Empirical mode decomposition: a method to reduce low frequency interferences from surface electroenterogram

Body Surface Gastrointestinal Potential Mapping: A Simulation Framework to Evaluate Source Separation Algorithms. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-4. [PMID: 38083102 DOI: 10.1109/embc40787.2023.10340911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Gastrointestinal (GI) potential mapping could be useful for evaluating GI motility disorders. Such disorders are found in inflammatory bowel diseases, such as Crohn's disease, or GI functional disorders. GI potential mapping data originate from a mixture of several GI electrophysiological sources (termed ExG) and other noise sources, including the electrocardiogram (ECG) and respiration. Denoising and/or source separation techniques are required, however, with real measurements, no ground truth is available. In this paper we propose a framework for the simulation of body surface GI potential mapping data. The framework is an electrostatic model, based on fecgsyn toolbox, using dipoles as electrical sources for the heart, stomach, small bowel and colon, and an array of surface electrodes. It is shown to generate realistic ExG waveforms, which are then used to compare several ECG and respiration cancellation techniques, based on, fast independent component analysis (FastICA) and pseudo-periodic component analysis (PiCA). The best performance was obtained with PiCA with a median root mean squared error of 0.005.

Pilot Validation of a New Wireless Patch System as an Ambulatory, Noninvasive Tool That Measures Gut Myoelectrical Signals: Physiologic and Disease Correlations

BACKGROUND AND AIMS

Limited means exist to assess gastrointestinal activity in a noninvasive, objective way that is highly predictive of underlying motility disorders. The aim of this paper is to demonstrate the feasibility of recording myoelectric gastrointestinal activity by cutaneous patches and to correlate myoelectric signals with gastrointestinal function in various clinical settings.

METHODS

A novel wireless patch system (WPS) (G-Tech Medical) that acquires gastrointestinal myoelectrical signals was placed on the patients' anterior abdomens. Data were transmitted wirelessly to a mobile device with a user interface and forwarded to a cloud server where processing algorithms identified episodes of motor activity, quantified their parameters, and nominally assigned them to specific gastrointestinal organs based on their frequencies.

RESULTS

The inherent reproducibility of the WPS measurement technique itself and from the underlying gut activity, coupled with source validation and sensitivity to changes in gut activity in several physiologic and pathologic states, demonstrates its feasibility, safety, and performance in clinical settings.

CONCLUSIONS

The novel WPS technology, measuring myoelectric intestinal activity noninvasively and continuously over multiple days, is feasible in a wide range of clinical settings, highlighting its promise in the diagnosis and management of motility disorders. Further research is required for more extensive validation and to determine how best to employ this information to optimize patient care.

Alterations in Spectral Attributes of Surface Electromyograms after Utilization of a Foot Drop Stimulator during Post-Stroke Gait

BACKGROUND

A foot drop stimulator (FDS) is a rehabilitation intervention that stimulates the common peroneal nerve to facilitate ankle dorsiflexion at the appropriate time during post-stroke hemiplegic gait. Time-frequency analysis (TFA) of non-stationary surface electromyograms (EMG) and spectral variables such as instantaneous mean frequency (IMNF) can provide valuable information on the long-term effects of FDS intervention in terms of changes in the motor unit (MU) recruitment during gait, secondary to improved dorsiflexion.

OBJECTIVE

The aim of this study was to apply a wavelet-based TFA approach to assess the changes in neuromuscular activation of the tibialis anterior (TA), soleus (SOL), and gastrocnemius (GA) muscles after utilization of an FDS during gait post-stroke.

METHODS

Surface EMG were collected bilaterally from the TA, SOL, and GA muscles from six participants (142.9 ± 103.3 months post-stroke) while walking without the FDS at baseline and 6 months post-FDS utilization. Continuous wavelet transform was performed to get the averaged time-frequency distribution of band pass filtered (20-300 Hz) EMGs during multiple walking trials. IMNFs were computed during normalized gait and were averaged during the stance and swing phases. Percent changes in the energies associated with each frequency band of 25 Hz between 25 and 300 Hz were computed and compared between visits.

