Coronary microvascular dysfunction and autoregulatory capacity interfere with resting Dicrotic notch morphology.

Coronary microvascular vasodilator capacity is substantially associated with coronary pressure waveform and dicrotic notch morphology, with or without concomitant epicardial disease. A prominent dicrotic notch is associated with preserved microvascular vasodilatory capacity and adequate resting microvascular tonus without relative hyperaemic state, cumulatively indicating a better microcirculatory health.

BP-Diff: a conditional diffusion model for cuffless continuous BP waveform estimation using U-Net.

OBJECTIVE: Continuous monitoring of blood pressure (BP) is crucial for daily healthcare. Although invasive methods provide accurate continuous BP measurements, they are not suitable for routine use. Photoplethysmography (PPG), a non-invasive technique that detects changes in blood volume within the microcirculation using light, shows promise for BP measurement. The primary goal of this study is to develop a novel cuffless method based on PPG for accurately estimating continuous BP. Approach. We introduce BP-Diff, an end-to-end method for cuffless continuous BP waveform estimation utilizing a conditional diffusion probability model combined with a U-Net architecture. This approach takes advantage of the stochastic properties of diffusion models and the strong feature representation capabilities of U-Net. It integrates the continuous BP waveform as the initial status and uses the PPG signal and its derivatives as conditions to guide the training and sampling process. Main results. BP-Diff was evaluated using both uncalibrated and calibrated schemes. The results indicate that, when uncalibrated, BP-Diff can accurately track BP dynamics, including peak and valley positions, as well as timing. After calibration, BP-Diff achieved highly accurate BP estimations. The mean absolute error (MAE) of the estimated BP waveforms, along with the systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) from the calibrated BP-Diff model, were 2.99 mmHg, 2.6 mmHg, 1.4 mmHg, and 1.44 mmHg, respectively. Consistency tests, including Bland-Altman analysis and Pearson correlation, confirmed its high reliability compared to reference BP. BP-Diff meets the American Association for Medical Instrumentation (AAMI) standards and has achieved a Grade A from the British Hypertension Society (BHS). Significance. This study utilizes PPG signals to develop a novel cuffless continuous BP measurement method, demonstrating superiority over existing approaches. The method is suitable for integration into wearable devices, providing a practical solution for continuous BP monitoring in everyday healthcare.

Traveling wave network location method based on adaptive waveform similarity.

High-voltage transmission technology can effectively address the issue of uneven spatial and temporal energy distribution, leading to its rapid development in recent years. To address the challenge of accurately identifying the source of the second traveling wave head in complex transmission network scenarios with existing single-ended fault location methods, a traveling wave network fault location method based on adaptive waveform similarity is proposed. The paper analyzes the propagation process of traveling waves in transmission lines and quantitatively derives the time-domain expression of the traveling wave waveform. The BFS algorithm is enhanced by incorporating the propagation characteristics of traveling waves, allowing for the determination of all paths from any location in the topological network to the measurement points. Based on the path information and the derived expression, the traveling wave waveform at the measurement points for the fault location is calculated. An optimization algorithm is used to iteratively solve for unknown parameters such as fault location, traveling wave speed, and fault point information, with the objective of maximizing the similarity between the adaptive waveform and the real waveform by adaptively adjusting the waveform shape. When the similarity between the adaptive waveform and the real waveform is maximized, the adaptive fault location is identified as the actual fault location. Verified through the PSCAD simulation platform, this method can achieve accurate location under different fault conditions.

DENOISING: Dynamic enhancement and noise overcoming in multimodal neural observations via high-density CMOS-based biosensors.

Large-scale multimodal neural recordings on high-density biosensing microelectrode arrays (HD-MEAs) offer unprecedented insights into the dynamic interactions and connectivity across various brain networks. However, the fidelity of these recordings is frequently compromised by pervasive noise, which obscures meaningful neural information and complicates data analysis. To address this challenge, we introduce DENOISING, a versatile data-derived computational engine engineered to adjust thresholds adaptively based on large-scale extracellular signal characteristics and noise levels. This facilitates the separation of signal and noise components without reliance on specific data transformations. Uniquely capable of handling a diverse array of noise types (electrical, mechanical, and environmental) and multidimensional neural signals, including stationary and non-stationary oscillatory local field potential (LFP) and spiking activity, DENOISING presents an adaptable solution applicable across different recording modalities and brain networks. Applying DENOISING to large-scale neural recordings from mice hippocampal and olfactory bulb networks yielded enhanced signal-to-noise ratio (SNR) of LFP and spike firing patterns compared to those computed from raw data. Comparative analysis with existing state-of-the-art denoising methods, employing SNR and root mean square noise (RMS), underscores DENOISING's performance in improving data quality and reliability. Through experimental and computational approaches, we validate that DENOISING improves signal clarity and data interpretation by effectively mitigating independent noise in spatiotemporally structured multimodal datasets, thus unlocking new dimensions in understanding neural connectivity and functional dynamics.

