Wearable sectorial electrical impedance tomography and k-means clustering for measurement of gastric processes. (1st September 2022)
- Record Type:
- Journal Article
- Title:
- Wearable sectorial electrical impedance tomography and k-means clustering for measurement of gastric processes. (1st September 2022)
- Main Title:
- Wearable sectorial electrical impedance tomography and k-means clustering for measurement of gastric processes
- Authors:
- Wicaksono, Ridwan
Darma, Panji Nursetia
Inoue, Atsuo
Tsuji, Hideyuki
Takei, Masahiro - Abstract:
- Abstract: A low-power and handy gastric data acquisition ( g -DAQ) system has been proposed to identify the gastric processes in the epigastric region with sectorial electrical impedance tomography ( s -EIT) and K-means sectorial clustering algorithm. The g -DAQ with a wearable abdominal sensor investigates gastric retention levels in the epigastric region during the emptying process. A C-runtime engine with Secure Shell protocol optimized an ARM microprocessor and field programmable gate array-based system with bidirectional channels to perform real-time data acquisition. The s -EIT algorithm projects the gastric conductivity distribution in the epigastric region into a cross-sectional image. K-means clustering method quantitatively identifies the gastric content images on the epigastric region to monitor the different clustered conductivity α k . The phantom experiments evaluated the s -EIT using liver-shaped, bone-shaped, and gastric-shaped phantoms in an abdominal-shaped vessel to distinguish gastric phantom conductivity. In human experiments, the proposed method was applied to measure 15 samples of the emptying process to evaluate the retention level of liquid gastric content. As a result, the proposed g -DAQ successfully performed a rapid acquisition at least 50 times faster than the conventional method in terms of the data acquisition rate. The developed g -DAQ with 110 mm × 66 mm × 51 mm of dimensions and 0.16 kg of weight took 0.32 sec to measure 208 points perAbstract: A low-power and handy gastric data acquisition ( g -DAQ) system has been proposed to identify the gastric processes in the epigastric region with sectorial electrical impedance tomography ( s -EIT) and K-means sectorial clustering algorithm. The g -DAQ with a wearable abdominal sensor investigates gastric retention levels in the epigastric region during the emptying process. A C-runtime engine with Secure Shell protocol optimized an ARM microprocessor and field programmable gate array-based system with bidirectional channels to perform real-time data acquisition. The s -EIT algorithm projects the gastric conductivity distribution in the epigastric region into a cross-sectional image. K-means clustering method quantitatively identifies the gastric content images on the epigastric region to monitor the different clustered conductivity α k . The phantom experiments evaluated the s -EIT using liver-shaped, bone-shaped, and gastric-shaped phantoms in an abdominal-shaped vessel to distinguish gastric phantom conductivity. In human experiments, the proposed method was applied to measure 15 samples of the emptying process to evaluate the retention level of liquid gastric content. As a result, the proposed g -DAQ successfully performed a rapid acquisition at least 50 times faster than the conventional method in terms of the data acquisition rate. The developed g -DAQ with 110 mm × 66 mm × 51 mm of dimensions and 0.16 kg of weight took 0.32 sec to measure 208 points per frame and consumed 3.67 Watt of average power operation. By drinking 500 ml of rehydration water with 0.69 S m −1 of conductivity, In subjects 1–4 and phantoms, the maximum R ( t ) was identified on t 1 as the gastric volume is fully bloated. During 30 min, the emptying liquid content was well-indicated because the minimum R ( t ) was identified on t 15 as an empty state. The mean of the measurement results is −0.0387 with the linear equation R ( t ) = −0.0387 t + 0.8105. In conclusion, the body mass index did not significantly affect the trendline. … (more)
- Is Part Of:
- Measurement science & technology. Volume 33:Number 9(2022)
- Journal:
- Measurement science & technology
- Issue:
- Volume 33:Number 9(2022)
- Issue Display:
- Volume 33, Issue 9 (2022)
- Year:
- 2022
- Volume:
- 33
- Issue:
- 9
- Issue Sort Value:
- 2022-0033-0009-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-09-01
- Subjects:
- sectorial EIT (s-EIT) -- g-DAQ -- SSH protocol -- K-means clustering -- gastric retention level
Physical measurements -- Periodicals
Scientific apparatus and instruments -- Periodicals
Equipment and Supplies -- Periodicals
Science -- instrumentation -- Periodicals
Technology -- instrumentation -- Periodicals
Mesures physiques -- Périodiques
Physical measurements
Scientific apparatus and instruments
Periodicals
502.87 - Journal URLs:
- http://iopscience.iop.org/0957-0233/ ↗
http://www.iop.org/Journals/mt ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1361-6501/ac6e2e ↗
- Languages:
- English
- ISSNs:
- 0957-0233
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 22058.xml