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Proceeding Paper

Feasibility Study on Fabric-Sheet Unified Sensing Electrode for Non-Contact In-Bed Measurements of ECG, Body Proximity and Respiratory Movement †

1
Master’s Program in Electrical and Electronic Engineering, Tokyo Denki University, Tokyo 120-8551, Japan
2
Department of Electrical and Electronic Engineering, school of Engineering, Tokyo Denki University, Tokyo 120-8551, Japan
*
Author to whom correspondence should be addressed.
Presented at the 7th International Symposium on Sensor Science, Napoli, Italy, 9–11 May 2019.
Proceedings 2019, 15(1), 19; https://doi.org/10.3390/proceedings2019015019
Published: 10 July 2019
(This article belongs to the Proceedings of 7th International Symposium on Sensor Science)

Abstract

:
In a recent article, we have reported that a fabric-sheet unified sensing electrode (FUSE) can detect electrocardiogram (ECG), body proximity at the chest and abdomen (BPxchest, BPxabd) and respiratory movement at the abdomen (RMabd) via worn clothes and bedsheet simultaneously from recumbent human subject. We conducted feasibility study involving 21 subjects to assess the influence of individual difference on this FUSE system. Results revealed that individual difference of physical constitution had little impact on both accuracies of ECG R wave and RMabd under the current FUSE configuration, but had some influence on the voltage changes in BPxchest and BPxabd caused by postural change. We deemed to revise some dimensions of the FUSE to avoid individual threshold setting for sitting up detection.

1. Introduction

With the rapid population aging [1], and the progress of information and communication technology, physiological and behavioral signals are considered to be monitored at home in the near future. Vital monitoring at home is considered to play an important role in both preventive daily healthcare and in-hospital care. In a recent research report, a fabric-sheet unified sensing electrode (FUSE) can detect electrocardiogram (ECG), body proximity at the chest and abdomen (BPxchest, BPxabd) and respiratory movement (RM) via worn clothes and bedsheet simultaneously from recumbent human subject [2]. In the article, however, verification of principle of the system and fundamental evaluation were only done. In the current research, we conduct feasibility study involving increased subjects to assess the influence of individual difference on this FUSE system.

2. Materials and Methods

2.1. Fabric-Sheet Unified Sensing Electrode (FUSE)

The FUSE can simultaneously measure capacitive electrocardiogram (cECG), BPxchest, BPxabd, and respiratory movement at the abdomen (RMabd) signals. The FUSE is laid under the bed sheet and the back of the lying subject. To prevent sleep disturbance due to night sweat, the FUSE is constructed from breathable materials (conductive fabric of porous copper thin film and insulating fabric; see Figure 1). The detection circuit is basically similar to the conventional system. In addition, a driven seat ground (DSG) circuit [3] was introduced to suppress common mode noise.

2.2. Simultaneous Measurements of cECG, BPxchest, BPxabd and RMabd at Rest and Sit-up Motion

The content of experiment was approved by the Human Life Ethic Committee of Tokyo Denki University. All subjects provided informed consent prior to participation in our experiments. We measured the cECG, BPxchest, BPxabd, and RMabd signals simultaneously totally 31 times from 9 males and 12 females (BMI: 16.0 to 29.0 kg/m2). Subjects were asked to keep supine posture and breathing at 30 breaths / minute (rpm) using the metronome on the bed for 5 minutes. Subjects were then asked to sit up. Reference electrocardiogram signal (ECGref) was simultaneously measured by a commercially available wireless telemetry type electrocardiograph (i.e., BN-RSPEC, BIOPAC Systems, Goleta, CA, USA) and disposable electrodes (i.e., F-150S, Nihon Kohden, Tokyo, Japan). Reference RMabd signal (RMref) simultaneously measured by a belt type respiratory transducer of the same telemetry type (i.e., BN-RESP-XDCR, BIOPAC Systems, Goleta, CA, USA). For evaluation, commercially available analysis software (i.e., AcqKnowledge 4.1, BIOPAC Systems, Goleta, CA, USA) was used. Five minutes of rest state was set as an analysis section of the cECG and RMabd signals. The cECG and ECGref signals were preprocessed by smoothed by the 20-point window, filtered through a digital high-pass filter (infinite impulse response filter, fc = 10 Hz) and differential processing, respectively. The each ECG were detected the R wave by the peak detection function of the software and calculated R-R intervals (RRIs). Detection was performed when the time difference between the RRI of each ECG was ±5 ms or less, and the detection accuracy of each was calculated. RMabd and RMref signals were preprocessed by filtered twice through a digital band-pass filter (infinite impulse response filter, fc = 0.15–0.5 Hz). Discrete RMabd cycles in each RMabd signals were automatically detected by software with threshold processing [4], and detection accuracy of each RMabd was calculated. Detection of the sit-up motion was calculated from the voltage change of BPxchest and BPxabd signals (ΔBPxchest, ΔBPxabd) before and after sit-up motion.