Frequency-Domain Features and Low-Frequency Synchronization of Photoplethysmographic Waveform Variability and Heart Rate Variability with Increasing Severity of Cardiovascular Diseases.

Objective-Heart rate variability (HRV) and photoplethysmographic waveform variability (PPGV) are available approaches for assessing the state of cardiovascular autonomic regulation. The goal of our study was to compare the frequency-domain features and low-frequency (LF) synchronization of the PPGV and HRV with increasing severity of cardiovascular diseases. Methods-Our study included 998 electrocardiogram (ECG) and finger photoplethysmogram (PPG) recordings from subjects, classified into five categories: 53 recordings from healthy subjects, aged 28.1 ± 6.2 years, 536 recordings from patients with hypertension (HTN), 49.0 ± 8.8 years old, 185 recordings from individuals with stable coronary artery disease (CAD) (63.9 ± 9.3 years old), 104 recordings from patients with myocardial infarction (MI) that occurred three months prior to the recordings (PMI) (65.1 ± 11.0 years old), and 120 recordings from study subjects with acute myocardial infarction (AMI) (64.7 ± 11.5 years old). Spectral analyses of the HRV and PPGV were carried out, along with an assessment of the synchronization strength between LF oscillations of the HRV and of PPGV (synchronization index). Results-Changes in all frequency-domain indices and the synchronization index were observed along the following gradient: healthy subjects → patients with HTN → patients with CAD → patients with PMI → patients with AMI. Similar frequency-domain indices of the PPGV and HRV show little relationship with each other. Conclusions-The frequency-domain indices of the PPGV are highly sensitive to the development of any cardiovascular disease and, therefore, are superior to the HRV indices in this regard. The S index is an independent parameter from the frequency-domain indices.

Effect of Current Waveform on Microstructure Evolution and Mechanical Properties of GH4169 High-Temperature Alloy Tungsten Inert Gas Additive Manufacturing.

Direct current (DC) and pulsed DC tungsten inert gas (TIG) additive manufacturing processes were employed to fabricate GH4169 high-temperature alloy specimens. Upon comparing and analysing the two additive manufacturing methods, the evolution of microstructure and mechanical properties of the additively manufactured specimens were discussed. It provided a useful reference for the engineering application of pulsed DC TIG technology. The results showed that the overall forming process of the specimen was relatively stable under the DC TIG additive manufacturing and pulsed DC TIG additive manufacturing processes. The aspect ratio of the deposited layer of the pulsed DC-deposited specimen was relatively low, and the deposited layer of the pulsed DC specimen became flatter, which was conducive to maintaining the stability of the molten pool during the deposition process and improving forming accuracy. The microstructure distribution of the deposited layer from bottom to top was relatively uneven, with columnar dendrites in the bottom layer, cellular crystals in the middle layer, and equiaxed crystals in the top layer. Compared with the DC TIG additive manufacturing of GH4169 high-temperature alloy specimens, the Laves phase of the pulsed DC specimens was significantly reduced, which improved the plasticity and brittleness of the material.

A Novel Waveform Optimization Method for Orthogonal-Frequency Multiple-Input Multiple-Output Radar Based on Dual-Channel Neural Networks.

The orthogonal frequency-division multiplexing (OFDM) mode with a linear frequency modulation (LFM) signal as the baseband waveform has been widely studied and applied in multiple-input multiple-output (MIMO) radar systems. However, its high sidelobe levels after pulse compression affect the target detection of radar systems. For this paper, theoretical analysis was performed, to investigate the causes of high sidelobe levels in OFDM-LFM waveforms, and a novel waveform optimization design method based on deep neural networks is proposed. This method utilizes the classic ResNeXt network to construct dual-channel neural networks, and a new loss function is employed to design the phase and bandwidth of the OFDM-LFM waveforms. Meanwhile, the optimization factor is exploited, to address the optimization problem of the peak sidelobe levels (PSLs) and integral sidelobe levels (ISLs). Our numerical results verified the correctness of the theoretical analysis and the effectiveness of the proposed method. The designed OFDM-LFM waveforms exhibited outstanding performance in pulse compression and improved the detection performance of the radar.

Variability of morphology in photoplethysmographic waveform quantified with unsupervised wave-shape manifold learning for clinical assessment.

