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Original Research

A novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography

, , , , , , , & show all
Pages 397-408 | Published online: 26 Nov 2018

Figures & data

Table 1 Demographics and ECG analysis across individual subjects

Table 2 Demographics and respiration analysis across individual subjects

Figure 1 Respiration measurements.

Notes: (A) Overlaid calculations of respiratory rate (RR) from the BiostampRC® system (red dots) and the PSG recording (blue dots) for a full night of recording in the lab. (B) Overlaid raw (blue) and filtered (green) signal of respiration from the BiostampRC®.
Figure 1 Respiration measurements.

Figure 2 Electrocardiogram measurements.

Notes: Overlaid raw signals from the ECG of the PSG recording (blue) and the ECG measured by the BiostampRC® (red) placed at Lead II position on the chest.
Figure 2 Electrocardiogram measurements.

Figure 3 Limb movement detection example.

Notes: The anterior tibialis EMG signals from the BiostampRC® (blue) and PSG system (red) are shown in A. The black bars in B and C represent identified contractions.
Figure 3 Limb movement detection example.

Figure 4 ROC curve for PLMS detection.

Notes: Each vertical bar is 2 seconds duration (the entire segment is just over 2 minutes of recording). The signals are color coded according to the legend in the top left. For example, the first upward deflection of the BiostampRC® (left side of tracing) was not seen by the PSG sensor, and thus is a false positive limb movement detection. The blue and red horizontal lines near the bottom of the plot are the thresholds (“limit” in the legend), relative to baseline noise, used by the algorithm for event detection. There are no false negatives in this image. Edges where signal falls below threshold adjacent to suprathreshold segments are shown for illustrative purposes only, but are not considered in the algorithm (see Methods section).
Figure 4 ROC curve for PLMS detection.

Figure S1 Schematic of signal processing of respiration signals.

Abbreviations: AXL, accelerometer; BRC, BiostampRC® sensor system; LP, low pass; PCA, principle component analysis; RMSE, root mean square error; RR, respiration rate; x, y, z, axes of the accelerometer; SQI, signal quality index.

Figure S1 Schematic of signal processing of respiration signals.Abbreviations: AXL, accelerometer; BRC, BiostampRC® sensor system; LP, low pass; PCA, principle component analysis; RMSE, root mean square error; RR, respiration rate; x, y, z, axes of the accelerometer; SQI, signal quality index.

Figure S2 BiostampRC® device.

Note: Left, position on the lower leg; Right, close-up view of one device.

Figure S2 BiostampRC® device.Note: Left, position on the lower leg; Right, close-up view of one device.

Figure S3 The true positive (TP) rate (ie, sensitivity) is shown on the y-axis, and the FP rate (ie, 1-speciificity) is shown on the x-axis

Abbreviations: AUC, area under the curve; EMG, electromyography; PSG, polysomnography; RMS, root mean square; TP, true positive.

Figure S3 The true positive (TP) rate (ie, sensitivity) is shown on the y-axis, and the FP rate (ie, 1-speciificity) is shown on the x-axisAbbreviations: AUC, area under the curve; EMG, electromyography; PSG, polysomnography; RMS, root mean square; TP, true positive.