Waveform Variation Research Articles

Medial entorhinal cortex activates in a traveling wave in the rat.

Traveling waves are hypothesized to support the long-range coordination of anatomically distributed circuits. Whether separate strongly interacting circuits exhibit traveling waves remains unknown. The hippocampus exhibits traveling 'theta' waves and interacts strongly with the medial entorhinal cortex (MEC). To determine whether the MEC also activates in a traveling wave, we performed extracellular recordings of local field potentials (LFP) and multi-unit activity along the MEC. These recordings revealed progressive phase shifts in activity, indicating that the MEC also activates in a traveling wave. Variation in theta waveform along the region, generated by gradients in local physiology, contributed to the observed phase shifts. Removing waveform-related phase shifts left significant residual phase shifts. The residual phase shifts covaried with theta frequency in a manner consistent with those generated by weakly coupled oscillators. These results show that the coordination of anatomically distributed circuits could be enabled by traveling waves but reveal heterogeneity in the mechanisms generating those waves.

Low-frequency variability in photoplethysmographic waveform and heart rate during on-pump cardiac surgery with or without cardioplegia

We studied the properties of low-frequency (LF) heart rate variability (HRV) and photoplethysmographic waveform variability (PPGV) and their interaction under conditions where the hemodynamic connection between them is obviously absent, as well as the LF regulation of PPGV in the absence of heart function. The parameters of HRV and finger PPGV were evaluated in 10 patients during cardiac surgery under cardiopulmonary bypass (on-pump cardiac surgery) with or without cardioplegia. The following spectral indices of PPGV and HRV were ertimated: the total spectral power (TP), the high-frequency (HF) and the LF ranges of TP in percents (HF% and LF%), and the LF/HF ratio. We assessed also the index S of synchronization between the LF oscillations in finger photoplethysmogram (PPG) and heart rate (HR) signals. The analysis of directional couplings was carried out using the methods of phase dynamics modeling. It is shown that the mechanisms leading to the occurrence of oscillations in the LF range of PPGV are independent of the mechanisms causing oscillations in the LF range of HRV. At the same time, the both above-mentioned LF oscillations retain their activity under conditions of artificial blood circulation and cardioplegia (the latter case applies only to LF oscillations in PPG). In artificial blood circulation, there was a coupling from the LF oscillations in PPG to those in HR, whereas the coupling in the opposite direction was absent. The coupling from the LF oscillations in PPG to those in HR has probably a neurogenic nature, whereas the opposite coupling has a hemodynamic nature (due to cardiac output).

Quantitative Comparison of the Performance of Piezoresistive, Piezoelectric, Acceleration, and Optical Pulse Wave Sensors.

The accurate measurement of the arterial pulse wave is beneficial to clinical health assessment and is important for the effective diagnosis of many types of cardiovascular disease. A variety of sensors have been developed for the non-invasive detection of these waves, but the type of sensor has an impact on the measurement results. Therefore, it is necessary to compare and analyze the signals obtained under a range of conditions using various pulse sensors to aid in making an informed choice of the appropriate type. From the available types we have selected four: a piezoresistive strain gauge sensor (PESG) and a piezoelectric Millar tonometer (the former with the ability to measure contact force), a circular film acceleration sensor, and an optical reflection sensor. Pulse wave signals were recorded from the left radial, carotid, femoral, and digital arteries of 60 subjects using these four sensors. Their performance was evaluated by analyzing their susceptibilities to external factors (contact force, measuring site, and ambient light intensity) and by comparing their stability and reproducibility. Under medium contact force, the peak-to-peak amplitude of the signals was higher than that at high and low force levels and the variability of signal waveform was small. The optical sensor was susceptible to ambient light. Analysis of the intra-class correlation coefficients (ICCs) of the pulse wave parameters showed that the tonometer and accelerometer had good stability (ICC > 0.80), and the PESG and optical sensor had moderate stability (0.46 < ICC < 0.86). Intra-observer analysis showed that the tonometer and accelerometer had good reproducibility (ICC > 0.75) and the PESG and optical sensor had moderate reproducibility (0.42 < ICC < 0.91). Inter-observer analysis demonstrated that the accelerometer had good reproducibility (ICC > 0.85) and the three other sensors had moderate reproducibility (0.52 < ICC < 0.96). We conclude that the type of sensor and measurement site affect pulse wave characteristics and the careful selection of appropriate sensor and measurement site are required according to the research and clinical need. Moreover, the influence of external factors such as contact pressure and ambient light should be fully taken into account.