Objective.We investigated fluctuations of the photoplethysmography (PPG) waveform in patients undergoing surgery. There is an association between the morphologic variation extracted from arterial blood pressure (ABP) signals and short-term surgical outcomes. The underlying physiology could be the numerous regulatory mechanisms on the cardiovascular system. We hypothesized that similar information might exist in PPG waveform. However, due to the principles of light absorption, the noninvasive PPG signals are more susceptible to artifacts and necessitate meticulous signal processing.Approach.Employing the unsupervised manifold learning algorithm, dynamic diffusion map, we quantified multivariate waveform morphological variations from the PPG continuous waveform signal. Additionally, we developed several data analysis techniques to mitigate PPG signal artifacts to enhance performance and subsequently validated them using real-life clinical database.Main results.Our findings show similar associations between PPG waveform during surgery and short-term surgical outcomes, consistent with the observations from ABP waveform analysis.Significance.The variation of morphology information in the PPG waveform signal in major surgery provides clinical meanings, which may offer new opportunity of PPG waveform in a wider range of biomedical applications, due to its non-invasive nature.

Unimodular Multi-Input Multi-Output Waveform and Mismatch Filter Design for Saturated Forward Jamming Suppression.

Forward jammers replicate and retransmit radar signals back to generate coherent jamming signals and false targets, making anti-jamming an urgent issue in electronic warfare. Jamming transmitters work at saturation to maximize the retransmission power such that only the phase information of the angular waveform at the designated direction of arrival (DOA) is retained. Therefore, amplitude modulation of MIMO radar angular waveforms offers an advantage in combating forward jamming. We address both the design of unimodular MIMO waveforms and their associated mismatch filters to confront mainlobe jamming in this paper. Firstly, we design the MIMO waveforms to maximize the discrepancy between the retransmitted jamming and the spatially synthesized radar signal. We formulate the problem as unconstrained non-linear optimization and solve it using the conjugate gradient method. Particularly, we introduce fast Fourier transform (FFT) to accelerate the numeric calculation of both the objection function and its gradient. Secondly, we design a mismatch filter to further suppress the filtered jamming through convex optimization in polynomial time. The simulation results show that for an eight-element MIMO radar, we are able to reduce the correlation between the angular waveform and saturated forward jamming to -6.8 dB. Exploiting this difference, the mismatch filter can suppress the jamming peak by 19 dB at the cost of an SNR loss of less than 2 dB.

The Determination of On-Water Rowing Stroke Kinematics Using an Undecimated Wavelet Transform of a Rowing Hull-Mounted Accelerometer Signal.

Boat acceleration profiles can provide valuable information for coaches and practitioners to make meaningful technical interventions and monitor the determinants of success in rowing. Previous studies have used simple feature detection methods to identify key phases within individual strokes, such as drive onset, drive time, drive offset and stroke time. However, based on skill level, technique or boat class, the hull acceleration profile can differ, making robust feature detection more challenging. The current study's purpose is to employ the undecimated wavelet transform (UWT) technique to detect individual features in the stroke acceleration profile from a single rowing hull-mounted accelerometer. In this investigation, the temporal and kinematic values obtained using the AdMosTM sensor in conjunction with the UWT processing approach were strongly correlated with the comparative measures of the Peach™ instrumented oarlock system. The measures for stroke time displayed very strong agreeability between the systems for all boat classes, with ICC values of 0.993, 0.963 and 0.954 for the W8+, W4- and W1x boats, respectively. Similarly, the drive time was also very consistent, with strong to very strong agreeability, producing ICC values of 0.937, 0.901 and 0.881 for the W8+, W4- and W1x boat classes. Further, a Bland-Altman analysis displayed little to no bias between the AdMosTM-derived and Peach™ measures, indicating that there were no systematic discrepancies between signals. This single-sensor solution could form the basis for a simple, cost-effective and accessible alternative to multi-sensor instrumented systems for the determination of sub-stroke kinematic phases.

Reliability of Digital Artery Palpation and Pulse Oximetry Waveform As Alternatives to Radial Pulse in the Assessment of Upper Limb Injuries.

