Multi-day, multi-sensor ambulatory monitoring of gastric electrical activity

被引:18
|
作者
Paskaranandavadivel, Niranchan [1 ,2 ]
Angeli, Timothy R. [1 ]
Manson, Tabitha [1 ]
Stocker, Abigail [3 ]
McElmurray, Lindsay [3 ]
O'Grady, Gregory [1 ,2 ]
Abell, Thomas [3 ]
Cheng, Leo K. [1 ,4 ]
机构
[1] Univ Auckland, Auckland Bioengn Inst, Auckland, New Zealand
[2] Univ Auckland, Dept Surg, Auckland, New Zealand
[3] Univ Louisville Hosp, Louisville, KY USA
[4] Vanderbilt Univ, Dept Surg, Nashville, TN 37240 USA
关键词
slow wave; gastroparesis; dysrhythmia; ambulatory; SLOW-WAVE ACTIVITY; PROPAGATION; STIMULATION; PATTERNS; ELECTROGASTROGRAPHY; GASTROPARESIS; ORIGIN; SYSTEM;
D O I
10.1088/1361-6579/ab0668
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Objective: Bioelectrial signals known as slow waves play a key role in coordinating gastric motility. Slow wave dysrhythmias have been associated with a number of functional motility disorders. However, there have been limited human recordings obtained in the consious state or over an extended period of time. This study aimed to evaluate a robust ambulatory recording platform. Approach: A commercially available multi-sensor recording system (Shimmer3, ShimmerSensing) was applied to acquire slow wave information from the stomach of six humans and four pigs. First, acute experiments were conducted in pigs to verify the accuracy of the recording module by comparing to a standard widely employed electrophysiological mapping system (ActiveTwo, BioSemi). Then, patients with medically refractory gastroparesis undergoing temporary gastric stimulator implantation were enrolled and gastric slow waves were recorded from mucosally-implanted electrodes for 5 d continuously. Accelerometer data was also collected to exclude data segments containing excessive patient motion artefact. Main results: Slow wave signals and activation times from the Shimmer3 module were closely comparable to a standard electrophysiological mapping system. Slow waves were able to be recorded continuously for 5 d in human subjects. Over the 5 d, slow wave frequency was 2.8 +/- 0.6 cpm and amplitude was 0.2 +/- 0.3 mV. Significance: A commercial multi-sensor recording module was validated for recording electrophysiological slow waves for 5 d, including in ambulatory patients. Multiple modules could be used simultaneously in the future to track the spatio-temporal propagation of slow waves. This framework can now allow for patho-electrophysiological studies to be undertaken to allow symptom correlation with dysrhythmic slow wave events.
引用
收藏
页数:8
相关论文
共 50 条
  • [41] Multi-sensor observation fusion scheme based on 3D variational assimilation for landslide monitoring
    Liu, Chun
    Shao, Xiaohang
    Li, Weiyue
    GEOMATICS NATURAL HAZARDS & RISK, 2019, 10 (01) : 151 - 167
  • [42] Advances in multi-sensor fusion for body sensor networks: Algorithms, architectures, and applications
    Fortino, Giancarlo
    Gravina, Raffaele
    Ghasemzadeh, Hassan
    Liu, Peter X.
    Poon, Carmen C. Y.
    Wang, Zhelong
    INFORMATION FUSION, 2019, 45 : 150 - 152
  • [43] Development and testing of a wireless smart toolholder with multi-sensor fusion
    Zhang, Jin
    Kang, Xinzhen
    Ye, Zhengmao
    Liu, Lei
    Tao, Guibao
    Cao, Huajun
    FRONTIERS OF MECHANICAL ENGINEERING, 2023, 18 (04)
  • [44] A distributed architecture for storing and processing multi-channel multi-sensor athlete performance data
    Ride, Jason R.
    James, Daniel A.
    Lee, James B.
    Rowlands, David D.
    ENGINEERING OF SPORT CONFERENCE 2012, 2012, 34 : 403 - 408
  • [45] Multi-Sensor Platform for Automatic Disorders Detection in Circadian Rhythm
    Leone, A.
    Caroppo, A.
    Diraco, G.
    Rescio, G.
    Siciliano, P.
    2016 IEEE SENSORS, 2016,
  • [46] DATA PROCESSING AND RECORDING USING A VERSATILE MULTI-SENSOR VEHICLE
    Borgmann, Bjoern
    Schatz, Volker
    Kieritz, Hilke
    Scherer-Kloeckling, Clemens
    Hebel, Marcus
    Arens, Michael
    ISPRS TC I MID-TERM SYMPOSIUM INNOVATIVE SENSING - FROM SENSORS TO METHODS AND APPLICATIONS, 2018, 4-1 : 21 - 28
  • [47] Wearable Multi-Sensor Positioning Prototype for Rowing Technique Evaluation
    Mendoza, Luis Rodriguez
    O'Keefe, Kyle
    SENSORS, 2024, 24 (16)
  • [48] Multi-Sensor Integration in Orthopedic Implants for Total Knee Arthroplasty
    Gasnier, Pierre
    Nonglaton, Guillaume
    Fourcade, Paul
    Rammouz, Ramzy
    Brulais, Sebastien
    Gauroy, Martin
    Frassati, Francois
    Descharles, Melanie
    Gougis, Maxime
    Chatard, Charles
    Moroi, Cecile
    Le Stum, Mathieu
    Leconte, Liz
    Dardenne, Guillaume
    Fuchs, Olivier
    Stindel, Eric
    2024 IEEE SENSORS, 2024,
  • [49] Multi-sensor fusion for real-time object tracking
    Verma, Sakshi
    Singh, Vishal K. K.
    MULTIMEDIA TOOLS AND APPLICATIONS, 2024, 83 (07) : 19563 - 19585
  • [50] MULTI-RADAR MULTI-SENSOR (MRMS) QUANTITATIVE PRECIPITATION ESTIMATION Initial Operating Capabilities
    Zhang, Jian
    Howard, Kenneth
    Langston, Carrie
    Kaney, Brian
    Qi, Youcun
    Tang, Lin
    Grams, Heather
    Wang, Yadong
    Cocks, Stephen
    Martinaitis, Steven
    Arthur, Ami
    Cooper, Karen
    Brogden, Jeff
    Kitzmiller, David
    BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2016, 97 (04) : 621 - 637