20 to +20. The mean difference between the blue and standard sensor SpO₂ measurements is not clinically important.

모바일 유비쿼터스 헬스케어시스템 설계 및 구현

최근 유비쿼터스 센서네트워크 및 모바일 통신기술의 발달에 힘입어 헬스케어 시스템에 대한 많은 연구가 이루어지고 있다. 본 논문에서는 모바일 센서네트워크 기반의 u-Healthcare 시스템을 설계하고 구현하였다. 구현한 u-Healthcare 시스템은 댁내의 무선 센서네트워크, 원격지에 위치하는 헬스케어센터 및 센싱한 생체선호를 헬스케어 센터로 전송하는 게이트웨이 등 세 부분으로 구성된다. 환자의 생체신호를 측정하기 위하여 3 채널 ECG센서, 맥박산소 농도계, 혈압 센서 등 세 가지의 센서를 이용하였다. 각 센서는 mote에 탑재되어 있으며, mote는 센성된 생체신호를 Zigbee 통신을 이용하여 베이스 노드로 전송한다. 베이스 노드는 수신한 신호를 헬스케어 센터로 보내게 되고 헬스케어센터는 이 선호를 다양한 알고리즘을 이용하여 분석하고 처리한다. 처리된 결과를 표준 데이터베이스와 비교하여 식이요법, 운동요법 등 적절한 처방을 환자에게 SMS 또는 웹으로 전송한다. 이렇게 함으로서 환자는 주기적으로 자선의 건강을 체크하여 관리할 수 있으며, 경증의 건강상의 문제로부터 자신의 건강을 유지할 수 있게 된다. Recently, owing to the development of ubiquitous sensor network and mobile communication technologies, many studies on healthcare system are being carried out. In this paper, we have designed and implemented a mobile u-Healthcare system based on sensor network. The u-Healthcare system is composed of three components: wireless sensor network at home, healthcare center located at remote site, and gateway which relays sensing physiological signals to healthcare center. In order to measure patient's physiological signal three sensors are used: three channel ECG sensor, pulse oximeter, and blood pressure sensor. Each sensor is mounted on a mote which can send gathered signal to the base node using Zigbee communication protocol. Once the base node receives physiological signal from each sensor, the client in the base node transfers the signal to the healthcare center. The received physiological signal at the healthcare center is analyzed and processed using various algorithms. The processed results are compared to the standard healthcare database and appropriate treatment including dietetics and exercise cure would be sent to the patient as feedback using SMS message or healthcare center web site. Each patient can check and manage one's health state every day using the healthcare system and gain a recovery under the treatments from minor health problems.

The Ability of Pleth Variability Index to Predict the Hemodynamic Effects of Positive End-Expiratory Pressure in Mechanically Ventilated Patients Under General Anesthesia

Pleth variability index (PVI) is a new algorithm allowing automated and continuous monitoring of respiratory variations in the pulse oximetry plethysmographic waveform amplitude. PVI can predict fluid responsiveness noninvasively in mechanically ventilated patients during general anesthesia. We hypothesized that PVI could predict the hemodynamic effects of 10 cm H2O positive end-expiratory pressure (PEEP). We studied 21 mechanically ventilated and sedated patients in the postoperative period after coronary artery bypass grafting. Patients were monitored with a pulmonary artery catheter and a pulse oximeter sensor attached to the index finger. Hemodynamic data (cardiac index [CI], PVI, pulse pressure variation, central venous pressure) were recorded at 3 successive tidal volumes (V(T)) (6, 8, and 10 mL/kg body weight) during zero end-expiratory pressure (ZEEP) and then after addition of a 10 cm H2O PEEP for each V(t). Hemodynamically unstable patients were defined as those with a >15% decrease in CI after the addition of PEEP. PEEP induced changes in CI and PVI for V(t) of 8 and 10 mL/kg. Hemodynamic instability occurred in 5 patients for a V(T) of 6 mL/kg, in 6 patients for a V(T) of 8 mL/kg, and in 9 patients for a V(T) of 10 mL/kg. For V(T) of 8 mL/kg, a PVI threshold value of 12% during ZEEP predicted hemodynamic instability with a sensitivity of 83% and a specificity of 80% (area under the receiver operating characteristic curve 0.806; P = 0.03). For V(T) of 10 mL/kg, a PVI threshold value of 13% during ZEEP predicted hemodynamic instability with a sensitivity of 78% and a specificity of 83% (area under the receiver operating characteristic curve 0.829; P = 0.01). PVI may be useful in automatically and noninvasively detecting the hemodynamic effects of PEEP when V(T) is >8 mL/kg in ventilated and sedated patients with acceptable sensitivity and specificity.