Non-periodicity of blood flow and its influence on wall shear stress in the carotid artery bifurcation: An in vivo measurement-based computational study

Although arterial blood flow is physiologically non-periodic under resting conditions, periodic flow assumption has been widely adopted in most hemodynamic studies. So far, it remains unclear how the non-periodicity of blood flow would influence local hemodynamic parameters, especially wall shear stress (WSS) that associates closely with endothelial function and vascular disease. In this study, numerical simulations of blood flows in sixteen normal carotid artery bifurcations were performed under measured non-periodic and averaged periodic flow conditions, respectively, with the obtained results being compared in terms of five typical WSS metrics (i.e., mean WSS (MWSS), time-averaged WSS (TAWSS), oscillatory shear index (OSI), transverse WSS (transWSS), and average temporal gradient of WSS (WSSTG)) in the atheroprone low-WSS regions. It was found that simplifying the physiologically non-periodic flow condition into a periodic one did not significantly alter the major features of WSS distribution, but resulted in underestimations of some WSS metrics. Specifically, the degree of underestimation was largest (27.2% ± 8.3%) for WSSTG, smallest (0.5% ± 0.4%) for MWSS, while moderate (5.1% ± 3.2% ~ 9.2% ± 4.1%) for other WSS metrics. Statistical analyses revealed that the cycle-to-cycle variability of flow velocity waveform (var-V) and the planarity of internal carotid artery correlated strongly with the periodic flow assumption-induced underestimations of WSS metrics. These findings suggest that taking the non-periodic characteristic of blood flow into consideration could be important for studying hemodynamics in arteries with a large var-V or specific morphological characteristics, especially when WSSTG is the main hemodynamic parameter of concern.

Modified high-resolution wavenumber analysis for detection of pulse wave velocity using coefficient of variation of arterial wall acceleration waveforms.

In high-resolution wavenumber analysis for detection of pulse wave velocity (PWV), phase information of analytic signals is used to estimate the wavenumber. However, the phase information could be affected by the adjacent signals in the temporal direction. Therefore, we propose a modified high-resolution wavenumber analysis technique using real acceleration waveforms of the arterial wall. In the modified wavenumber analysis, we propose a new evaluation function that corresponds to the inverse of the squared coefficient of variation. The accuracy of estimation of PWV was investigated by performing simulations, and the feasibility was also examined in an in vivo experiment. In the simulation experiments, the estimation accuracy using the proposed method was comparable to that using the previous method using phase information. However, when the pulse wave included the reflection components, the PWV estimated using the proposed method was more stable than that estimated using the previous method. Also, in the in vivo experiments, at opening of the aortic valve, the velocity estimated by the proposed method was almost equal to that estimated by the previous method (previous: 2.97 ± 1.2m/s, proposed: 4.82 ± 1.4m/s). Meanwhile, when the reflection components were present, the estimated PWV values yielded by the previous and proposed methods were - 1.13 and - 3.50 ± 0.9m/s, respectively. The PWVs at those two time points estimated by the previous method were quite different, and the PWV estimate was considered to be more affected by the reflected waves. The results of the simulations and in vivo experiments indicated that the modified high-resolution wavenumber analysis method was less affected by the reflected waves and more accurate in estimation of PWVs of both the forward and reflected waves.

Concrete strength monitoring based on the variation of ultrasonic waveform acquired by piezoelectric aggregates

Ultrasonic waves provide a non-destructive and sensitive way to monitor the concrete hydration. However, limited works are reported to monitor the evolution of the mechanical parameter at early ages. In this study, modified piezoelectric aggregates are embedded inside a concrete beam to excite and receive primary waves. A hydration index, namely, the variation of ultrasonic waveform (VUW) is developed to characterize the variation of the transmitted waves during the hydration process. The recorded hydration indices are compared with the compressive strength measured by destructive test at different ages. The results show that the VUW is closer to the compressive strength than the other two traditional hydration indices, ultrasonic velocity and wave packet energy. The proposed VUW provides a simple and accurate way to monitor the concrete hydration at early ages.

Spinal genesis of Mayer waves.