RESULTS

Averaged time-frequency representations of the affected TA, SOL, and GA EMG show altered spectral attributes post-FDS utilization during normalized gait. The mean IMNF values for the affected TA were significantly lower than the unaffected TA at baseline (p = 0.026) and follow-up (p = 0.038) during normalized stance. The mean IMNF values significantly increased (p = 0.017) for the affected GA at follow-up during normalized swing. The frequency band of 250-275 Hz significantly increased in the energies post-FDS utilization for all muscles.

CONCLUSION

The application of wavelet-based TFA of EMG and outcome measures (IMNF, energy) extracted from the time-frequency distributions suggest alterations in MU recruitment strategies after the use of FDS in individuals with chronic stroke. This further establishes the efficacy of FDS as a rehabilitation intervention that may promote motor recovery in addition to treating the secondary complications of foot drop due to post-stroke hemiplegia.

Empirical Mode Decomposition of simulated and real ultrasonic Doppler signals of periodic fetal activity

Simulated signals comprising components (trains of Gaussian packets) resulting from cardiac movements and from pseudorespiratory movements with added white noise were submitted to Empirical Mode Decomposition. The increase of sampling frequency fs (from 0.5 kHz to 5 kHz) for given signal to noise ratio SNR moves signal components toward higher order intrinsic mode functions (IMFs) and increases their number. The increase of the SNR (from -5 dB to 10 dB, fixed fs) moves the signal components to lower order IMFs. The separation of components is most efficient for SNR≥5 dB and fs not exceeding 1 kHz, for lower SNRs fs should be at least 2 kHz. SNR=∞ results in erroneous decomposition and therefore limited noise level is beneficial. Recommended number of sifting iterations is 10. Fetal data obtained using 2 MHz emission frequency and sampled at 2 kHz were decomposed. The cardiac signal always appears in IMF3, frequently also in IMF1 and IMF2. The pseudobreathing signal, appearing mainly in IMF4-6, is easy to separate. Signals resulting from fetal displacements due to maternal respiration appear in IMF7 or IMF8. The EMD performs better than the classic linear filtering as a tool for separation of the pseudorespiration signals and provides inferior results in terms of separation of the cardiac signals.

Active concentric ring electrode for non-invasive detection of intestinal myoelectric signals

Although the surface electroenterogram (EEnG) is a weak signal contaminated by strong physiological interference, such as ECG and respiration, abdominal surface recordings of the EEnG could provide a non-invasive method of studying intestinal activity. The goal of this work was to develop a modular, active, low-cost and easy-to-use sensor to obtain a direct estimation of the Laplacian of the EEnG on the abdominal surface in order to enhance the quality of bipolar surface monitoring of intestinal activity. The sensor is made up of a set of 3 concentric dry Ag/AgCl ring electrodes and a battery-powered signal-conditioning circuit. Each section is etched on a different printed circuit board (PCB) and the sections are joined to each other by surface mount technology connectors. This means the sensing electrodes can be treated independently for purposes of maintenance and replacement and the signal conditioning circuit can be re-used. A total of ten recording sessions were carried out on humans. The results show that the surface recordings of the EEnG obtained by the active sensor present significantly less ECG and respiration interference than those obtained by bipolar recordings. In addition, bioelectrical sources whose frequency fitted with the slow wave component of the EEnG (SW) were identified by parametric spectral analysis in the surface signals picked up by the active sensors.

The detection of intestinal spike activity on surface electroenterograms

Myoelectrical recording could provide an alternative technique for assessing intestinal motility, which is a topic of great interest in gastroenterology since many gastrointestinal disorders are associated with intestinal dysmotility. The pacemaker activity (slow wave, SW) of the electroenterogram (EEnG) has been detected in abdominal surface recordings, although the activity related to bowel contractions (spike bursts, SB) has to date only been detected in experimental models with artificially favored electrical conductivity. The aim of the present work was to assess the possibility of detecting SB activity in abdominal surface recordings under physiological conditions. For this purpose, 11 recording sessions of simultaneous internal and external myolectrical signals were conducted on conscious dogs. Signal analysis was carried out in the spectral domain. The results show that in periods of intestinal contractile activity, high-frequency components of EEnG signals can be detected on the abdominal surface in addition to SW activity. The energy between 2 and 20 Hz of the surface myoelectrical recording presented good correlation with the internal intestinal motility index (0.64 +/- 0.10 for channel 1 and 0.57 +/- 0.11 for channel 2). This suggests that SB activity can also be detected in canine surface EEnG recording.