Pulse Oximeter Plethysmographic Waveform Changes in Awake, Spontaneously Breathing, Hypovolemic Volunteers

The primary objective of this study was to determine whether alterations in the pulse oximeter waveform characteristics would track progressive reductions in central blood volume. We also assessed whether changes in the pulse oximeter waveform provide an indication of blood loss in the hemorrhaging patient before changes in standard vital signs. Pulse oximeter data from finger, forehead, and ear pulse oximeter sensors were collected from 18 healthy subjects undergoing progressive reduction in central blood volume induced by lower body negative pressure (LBNP). Stroke volume measurements were simultaneously recorded using impedance cardiography. The study was conducted in a research laboratory setting where no interventions were performed. Pulse amplitude, width, and area under the curve (AUC) features were calculated from each pulse wave recording. Amalgamated correlation coefficients were calculated to determine the relationship between the changes in pulse oximeter waveform features and changes in stroke volume with LBNP. For pulse oximeter sensors on the ear and forehead, reductions in pulse amplitude, width, and area were strongly correlated with progressive reductions in stroke volume during LBNP (R(2) ≥ 0.59 for all features). Changes in pulse oximeter waveform features were observed before profound decreases in arterial blood pressure. The best correlations between pulse features and stroke volume were obtained from the forehead sensor area (R(2) = 0.97). Pulse oximeter waveform features returned to baseline levels when central blood volume was restored. These results support the use of pulse oximeter waveform analysis as a potential diagnostic tool to detect clinically significant hypovolemia before the onset of cardiovascular decompensation in spontaneously breathing patients.

Misalignment of Disposable Pulse Oximeter Probes Results in False Saturation Readings That Influence Anesthetic Management

We report a small case series in which misaligned disposable pulse oximeter sensors gave falsely low saturation readings. In each instance, the sensor performed well during preinduction oxygen administration and the early part of the case, most notably by producing a plethysmographic trace rated as high quality by the oximeter software. The reported pulse oximeter oxygen saturation eventually decreased to concerning levels in each instance, but the anesthesiologists, relying on the reported high-quality signal, initially sought other causes for apparent hypoxia. They undertook maneuvers and diagnostic procedures later deemed unnecessary. When the malpositioned sensors were discovered and repositioned, the apparent hypoxia was quickly relieved in each case. We then undertook a survey of disposable oximeter sensors as patients entered the recovery room, and discovered malposition of more than 1 cm in approximately 20% of all sensors, without apparent consequence. We conclude that the technology is quite robust, but that the diagnosis of apparent hypoxia should include a quick check of oximeter position early on.

Blood pressure cuffs and pulse oximeter sensors: A potential source of cross-contamination