Variability in cardiovascular spectra was first described by Stephan Hales in 1733. Traube and Hering initially noted respirophasic variation of the arterial pressure waveform in 1865 and Sigmund Mayer noted a lower frequency oscillation of the same in anesthetized rabbits in 1876. Very low frequency oscillations were noted by Barcroft and Nisimaru in 1932, likely representing vasogenic autorhythmicity. While the origins of Traube Hering and very low frequency oscillatory variability in cardiovascular spectra are well described, genesis mechanisms and functional significance of Mayer waves remain in controversy. Various theories have posited baroreflex and central supraspinal mechanisms for genesis of Mayer waves. Several studies have demonstrated the persistence of Mayer waves following high cervical transection, indicating a spinal capacity for genesis of these oscillations. We suggest a general tendency for central sympathetic neurons to oscillate at the Mayer wave frequency, the presence of multiple Mayer wave oscillators throughout the brainstem and spinal cord, and possible contemporaneous genesis by baroreflex and vasomotor mechanisms.

The Monitoring of Milling Tool Tipping by Estimating Holder Exponents of Vibration

The gradual tool wear is unavoidable in the machining process, it directly influences the surface integrity and dimensional tolerances of the components. The tool condition monitoring (TCM) systems have the capacity to make full use of the cutting potential of the cutting tools, which is of great significance for improving production efficiency and ensuring product quality. In milling titanium alloys, tool tipping is one of the main failure modes. Therefore, this study focuses on establishing a tool tipping monitoring approach for the milling process. The singularity analysis method based on wavelet transform was employed to characterize the variation of vibration waveforms quantitatively with the Holder Exponent (HE) index. The probability density distribution and statistical analysis were adopted to extract effective HE features from the HE indexes to correlate with the different tool conditions. The mutual information method was adopted to rank the discriminability of the HE statistical parameters. Then, several machine learning (ML) models were established with the screened HE features. Finally, the results of the experiments indicate that the Support Vector Machine (SVM) model has the highest classification accuracy and can provide practical guides on the tool changes.

Joint Optimization of Transmit Waveform and Receive Filter with Pulse-to-Pulse Waveform Variations for MIMO GMTI.

Multi-input multi-output (MIMO) is usually defined as a radar system in which the transmit time and receive time, space and transform domain can be separated into multiple independent signals. Given the bandwidth and power constraints of the radar system, MIMO radar can improve its performance by optimize design transmit waveforms and receive filters, so as to achieve better performance in suppressing clutter and noise. In this paper, we cyclicly optimize the transmit waveform and receive filters, so as to maximize the output signal interference and noise ratio (SINR). From fixed pulse-to-pulse waveform to pulse-to-pulse waveform variations, we discuss the joint optimization under energy constraint, then extend it to optimizations under constant-envelope constraint and similarity constraint. Compared to optimization with fixed pulse-to-pulse waveform, the generalized optimization achieves higher output SINR and lower minimum detectable velocity (MDV), further improve the suppressing performance.

A novel method for extracting interictal epileptiform discharges in multi-channel MEG: Use of fractional type of blind source separation

ObjectiveVisual inspection of interictal epileptiform discharges (IEDs) in multi-channel MEG requires a time-consuming evaluation process and often leads to inconsistent results due to variability of IED waveforms. Here, we propose a novel extraction method for IEDs using a T/k type of blind source separation (BSST/k). MethodsWe applied BSST/k with seven patients with focal epilepsy to test the accuracy of identification of IEDs. We conducted comparisons of the results of BSS components with those obtained by visual inspection in sensor-space analysis. ResultsBSST/k provided better signal estimation of IEDs compared with sensor-space analysis. Importantly, BSST/k was able to uncover IEDs that could not be detected by visual inspection. Furthermore, IED components were clearly extracted while preserving spike and wave morphology. Variable IED waveforms were decomposed into one dominant component. ConclusionsBSST/k was able to visualize the spreading signals over multiple channels into a single component from a single epileptogenic zone. BSST/k can be applied to focal epilepsy with a simple parameter setting. SignificanceOur novel method was able to highlight IEDs with increased accuracy for identification of IEDs from multi-channel MEG data.

