Sleep Monitoring Based on a Tri-Axial Accelerometer and a Pressure Sensor
<p>Process flow for sleep quality monitoring.</p> "> Figure 2
<p>Sleeping postures.</p> "> Figure 3
<p>Our test-bed environment, (<b>a</b>) test-bed; (<b>b</b>) Polysomnography.</p> "> Figure 4
<p>Screenshots of the user interfaces and examples of signals obtained from the sleep quality monitoring system. Screenshots of user interfaces in the sleep quality monitoring system. (<b>a</b>) screenshots of user interfaces in the sleep quality monitoring system; (<b>b</b>) example signals obtained from the sleep quality monitoring system.</p> "> Figure 5
<p>Example of signals obtained from the PSG.</p> "> Figure 6
<p>Analog-to-digital converter (ADC) board. (<b>a</b>) ADC board; (<b>b</b>) architecture of ADC board.</p> "> Figure 7
<p>Heart rate variability and respiratory rate. (<b>a</b>) Raw data obtained from ADC (100 samples/s, 12-bit resolution); (<b>b</b>) Filtering data using an infinite impulse (IIR) filter for estimating the heart rate; (<b>c</b>) Filtering data using an infinite impulse (IIR) filter for estimating the respiratory rate; (<b>d</b>) Heart peak obtained from filtering data after noise reduction; (<b>e</b>) Selected heart peak.</p> "> Figure 7 Cont.
<p>Heart rate variability and respiratory rate. (<b>a</b>) Raw data obtained from ADC (100 samples/s, 12-bit resolution); (<b>b</b>) Filtering data using an infinite impulse (IIR) filter for estimating the heart rate; (<b>c</b>) Filtering data using an infinite impulse (IIR) filter for estimating the respiratory rate; (<b>d</b>) Heart peak obtained from filtering data after noise reduction; (<b>e</b>) Selected heart peak.</p> "> Figure 8
<p>Bland–Altman plot with a mean difference of 0.076 that shows the limit of agreement of 95% (dashed lines are mean differences ± the limit of agreement) between the continuous heart rate (HR) of pressure signal and its corresponding electro-cardiogram (ECG) signal.</p> "> Figure 9
<p>Results of the sleeping pose rate and sleeping pose detection. (<b>a</b>) Sleeping pose rate; (<b>b</b>) Sleeping pose detection.</p> "> Figure 10
<p>Sleep apnea detection.</p> "> Figure 11
<p>Results of the sleep stage classification.</p> "> Figure 12
<p>Example of signals obtained from sensors in the presence of motion artifact. (<b>a</b>) Example of signals obtained from the PSG in the presence of motion artifact; (<b>b</b>) Example of signals obtained from an accelerometer sensor and a pressure sensor in the presence of motion artifacts.</p> ">
Abstract
:1. Introduction
2. Sleep Quality Monitoring System
2.1. System Architecture
2.2. Feature Extraction and Data Analysis
3. Experimental Results
3.1. Experimental Environments
3.2. Results
4. Discussion
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Sensor | Specifications | |
---|---|---|
three-axis accelerometer | Size: 5 cm, weight: 500 g, consumption current: 0.6 mA, resolution: 60 Hz, MSP430 micro controller for a micro controller (MCU): 16 bit reduced instruction set computer (RISC) | |
pressure | Size: 40 cm × 40 cm, weight: 300 g, sensor type: film, operating temp: from −40 C to +50 C, sensitivity: 25–250 pc/n, operating force range: >100 N/cm |
Subject | Total Sleep Time (Hour) | The Number of Sleep Apnea (Ours) | The Number of Sleep Apnea (PSG) | The Number of Sleep State Change (Ours) | The Number of Sleep State Change (PSG) | Sleep Quality | Dominant Sleeping Pose |
---|---|---|---|---|---|---|---|
A | 7.1 | 16.3 | 16.6 | 5.6 | 5.8 | 75.77 | Right |
B | 6.8 | 12.7 | 12.2 | 4.8 | 4.4 | 81.54 | Front |
C | 7.6 | 13.6 | 13.2 | 5.2 | 5.6 | 77.57 | Right |
D | 5.1 | 0 | 0 | 4 | 4 | 87.44 | Right |
E | 10 | 0 | 0 | 3 | 3 | 120.3 | Front |
F | 7 | 0 | 0 | 16 | 16 | 74.17 | Back |
G | 7 | 5 | 5.2 | 6 | 6 | 77.66 | Right |
H | 5.6 | 0 | 0 | 2 | 2 | 86.67 | Front |
I | 7 | 2 | 2.2 | 3 | 3 | 104.75 | Front |
J | 7 | 16 | 16.2 | 3 | 3 | 85.81 | Front |
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Nam, Y.; Kim, Y.; Lee, J. Sleep Monitoring Based on a Tri-Axial Accelerometer and a Pressure Sensor. Sensors 2016, 16, 750. https://doi.org/10.3390/s16050750
Nam Y, Kim Y, Lee J. Sleep Monitoring Based on a Tri-Axial Accelerometer and a Pressure Sensor. Sensors. 2016; 16(5):750. https://doi.org/10.3390/s16050750
Chicago/Turabian StyleNam, Yunyoung, Yeesock Kim, and Jinseok Lee. 2016. "Sleep Monitoring Based on a Tri-Axial Accelerometer and a Pressure Sensor" Sensors 16, no. 5: 750. https://doi.org/10.3390/s16050750