Summary Background Emergency Departments were traditionally designed to manage episodic acute care, but with the variability in accessing affordable after-hours general practice coupled with an increase in the aging population, our departments are now experiencing increased throughput resulting in overcrowding and access block. 1 Considering there has been a 15% decline in the number of inpatient beds across the nation over the past 10 years, it isn't surprising to also find there has been a nation-wide increase in the presentations to Emergency Departments. 1 The Department of Health and Aging estimated a nation-wide 10% increase in people seeking treatment at Emergency Departments during the period 1998 to 2003. 34 Such challenges lead to a number of potential or actual adverse outcomes that in turn lead to time available to attend to the decontamination, cleaning and disinfection of our non-critical monitoring equipment such as blood pressure cuffs and pulse oximeters. This small study examined the presence of micro-organisms on re-usable blood pressure cuffs and pulse oximeter sensors within a rural Emergency Department and questions the effectiveness of including the maintenance of this equipment within the nursing role. Methods This was a single centre prospective study within an Emergency Department treating over 35,000 patients per annum. Swabs obtained from re-usable blood pressure cuffs and pulse oximeters formed Group A. While it is acknowledged the total number of 30 swabs collected in Group A is small, this restriction was determined by the availability of blood pressure cuffs and pulse oximeters in use within the department. The swabs were cultured for a period of 48hours. Results were formally reported** on to identify micro-organisms that have the potential to cause hospital acquired infections. Both new and cleaned equipment enabled the formation of control groups B and C respectfully. While the sample size for the control group B is below that of control group C, it was dependent on having access to new blood pressure cuffs and pulse oximeters still remaining within their original packaging and thereby meeting the criteria for swabbing. Equipment forming Group C was cleaned according the Spaulding Classification System 2 and then swabbed by the principle researcher. Ethics approval was not sought, but institutional approval was granted through the Infection Control Unit. Results Of the 30 swabs obtained in group A, 83% reported growths of saprophytes predominantly being a combination of mixed skin flora and environmental pathogens. Two pulse oximeter sensors returned clinically significant colonies of Staphylococcus aureus and Bacillus species. Conclusion While 70% alcohol has been found to be an effective agent in the decontamination of re-usable non-critical medical equipment, this study emphasises not only the need for vigilance in the cleaning practices associated with blood pressure cuffs and pulse oximeter sensors as a contributing factor in the prevention of hospital acquired infections, but also encourages an examination of who is the best to perform the cleaning role given Emergency Nurses work within an environment that is often overcrowded and subject to bed blocks.

Ring sensor and heart rate monitoring system for sensor network applications

A ring-type pulse oximeter sensor attached to the finger and its 24-hour ambulatory heart rate monitoring system are presented. The PCB has been designed with a light-to-frequency converter and the CPU with a built-in Zigbee stack for simple and low power consumption. Also designed is the algorithm using a least square estimator to calibrate various signal distortions caused by motion artefacts for a proper accuracy.

Pulse oximeter accuracy and precision affected by sensor location in cyanotic children

Children's digits are often too small for proper attachment of oximeter sensors, necessitating sensor placement on the sole of the foot or palm of the hand. No study has determined what effect these sensor locations have on the accuracy and precision of this technology. The objective of this study was to assess the effect of sensor location on pulse oximeter accuracy (i.e., bias) and precision in critically ill children. Prospective, observational study with consecutive sampling. Tertiary care, pediatric intensive care unit. Fifty critically ill children, newborn to 2 yrs of age, with an indwelling arterial catheter. Forty-seven of 50 (94%) patients were postcardiac surgery. None. Co-oximeter-measured arterial oxygen saturation (Sao2) was compared with simultaneously obtained pulse oximetry saturations (Spo2). A total of 98 measurements were obtained, 48 measurements in the upper extremities (finger and palm) and 50 measurements in the lower extremities (toe and sole). The median Sao2 was 92% (66% to 100%). There was a significant difference in bias (i.e., average Spo2 - Sao2) and precision (+/-1 sd) when the sole and toe were compared (sole, 2.9 +/- 3.9 vs. toe, 1.6 +/- 2.2, p = .02) but no significant difference in bias and precision between the palm and the finger (palm, 1.4 +/- 3.2 vs. finger, 1.2 +/- 2.3, p = .99). There was a significant difference in bias +/- precision when the Sao2 was <90% compared with when Sao2 was >or=90% in the sole (6.0 +/- 5.7 vs. 1.8 +/- 2.1, p = .002) and palm (4.5 +/- 4.5 vs. 0.7 +/- 2.4, p = .006) but no significant difference in the finger (1.8 +/- 3.8 vs. 1.1 +/- 1.8, p = .95) or toe (1.9 +/- 2.9 vs. 1.6 +/- 1.9, p = .65). The Philips M1020A pulse oximeter and Nellcor MAX-N sensors were less accurate and precise when used on the sole of the foot or palm of the hand of a child with an Sao2 <90%.