The intensity of oscillations of the photoplethysmographic waveform variability at frequencies 0.04–0.4 Hz is effective marker of hypertension and coronary artery disease in males

Background: It is believed that the intensity of oscillations in the photoplethysmographic waveform variability reflects the activity of vascular regulatory mechanisms. However, the relationship of such fluctuations with the state of health is poorly understood.Purpose: The aim of our study was to assess the possibility of using spectral indices that reflect the intensity of oscillations of the photoplethysmographic waveform variability at frequencies 0.04-0.4 Hz as markers of hypertension and coronary artery disease. We did not study women to exclude the influence of menopause and sex hormones on the results.Materials and Methods: We compared synchronous 10-minute records of finger photoplethysmogram and respiration at rest in 30 healthy males (48.8 ± 4.5 years; data presented as Mean ± SD) versus 30 patients with hypertension (aged 49.0 ± 4.3 years) versus 30 patients with stable coronary artery disease (49.2 ± 4.8 years). Percentages of high-frequency and low-frequency ranges in the total power of photoplethysmographic waveform variability spectrum (HF% and LF%), and LF/HF ratio were assessed.Results: HF% are subject to by 2- to 5-fold increase in hypertensive patients (p < .001) and up to an 8-fold increase in patients with coronary artery disease (p < .001) when compared with healthy persons. On the contrary, LF% is reduced by 1.5-5 times in all patients when compared with healthy people (p < .001). We identified cut-off points for each photoplethysmographic index to distinguish patients with coronary artery disease or hypertension from healthy subjects. Multiple logistic regression models based on photoplethysmographic waveform variability indices had sufficient sensitivity and specificity for patients with hypertension or coronary artery disease.Conclusion: Frequency-domain indices of photoplethysmographic waveform variability (in particular, HF%, LF%, and LF/HF) are sufficiently sensitive and specific markers of hypertension and coronary artery disease in adult males.

Beat to Beat Modulation of Arterial Pulse Wave Velocity Induced by Vascular Smooth Muscle Tone.

The level of smooth muscle activation or `tone' (VSMT) can be defined as an intrinsic spontaneous level of vasoconstriction that may change in response to biomechanical stimuli such as flow, pressure, hormonal stimuli, neural stimuli, and drugs. Arteries can actively modify arterial pressure pulse wave velocity (PWV) by changing smooth muscle tone and diameter with little change in the mean arterial blood pressure. To evaluate the influence of aortic VSMT in terms of beat to beat PWV variations. Aortic pressure-diameter (P-D) relationships were invasively evaluated in five conscious animals. An `incremental' PWV was directly derived from the P-D loops, both in purely elastic conditions as well as in the presence of VSMT. Beat to beat PWV waveform variations showed different behavior, where mean PWV values were higher when VSMT was included in the P-D evaluation. Changes in incremental beat to beat PWV could be attributed to the influence of VSMT.

Individuals with knee osteoarthritis present increased gait pattern deviations as measured by a knee-specific gait deviation index

BackgroundA biomechanical analysis can provide valuable information on osteoarthritis (OA) gait, but important multidimensional interactions are often ignored. The Gait Deviation Index (GDI) was designed to address the issue of data complexity in gait analyses by providing a single, encompassing, value for one’s deviation from a normative reference group. Research QuestionThe primary aim of this study was to examine differences in a knee-specific GDI among young adults, and older individuals with and without knee OA. Secondarily, we aimed to examine these differences while controlling for gait speed. MethodSagittal and frontal plane knee joint angles and moments were used in the computation of a GDI among young adults, and older individuals with and without knee OA. The GDI was calculated such that scores ≥100% were considered typical young-healthy gait and a 10% decrease below 100 equated to 1 standard deviation from typical gait. Scores were first examined using a one-way analysis of variance, and examined again after correcting for gait speed. ResultsThe GDI was calculated for three groups: young-healthy adults (n = 52), older individuals without knee OA (n = 56), and individuals with knee OA (n = 191). Those with knee osteoarthritis exhibited a mean GDI of 87.2 (11.1), which was significantly lower than young adults (99.6 (10.6); p < 0.001) and older individuals without knee OA (94.3 (11.0); p < 0.001). Differences in GDI remained consistent after controlling for gait speed. Knee OA gait waveforms displayed significant variability across similar GDIs, specifically in frontal plane patterns. ConclusionThose with knee osteoarthritis exhibited lower (worse) GDIs compared to those without knee osteoarthritis and young, healthy individuals. After correcting for gait speed, these findings did not change. The GDI highlighted the significant variability in gait waveforms within individuals with knee OA, but the clinical utility of the GDI score itself remains limited.

Recursive Decomposition of Electromyographic Signals With a Varying Number of Active Sources: Bayesian Modeling and Filtering.

