Where do pulse oximeter probes break?

Pulse oximetry, a non-invasive method for accurate assessment of blood oxygen saturation (SPO2), is an important monitoring tool in health care facilities. However, it is often not available in many low-resource settings, due to expense, overly sophisticated design, a lack of organised procurement systems and inadequate medical device management and maintenance structures. Furthermore medical devices are often fragile and not designed to withstand the conditions of low-resource settings. In order to design a probe, better suited to the needs of health care facilities in low-resource settings this study aimed to document the site and nature of pulse oximeter probe breakages in a range of different probe designs in a low to middle income country. A retrospective review of job cards relating to the assessment and repair of damaged or faulty pulse oximeter probes was conducted at a medical device repair company based in Cape Town, South Africa, specializing in pulse oximeter probe repairs. 1,840 job cards relating to the assessment and repair of pulse oximeter probes were reviewed. 60.2 % of probes sent for assessment were finger-clip probes. For all probes, excluding the neonatal wrap probes, the most common point of failure was the probe wiring (>50 %). The neonatal wrap most commonly failed at the strap (51.5 %). The total cost for quoting on the broken pulse oximeter probes and for the subsequent repair of devices, excluding replacement components, amounted to an estimated ZAR 738,810 (USD $98,508). Improving the probe wiring would increase the life span of pulse oximeter probes. Increasing the life span of probes will make pulse oximetry more affordable and accessible. This is of high priority in low-resource settings where frequent repair or replacement of probes is unaffordable or impossible.

Photoplethysmogram signal quality estimation using repeated Gaussian filters and cross-correlation.

Pulse oximeters are monitors that noninvasively measure heart rate and blood oxygen saturation (SpO2). Unfortunately, pulse oximetry is prone to artifacts which negatively impact the accuracy of the measurement and can cause a significant number of false alarms. We have developed an algorithm to segment pulse oximetry signals into pulses and estimate the signal quality in real time. The algorithm iteratively calculates a signal quality index (SQI) ranging from 0 to 100. In the presence of artifacts and irregular signal morphology, the algorithm outputs a low SQI number. The pulse segmentation algorithm uses the derivative of the signal to find pulse slopes and an adaptive set of repeated Gaussian filters to select the correct slopes. Cross-correlation of consecutive pulse segments is used to estimate signal quality. Experimental results using two different benchmark data sets showed a good pulse detection rate with a sensitivity of 96.21% and a positive predictive value of 99.22%, which was equivalent to the available reference algorithm. The novel SQI algorithm was effective and produced significantly lower SQI values in the presence of artifacts compared to SQI values during clean signals. The SQI algorithm may help to guide untrained pulse oximeter users and also help in the design of advanced algorithms for generating smart alarms.

Usability testing of a prototype Phone Oximeter with healthcare providers in high- and low-medical resource environments.

To increase the use of pulse oximetry by capitalise on the wide availability of mobile phones, we have designed, developed and evaluated a prototype pulse oximeter interfaced to a mobile phone. Usability of this Phone Oximeter was tested as part of a rapid prototyping process. Phase 1 of the study (20 subjects) was performed in Canada. Users performed 23 tasks, while thinking aloud. Time for completion of tasks and analysis of user response to a mobile phone usability questionnaire were used to evaluate usability. Five interface improvements were made to the prototype before evaluation in Phase 2 (15 subjects) in Uganda. The lack of previous pulse oximetry experience and mobile phone use increased median (IQR [range]) time taken to perform tasks from 219 (160-247 [118-274]) s in Phase 1 to 228 (151-501 [111-2661]) s in Phase 2. User feedback was positive and overall usability high (Phase 1--82%, Phase 2--78%).

Pulse oximeter plethysmograph variation and its relationship to the arterial waveform in mechanically ventilated children.

The variations induced by mechanical ventilation in the arterial pulse pressure and pulse oximeter plethysmograph waveforms have been shown to correlate closely and be effective in adults as markers of volume responsiveness. The aims of our study were to investigate: (1) the feasibility of recording plethysmograph indices; and (2) the relationship between pulse pressure variation (ΔPP), plethysmograph variation (ΔPOP) and plethysmograph variability index (PVI) in a diverse group of mechanically ventilated children. A prospective, observational study was performed. Mechanically ventilated children less than 11 years of age, with arterial catheters, were enrolled during the course of their clinical care in the operating room or in the pediatric intensive care unit. Real time monitor waveforms and trend data were recorded. ΔPP and ΔPOP were manually calculated and the relationships between ΔPP, ΔPOP and PVI were compared using Bland-Altman analysis and Pearson correlations. Forty-nine children were recruited; four (8%) subjects were excluded due to poor quality of the plethysmograph waveforms. ΔPP and ΔPOP demonstrated a strong correlation (r = 0.8439, P < 0.0001) and close agreement (Bias = 1.44 ± 6.4%). PVI was found to correlate strongly with ΔPP (r = 0.7049, P < 0.0001) and ΔPOP (r = 0.715, P < 0.0001). This study demonstrates the feasibility of obtaining plethysmographic variability indices in children under various physiological stresses. These data show a similarly strong correlation to that described in adults, between the variations induced by mechanical ventilation in arterial pulse pressure and the pulse oximeter plethysmograph.

Sleep and Wake Classification With ECG and Respiratory Effort Signals.

We describe a method for the online classification of sleep/wake states based on cardiorespiratory signals produced by wearable sensors. The method was conceived in view of its applicability to a wearable sleepiness monitoring device. The method uses a fast Fourier transform as the main feature extraction tool and a feedforward artificial neural network as a classifier. We show that when the method is applied to data collected from a single young male adult, the system can correctly classify, on average, 95.4% of unseen data from the same user. When the method is applied to classify data from multiple users with the same age and gender, its accuracy is reduced to 85.3%. However, receiver operating characteristic analysis shows that compared to actigraphy, the proposed method produces a more balanced correct classification of sleep and wake periods. Additionally, by adjusting the classification threshold of the neural classifier, 86.7% of correct classification is obtained.

A 3000-year climatic record from biogenic silica oxygen isotopes in an equatorial high-altitude lake

A record of oxygen isotopes in biogenic opal, 4200 to 1200 calibrated years before the present, from a high-altitude proglacial lake on Mount Kenya, East Africa, exhibits short-term fluctuations on a time scale of centuries as well as long-term variations. The short-term fluctuations are attributed to changes in the glacier meltwater input, and the long-term variations are related to changes in lake temperature. The record indicates that the climate was warm in Equatorial East Africa from 2300 to 1500 years before the present.