3. Results and Discussion

Table 1 shows the maximum value (Max), the minimum value (Min), the mean value (MN) and standard deviation (SD) of the accuracies of cECG R wave and RMabd signals, and each ΔBPx. Figure 2 shows representative simultaneous measured waveforms of BPxchest, BPxabd, cECG, ECGref, RMabd and RMref signals including sit-up motion. Detection accuracy of cECG R wave exceeded 90% in all subjects. The average value of detection accuracy in RMabd signal was 91.9%. The ΔBPx due to the sit-up motion varied from 0.2 to 4.0 V in ΔBPxchest and from 0.2 to 6.0 V in ΔBPxabd. Measurement of cECG signal were stable in all subjects. On average, the detection accuracy of the RMabd signals exceeded 90%. Individual difference was confirmed in ΔBPxchest, and ΔBPxabd due to sit-up motion. It was inferred that this is due to the difference in bonding position between the electrode and the body due to the difference in physique. It is considered that examination of electrode size is necessary to reduce the influence of difference in body size.

4. Conclusions

Feasibility study was conducted to evaluate the influence of the individual difference on the FUSE. Totally 31 measurements were done for 9 males and 12 females (BMI: 16.0 to 29.0 kg/m2). Individual difference of physical constitution had little impact on both accuracies of cECG R wave and RMabd under the current FUSE configuration, but had some influence on the BPxchest and BPxabd caused by sit-up motion. Therefore, we deemed to revise some dimensions of the current FUSE to avoid individual threshold setting for detecting sit-up motion.

References

  1. United Nations. Available online: https://www.un.org/development/desa/publications/world-population-prospects-the-2012-revision.html (accessed on 18 January 2019).
  2. Takano, M.; Ueno, A. Noncontact in-bed measurements of physiological and behavioral signals using an integrated fabric-sheet sensing scheme. IEEE J. Biomed. Health Inf. 2019, 23, 618–630. [Google Scholar] [CrossRef] [PubMed]
  3. Kim, K.K.; Lim, Y.K.; Park, K.S. Common mode noise cancellation for electrically non-contact ECG measurement system on a chair. In Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, China, 17–18 January 2006; IEEE: Washington, DC, USA, 2005; Volume 6, pp. 5881–5883. [Google Scholar]
  4. Yamagishi, S.; Takano, M.; Ueno, A.; Fukuoka, Y. A study on breath detection algorithm for capacitive in-bed cardiorespiratory monitor. IEICE Technical Report MBE2015-103 2016, 115, 5–8. [Google Scholar]
Figure 1. The measuring system used in this study. (a) Cross-sectional side-view configuration of the FUSE. (b) Top-view configuration of the FUSE and block diagram of the measuring system.
Figure 1. The measuring system used in this study. (a) Cross-sectional side-view configuration of the FUSE. (b) Top-view configuration of the FUSE and block diagram of the measuring system.
Proceedings 15 00019 g001
Figure 2. Representative measurements including sit-up motion. (a) Discriminative recordings of BPxchest, BPxabd, cECG, ECGref, RMabd and RMref signals measured simultaneously by the FUSE. cECG waveform was smoothed by the 20-point window. (b) Enlarged example of cECG and ECGref waveforms for the segment enclosed by dotted line in (a).
Figure 2. Representative measurements including sit-up motion. (a) Discriminative recordings of BPxchest, BPxabd, cECG, ECGref, RMabd and RMref signals measured simultaneously by the FUSE. cECG waveform was smoothed by the 20-point window. (b) Enlarged example of cECG and ECGref waveforms for the segment enclosed by dotted line in (a).
Proceedings 15 00019 g002
Table 1. Max, Min, MN and SD of the accuracies of cECG R wave and RMabd signals, and each ΔBPx.
Table 1. Max, Min, MN and SD of the accuracies of cECG R wave and RMabd signals, and each ΔBPx.
accuracy of cECG R wave (%)accuracy of RMabd (%)ΔBPxchest (V)ΔBPxadb (V)
Max100.0100.04.06.0
Min92.540.30.20.2
MN ± SD97.8 ± 2.291.9 ± 12.92.1 ± 1.03.0 ± 1.6

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MDPI and ACS Style

Sakajiri, Y.; Ueno, A. Feasibility Study on Fabric-Sheet Unified Sensing Electrode for Non-Contact In-Bed Measurements of ECG, Body Proximity and Respiratory Movement. Proceedings 2019, 15, 19. https://doi.org/10.3390/proceedings2019015019

AMA Style

Sakajiri Y, Ueno A. Feasibility Study on Fabric-Sheet Unified Sensing Electrode for Non-Contact In-Bed Measurements of ECG, Body Proximity and Respiratory Movement. Proceedings. 2019; 15(1):19. https://doi.org/10.3390/proceedings2019015019

Chicago/Turabian Style

Sakajiri, Yuichiro, and Akinori Ueno. 2019. "Feasibility Study on Fabric-Sheet Unified Sensing Electrode for Non-Contact In-Bed Measurements of ECG, Body Proximity and Respiratory Movement" Proceedings 15, no. 1: 19. https://doi.org/10.3390/proceedings2019015019

APA Style

Sakajiri, Y., & Ueno, A. (2019). Feasibility Study on Fabric-Sheet Unified Sensing Electrode for Non-Contact In-Bed Measurements of ECG, Body Proximity and Respiratory Movement. Proceedings, 15(1), 19. https://doi.org/10.3390/proceedings2019015019

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