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Development of a portable non-invasive swallowing and respiration assessment device.

Shieh WY, Wang CM, Chang CS - Sensors (Basel) (2015)

Bottom Line: All signals are received and processed for swallowing event recognition.A total of 19 volunteers participated in the testing and over 57 measurements were made.The results show that the proposed approach can effectively distinguish the swallowing function in people of different ages and genders.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Information Engineering, Chang Gung University, No. 259, Wen-Hwa 1st Road, Kwei-Shan, Tao-Yuan 333, Taiwan. wyshieh@mail.cgu.edu.tw.

ABSTRACT
Dysphagia is a condition that happens when a person cannot smoothly swallow food from the mouth to the stomach. It causes malnourishment in patients, or can even cause death due to aspiration pneumonia. Recently, more and more researchers have focused their attention on the importance of swallowing and respiration coordination, and the use of non-invasive assessment systems has become a hot research trend. In this study, we aimed to integrate the timing and pattern monitoring of respiration and swallowing by using a portable and non-invasive approach which can be applied at the bedside in hospitals or institutions, or in a home environment. In this approach, we use a force sensing resistor (FSR) to detect the motions of the thyroid cartilage in the pharyngeal phase. We also use the surface electromyography (sEMG) to detect the contraction of the submental muscle in the oral phase, and a nasal cannula to detect nasal airflow for respiration monitoring during the swallowing process. All signals are received and processed for swallowing event recognition. A total of 19 volunteers participated in the testing and over 57 measurements were made. The results show that the proposed approach can effectively distinguish the swallowing function in people of different ages and genders.

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Related in: MedlinePlus

The processing of the submental muscle sEMG: (a) Before; (b) After.
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sensors-15-12428-f007: The processing of the submental muscle sEMG: (a) Before; (b) After.

Mentions: For submental muscle sEMG: We use the BIOPAC MP100 system [20] to record the sEMG signals (e.g., Figure 7a). The sEMG signals were filtered through a Butterworth digital filter (second-order band-pass filter) with a passband of 20–400 Hz, and smoothed using a 15-point moving average [21,22], as shown in Figure 7b. To identify the sEMG onset time, we fetch the data from the first three seconds and calculate the mean (M) with the standard deviation (SD). For the data (say: sEMG[i]) after the third second, we set a threshold (M + α · SD), where α is a factor ranged from 1 to 3 (the value of α should be determind by real signal patterns; in this work, we set the value of α as one.) If sEMG[i] is the first point of which the value is over the threshold, we mark it as the onset time point. Typically a swallow will finish in a few seconds. Therefore we fetch totally four-second data after the oneset time point for analysis. If sEMG[j] is the last point of which the value is over the threshold in this period, we mark it as the offset time point. The time between sEMG[i] and sEMG[j] is the “EMG duration”.


Development of a portable non-invasive swallowing and respiration assessment device.

Shieh WY, Wang CM, Chang CS - Sensors (Basel) (2015)

The processing of the submental muscle sEMG: (a) Before; (b) After.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507683&req=5

sensors-15-12428-f007: The processing of the submental muscle sEMG: (a) Before; (b) After.
Mentions: For submental muscle sEMG: We use the BIOPAC MP100 system [20] to record the sEMG signals (e.g., Figure 7a). The sEMG signals were filtered through a Butterworth digital filter (second-order band-pass filter) with a passband of 20–400 Hz, and smoothed using a 15-point moving average [21,22], as shown in Figure 7b. To identify the sEMG onset time, we fetch the data from the first three seconds and calculate the mean (M) with the standard deviation (SD). For the data (say: sEMG[i]) after the third second, we set a threshold (M + α · SD), where α is a factor ranged from 1 to 3 (the value of α should be determind by real signal patterns; in this work, we set the value of α as one.) If sEMG[i] is the first point of which the value is over the threshold, we mark it as the onset time point. Typically a swallow will finish in a few seconds. Therefore we fetch totally four-second data after the oneset time point for analysis. If sEMG[j] is the last point of which the value is over the threshold in this period, we mark it as the offset time point. The time between sEMG[i] and sEMG[j] is the “EMG duration”.

Bottom Line: All signals are received and processed for swallowing event recognition.A total of 19 volunteers participated in the testing and over 57 measurements were made.The results show that the proposed approach can effectively distinguish the swallowing function in people of different ages and genders.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Information Engineering, Chang Gung University, No. 259, Wen-Hwa 1st Road, Kwei-Shan, Tao-Yuan 333, Taiwan. wyshieh@mail.cgu.edu.tw.

ABSTRACT
Dysphagia is a condition that happens when a person cannot smoothly swallow food from the mouth to the stomach. It causes malnourishment in patients, or can even cause death due to aspiration pneumonia. Recently, more and more researchers have focused their attention on the importance of swallowing and respiration coordination, and the use of non-invasive assessment systems has become a hot research trend. In this study, we aimed to integrate the timing and pattern monitoring of respiration and swallowing by using a portable and non-invasive approach which can be applied at the bedside in hospitals or institutions, or in a home environment. In this approach, we use a force sensing resistor (FSR) to detect the motions of the thyroid cartilage in the pharyngeal phase. We also use the surface electromyography (sEMG) to detect the contraction of the submental muscle in the oral phase, and a nasal cannula to detect nasal airflow for respiration monitoring during the swallowing process. All signals are received and processed for swallowing event recognition. A total of 19 volunteers participated in the testing and over 57 measurements were made. The results show that the proposed approach can effectively distinguish the swallowing function in people of different ages and genders.

Show MeSH
Related in: MedlinePlus