Chris Petersen

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%).

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%).

The Phone Oximeter for Mobile Spot-Check

8 Measuring adeQuacy of analgesia with cardiorespiratory coherence Chris Brouse, Walter Karlen, Guy Dumont, Dorothy Myers, Erin Cooke, Jonathan Stinson, Joanne Lim, J. Mark Ansermino The University of British Columbia, Vancouver, Canada Introduction: An automated nociception monitor would be very useful in general anesthesia, providing anesthesiologists with real-time feedback about the adequacy of analgesia. We have developed an algorithm to measure nociception using respiratory sinus arrhythmia (RSA) in heart rate variability (HRV). We have previously shown that this algorithm can detect patient movement (strongly nociceptive events) during general anesthesia 1. We will now attempt to determine if the algorithm responds to boluses of anesthetic drugs (strongly anti-nociceptive events). Method: Algorithm: The algorithm estimates cardiorespiratory coherence, which is the strength of linear coupling between HR and respiration (one measure of RSA). It measures and combines the spectral power in both signals using wavelet analysis. Coherence is dimensionless, and ranges from 0 (no coherence, strong nociception) to 1 (perfect coherence, no nociception). Data Analysis: Following ethics approval and informed consent, 60 drug bolus events (excluding induction of anesthesia) were recorded in 47 pediatric patients receiving general anesthesia during dental surgery. In post hoc analysis, coherence was averaged over the 60s immediately preceding the bolus dose of drug (nociceptive period). The bolus was given 30s to take effect, after which the coherence was averaged over the following 60s (anti-nociceptive period). The change in average coherence between the two periods was calculated. The change in average HR was also calculated, for comparison. Results: Coherence increased by an average of 0.14 (32%) in response to the bolus dose of anesthetic drug. HR decreased by an average of 4.1 beats/min (3.9%). Discussion: Cardiorespiratory coherence responded much more strongly to the anesthetic boluses than did HR alone. This result, combined with previous work showing that coherence is low during periods of nociception [1], demonstrates that cardiorespiratory coherence can be used to measure the adequacy of analgesia during general anesthesia. We are currently adapting the algorithm so that it can be used in real-time.

Photoplethysmogram Processing Using an Adaptive Single Frequency Phase Vocoder Algorithm

We have previously designed a pulse oximeter connected to a mobile phone, called the Phone Oximeter, for clinical decision making based on photoplethysmography. The limited battery and computational resources demand efficient and low-power algorithms for the Phone Oximeter to be effective in resource-poor and remote areas. We present two new algorithms for the fast and economical estimation of heart rate (HR) from the photoplethysmogram (PPG). One method estimates the HR frequency by adaptively modeling the PPG wave with a sine function using a modified phase vocoder. The other method uses the obtained wave as an envelope for the detection of peaks in the PPG signal. HR is computed using the vocoder center frequency or the peak intervals in a histogram, respectively. PPG data obtained from 42 subjects were processed with the vocoder algorithms and, for comparison, with two traditional methods that use filtering algorithms (Pan-Tompkins) and frequency domain transformations (Fast-Fourier Transform). We compared HR estimates obtained from these four methods to the reference HR obtained from a electrocardiogram. The two vocoder methods performed at least as well as the two traditional methods in terms of normalized root mean sqare error and robustness towards artifacts. Experiments on a mobile device prototype showed comparable speed performance of the vocoder algorithms with the Pan-Tompkins algorithm while the frequency domain approach was nearly two orders of magnitude slower. These results point to further developments using a combination of both vocoder HR estimation methods that will enable the robust implementation of adaptive phase vocoders into mobile device health applications.