Optical biosensing: future possibilities

How the construction of oximeter sensors has evolved over the last decade is a reflection of the advancement in light sources and detectors from the optoelectronics and microelectronics research fields.

센서 네트워크 응용을 위한 반지형 맥박센서와 모니터링 시스템

블루투스, 지그비, RFID와 같은 저가의 저 전력 무선통신 기술의 실용화는 웰빙 바람과 함께 유비쿼터스 헬스케어에 대한 관심이 급격하게 증가하고 있으며 u-Health는 센서네트워크분야에서 가장 중요한 응용분야중 하나가 되고 있다. 특히 독거노인이나 실버타운의 노인을 위해 응급상황에 대한 대처가 가능한 의료서비스를 개발하는 것은 그 자체로 의미가 있으며 그 수요는 노령인구의 급속한 증가와 함께 지속적으로 늘어날 것으로 기대된다. 이에 본 논문은 일상생활에서 손가락에 착용한 반지모양의 pulse oximeter 센서에 의해 수집된 PPG 신호로부터 정확한 맥박 변화율을 이끌어내는 것에 대한 타당성을 보이고자 한다. 이를 위해 반사형과 투과형 2가지 종류의 반지센서를 제작하였으며 반지센서로부터 맥박데이터를 수집, 분석하고 응급상황에 대처할 수 있는 원격의 모니터링 시스템을 개발하였다. As low power, low cost wireless communication technology like Bluetooth, Zigbee, RFID has been put to practical use together with the wellbeing trend, the concern about ubiquitous health care has been greatly increased and u-Health is becoming one of the most important application in the sensor network field. Especially, development of the medical services to be able to cope with a state of emergency for solitary senior citizens and the aged in silver town is very meaningful itself and their needs are also expected to continuously increase with a rapid increase in an aging population. In this paper we demonstrate the feasibility of extracting accurate heart rate variability (HRV) measurements from photoelectric plethysmography(PPG) signals gathered by a ring type pulse oximeter sensor attached to the finger. For this, we made 2 types of ring sensor, that is reflective and pervious type, and developed the remote monitoring system which is able to collect HR data from ring sensor, analyze and cope with a state of emergency.

Skin Burn Associated with Pulse Oximeter - A case report -

A pulse oximeter is used widely on account of its convenience and very few complications. We experienced a case of accidental burning by a pulse oximeter sensor. An 83-year-old woman underwent total hip replacement surgery. A pulse oximeter (Oxisensor II N-25, Nellcor Puritan Bennett Inc., USA) was placed on the left index finger. The patient complained of pain on her index finger 5 minutes after the operation began. A localized skin burn was found underneath the sensor of the pulse oximeter. The skin burn healed without any sequelae.

Measurement of Carboxyhemoglobin and Methemoglobin by Pulse Oximetry

A new eight-wavelength pulse oximeter is designed to measure methemoglobin and carboxyhemoglobin, in addition to the usual measurements of hemoglobin oxygen saturation and pulse rate. This study examines this device's ability to measure dyshemoglobins in human volunteers in whom controlled levels of methemoglobin and carboxyhemoglobin are induced. Ten volunteers breathed 500 ppm carbon monoxide until their carboxyhemoglobin levels reached 15%, and 10 different volunteers received intravenous sodium nitrite, 300 mg, to induce methemoglobin. All were instrumented with arterial cannulas and six Masimo Rad-57 (Masimo Inc., Irvine, CA) pulse oximeter sensors. Arterial blood was analyzed by three laboratory CO-oximeters, and the resulting carboxyhemoglobin and methemoglobin measurements were compared with the corresponding pulse oximeter readings. The Rad-57 measured carboxyhemoglobin with an uncertainty of +/-2% within the range of 0-15%, and it measured methemoglobin with an uncertainty of 0.5% within the range of 0-12%. The Masimo Rad-57 is the first commercially available pulse oximeter that can measure methemoglobin and carboxyhemoglobin, and it therefore represents an expansion of our oxygenation monitoring capability.