This paper describes a sequential decomposition algorithm for single-channel intramuscular electromyography (iEMG) generated by a varying number of active motor neurons. As in previous work, we establish a hidden Markov model of iEMG, in which each motor neuron spike train is modeled as a renewal process with inter-spike intervals following a discrete Weibull law and motor unit action potentials are modeled as impulse responses of linear time-invariant systems with known prior. We then expand this model by introducing an activation vector associated with the state vector of the hidden Markov model. This activation vector represents recruitment/derecruitment of motor units and is estimated together with the state vector using Bayesian filtering. Non-stationarity of the model parameters is addressed by means of a sliding window approach, thus making the algorithm adaptive to variations in contraction force and motor unit action potential waveforms. The algorithm was validated using simulated and experimental iEMG signals with varying number of active motor units. The experimental signals were acquired from the tibialis anterior and abductor digiti minimi muscles by fine wire and needle electrodes. The decomposition accuracy in both simulated and experimental signals exceeded 90%. The recruitment/derecruitment was successfully tracked by the algorithm. Because of its parallel structure, this algorithm can be efficiently accelerated, which lays the basis for its real-time applications in human-machine interfaces. The proposed method substantially broadens the domains of applicability of the algorithm.

Robust heart rate estimation using combined ECG and PPG signal processing

Heart rate variability (HRV) from recorded electrocardiograms (ECG) is a well-known diagnostic method for the assessment of autonomic nervous function of the heart, which is widely used to predict clinically relevant outcomes in the critical care setting, to risk stratify patients, and predict outcomes such as mortality. The morphological variations in the ECG waveform and the high degree of heterogeneity in the QRS complex often make it difficult to identify R waves, which may preclude the accurate analysis for HRV. Photoplethysmographic (PPG) signal can provide information about both the cardiovascular and respiratory systems and have extremely high degree of correlation with ECG during cardiac cycle. In this paper, we developed robust algorithm for high-resolution inter-beat waveform extraction using combined ECG and PPG analysis, which is highly needed for accurate HRV estimation. The simulation results showed high performance for inter-beat waveform detection in different cases that identifies missing/extra peaks in the QRS detection algorithm.

Reflector dip estimates based on seismic waveform curvature/flexure analysis

Reliable estimation of the reflector dip serves as a fundamental and essential tool for subsurface structure interpretation from 3D seismic surveys. We have developed a new method for accurate dip estimation, which consists of two major components. First, the curvature/flexure concept is adapted from the traditional reflector geometry analysis to work for the seismic waveforms, denoted as the waveform curvature and waveform flexure, respectively. Physically, both of them are capable of measuring the most and least apparent variation of the local waveforms in a seismic profile, and thus the corresponding measuring orientations represent the normal and dipping directions of the seismic reflectors, respectively. Second, the complex seismic trace is incorporated into our workflow of waveform curvature/flexure analysis to enhance the accuracy of dip estimation in the presence of seismic noises, especially in the zones of weak reflection intensity, such as zero crossings. The added values of our method are verified through various applications, such as horizon tracking and fault detection, to two 3D seismic data sets, one from the Netherlands North Sea and the other from the Great South Basin in New Zealand that is rich of faults. The results not only demonstrate the good accuracy of the generated dip vectors in guiding the seeded horizon tracking, but they also hold great potential for assisting seismic interpretation in more ways, such as structural-oriented filtering and attribute analysis.

The effects of variation in the arterial pulse waveform on perivascular flow

Cerebrospinal fluid (CSF) enters nervous tissues through perivascular spaces. Flow through these pathways is important for solute transport and to prevent fluid accumulation. Syringomyelia is commonly associated with subarachnoid space obstructions such as Chiari I malformation. However, the mechanism of development of these fluid-filled cavities is unclear. Studies have suggested that changes in the arterial and CSF pressures could alter normal perivascular flow. This study uses an idealised model of the perivascular space to investigate how variation in the arterial pulse influences fluid flow. The model used simulated subarachnoid pressures from healthy controls (N = 9), Chiari patients with (N = 7) and without (N = 8) syringomyelia. A parametric analysis was conducted to determine how features of the arterial pulse altered flow. The features of interest included: the timing and magnitude of the peak displacement, and the area under the curve in the phases of uptake and decline. A secondary aim was to determine if the previously observed differences between subject groups were sensitive to variation in the arterial pulse wave. The study demonstrated that the Chiari patients without a syrinx maintained a significantly higher level of perivascular inflow over a physiologically likely range of pulse wave shapes. The analysis also suggested that age-related changes in the arterial pulse (i.e. increased late systolic pulse amplitude and faster diastolic decay), could increase resistance to perivascular inflow affecting solute transport.

