Abstract
The increasing prevalence of functional and motility gastrointestinal (GI) disorders is at odds with bottlenecks in their diagnosis, treatment, and follow-up. Lack of noninvasive approaches means that only specialized centers can perform objective assessment procedures. Abnormal GI muscular activity, which is coordinated by electrical slow-waves, may play a key role in symptoms. As such, the electrogastrogram (EGG), a noninvasive means to continuously monitor gastric electrical activity, can be used to inform diagnoses over broader populations. However, it is seldom used due to technical issues: inconsistent results from single-channel measurements and signal artifacts that make interpretation difficult and limit prolonged monitoring. Here, we overcome these limitations with a wearable multi-channel system and artifact removal signal processing methods. Our approach yields an increase of 0.56 in the mean correlation coefficient between EGG and the clinical “gold standard”, gastric manometry, across 11 subjects (p < 0.001). We also demonstrate this system’s usage for ambulatory monitoring, which reveals myoelectric dynamics in response to meals akin to gastric emptying patterns and circadian-related oscillations. Our approach is noninvasive, easy to administer, and has promise to widen the scope of populations with GI disorders for which clinicians can screen patients, diagnose disorders, and refine treatments objectively.
Highlights
Fluoroscopic or endoscopic guidance, can differentiate between myopathic and neuropathic disorders and can change the diagnosis and treatment of 15% to 20% of patients with upper GI symptoms[9,10]
We used an interference cancellation approach where we first identified the artifact as interference in time using a linear minimum mean squared error estimation (LMMSE) with locally estimated mean and variance statistics, and subsequently subtracted it from the waveform
When comparing the traditional location to the highest signal-to-noise ratio (SNR) location from the electrode array, we found a significantly higher percentage of normal slow-waves in all 11 subjects (p = 1.4 × 10−4; Fig. 4c), which was further increased after artifact removal (p = 1.1 × 10−8; Fig. 4c)
Summary
Fluoroscopic or endoscopic guidance, can differentiate between myopathic and neuropathic disorders and can change the diagnosis and treatment of 15% to 20% of patients with upper GI symptoms[9,10]. Unlike the electrocardiogram (ECG; recordings of heart electrical activity), the EGG has not seen widespread clinical adoption due to its poor correlation with gastric emptying tests, manometry, and diagnosed disease status[24]. These unsatisfactory results arise in part from inconsistent and poor signal quality[25]. Independent component analysis (ICA), a popular approach for removing artifacts from the EEG31, is not ideal for removing non-stereotyped artifacts due to the unique spatial patterns on the recorded waveforms that adversely affect ICA decompositions[30] These types of artifacts are manually removed prior to ICA analysis[32,33]; such manual intervention limits the ability for widespread automated analyses in ambulatory recordings
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