Quantitative Comparison of Photoplethysmographic Waveform Characteristics: Effect of Measurement Site.

Introduction: Photoplethysmography (PPG) has been widely used to assess cardiovascular function. However, few studies have comprehensively investigated the effect of measurement site on PPG waveform characteristics. This study aimed to provide a quantitative comparison on this.Methods: Thirty six healthy subjects participated in this study. For each subject, PPG signals were sequentially recorded for 1 min from six different body sites (finger, wrist under (anatomically volar), wrist upper (dorsal), arm, earlobe, and forehead) under both normal and deep breathing patterns. For each body site under a certain breathing pattern, the mean amplitude was firstly derived from recorded PPG waveform which was then normalized to derive several waveform characteristics including the pulse peak time (Tp), dicrotic notch time (Tn), and the reflection index (RI). The effects of breathing pattern and measurement site on the waveform characteristics were finally investigated by the analysis of variance (ANOVA) with post hoc multiple comparisons.Results: Under both breathing patterns, the PPG measurements from the finger achieved the highest percentage of analyzable waveforms for extracting waveform characteristics. There were significant effects of breathing pattern on Tn and RI (larger Tn and smaller RI with deep breathing on average, both p < 0.03). The effects of measurement site on mean amplitude, Tp, Tn, and RI were significant (all p < 0.001). The key results were that, under both breathing patterns, the mean amplitude from finger PPG was significantly larger and its Tp and RI were significantly smaller than those from the other five sites (all p < 0.001, except p = 0.04 for the Tp of “wrist under”), and Tn was only significantly larger than that from the earlobe (both p < 0.05).Conclusion: This study has quantitatively confirmed the effect of PPG measurement site on PPG waveform characteristics (including mean amplitude, Tp, Tn, and RI), providing scientific evidence for a better understanding of the PPG waveform variations between different body sites.

Analysis on the influence mechanism of conical shock wave on pulsed laser forward detection

In order to study the influence mechanism of conical shock waves on pulsed laser forward detection, an analytical method is proposed for arbitrary Mach number and cone angle conditions. Based on traditional gas dynamics and physical optics, a simplified model of Gaussian beam transmission across the conical shock wave flow field is established. On this basis, combined with the process of pulsed laser detection, the analytical expression of pulsed laser echo waveform under the influence of shock wave is derived. Simulation results show that the conical shock wave under different conditions can lead to beam deflection, focus, and reflection to different degrees. Furthermore, the variation of echo waveform caused by aero-optical effect is also analyzed, and it is shown that the peak power, pulse width and arrival time of echo all fluctuate greatly with rolling motion at different shock angle and cone angle, among which the shift of the arrival time and the reflection effect of shock wave have the largest impact on laser detection.

External Loading Effects on Guided Wave Magnetostrictive Sensor Using a Surface-Bonded Nickel Patch

This paper presents the external loading effects on an ultrasonic guided wave (GW) magnetostrictive sensor using a nickel disk patch permanently attached to a thin metallic waveguide plate. The circular magnetostrictive patch transducer (CMPT) consists of the surface-bonded nickel patch and a detachable magnetic circuit device enclosing a ring-shaped sensing coil and cylindrical biasing magnets. Various compressive and tensile stresses were applied to the nickel patch on account of the buckling response of the plate structure. Strain gauges attached to the nickel patch, a Hall effect sensing device, and a laser displacement sensor were utilized to verify the in-plane deformation and the corresponding magnetic flux density change of the nickel patch and the plate's central deflection, respectively, under various external loading conditions of the plate. Several PZT wafers also mounted to the plate were individually used to generate a 30 kHz toneburst GW, which is less sensitive to local stiffness changes of the plate due to the buckling mode. The external loading effects on the CMPT were determined by evaluating the peak-to-peak amplitude variation of the direct arrival waveform of the GW signals acquired by the PZT and CMPT sensor networks. The experimental results demonstrate that the external load applied to the waveguide structure induces compressive and tensile stresses in the nickel patch, leading to distorted GW sensing performance and the directional pattern of the CMPT. Although the presented CMPT has an omnidirectional sensing profile due to its design configuration, the planar-stressed CMPT exhibits a specific directional sensing performance as a result of the stress-induced anisotropic magnetostriction of the nickel disk patch.