INTRODUCTION: Radial pulse palpation is widely accepted as a gold standard clinical method to assess distal vascular perfusion of the upper limb. In some instances, the radial pulse may not be accessible due to splints, casts, or swelling, or the injury may be at the level or distal to the radial artery. Here, the authors assess two alternative methods of assessing perfusion of the hand more distally: palpation of the digital pulse and pulse oximetry (PO) waveform. METHODS: Twenty-four healthy adult volunteers (48 hands) were assessed by two assessors. Digital artery pulses were palpated, and ease of location was recorded. A brachial cuff pressure was inflated to 20 mmHg above systolic pressure to occlude distal perfusion. Radial pulse, digital artery pulse, and PO waveform were monitored as the brachial cuff pressure was deflated in 5 mmHg increments to ascertain when each returned and compare the reliability of these tests to the gold standard of the radial pulse. RESULTS: The digital artery pulse was easily located in 20/24 participants, most reliably over the proximal phalanx of the index finger. With occlusion of the brachial artery, no distal pulses could be felt, and PO showed no waveform. As the brachial artery cuff pressure was incrementally deflated, the digital pulse returned with the same cuff pressure or a lower cuff pressure than the radial pulse in all cases, suggesting a high positive predictive value of radial pulse presence. PO waveform returned at a higher cuff pressure or with the same cuff pressure as the return of the radial pulse, suggesting a higher sensitivity than radial pulse palpation in assessing hand perfusion. CONCLUSION: Digital pulse palpation can be used as a surrogate method of assessing hand perfusion. When present, it can be assumed a radial pulse is present due to a high positive predictive value and no false positives seen in any participant. When absent, further investigation is required. The PO waveform was found to be more sensitive than digital or radial pulse palpation as a measure of distal perfusion, with a return of waveform prior to palpable pulses. This likely represents a more accurate clinical test of distal perfusion and can be relied upon even when pulses are not palpable.

Adverse Cardiovascular Effects of Nicotine Delivered by Chronic Electronic Cigarettes or Standard Cigarettes Captured by Cardiovascular Intrinsic Frequencies.

BACKGROUND: Electronic cigarettes have gained popularity as a nicotine delivery system, which has been recommended by some as an aid to help people quit traditional smoking. The potential long-term effects of vaping on the cardiovascular system, as well as how their effects compare with those from standard cigarettes, are not well understood. The intrinsic frequency (IF) method is a systems approach for analysis of left ventricle and arterial function. Recent clinical studies have demonstrated the diagnostic and prognostic value of IF. Here, we aim to determine whether the novel IF metrics derived from carotid pressure waveforms can detect effects of nicotine (delivered by chronic exposure to electronic cigarette vapor or traditional cigarette smoke) on the cardiovascular system. METHODS AND RESULTS: One hundred seventeen healthy adult male and female rats were exposed to purified air (control), electronic cigarette vapor without nicotine, electronic cigarette vapor with nicotine, and traditional nicotine-rich cigarette smoke, after which hemodynamics were comprehensively evaluated. IF metrics were computed from invasive carotid pressure waveforms. Standard cigarettes significantly increased the first IF (indicating left ventricle contractile dysfunction). Electronic cigarettes with nicotine significantly reduced the second IF (indicating adverse effects on vascular function). No significant difference was seen in the IF metrics between controls and electronic cigarettes without nicotine. Exposure to electronic cigarettes with nicotine significantly increased the total IF variation (suggesting adverse effects on left ventricle-arterial coupling and its optimal state), when compared with electronic cigarettes without nicotine. CONCLUSIONS: Our IF results suggest that nicotine-containing electronic cigarettes adversely affect vascular function and left ventricle-arterial coupling, whereas standard cigarettes have an adverse effect on left ventricle function.

Why do thoracic epidurals fail? A literature review on thoracic epidural failure and catheter confirmation.

Thoracic epidural anesthesia (TEA) has been the gold standard of perioperative analgesia in various abdominal and thoracic surgeries. However, misplaced or displaced catheters, along with other factors such as technical challenges, equipment failure, and anatomic variation, lead to a high incidence of unsatisfactory analgesia. This article aims to assess the different sources of TEA failure and strategies to validate the location of thoracic epidural catheters. A literature search of PubMed, Medline, Science Direct, and Google Scholar was done. The search results were limited to randomized controlled trials. Literature suggests techniques such as electrophysiological stimulation, epidural waveform monitoring, and x-ray epidurography for identifying thoracic epidural placement, but there is no one particular superior confirmation method; clinicians are advised to select techniques that are practical and suitable for their patients and practice environment to maximize success.

Age-related differences in how the shape of alpha and beta oscillations change during reaction time tasks.

While the shape of cortical oscillations is increasingly recognised to be physiologically and functionally informative, its relevance to the aging motor system has not been established. We therefore examined the shape of alpha and beta band oscillations recorded at rest, as well as during performance of simple and go/no-go reaction time tasks, in 33 young (23.3 ± 2.9 years, 27 females) and 27 older (60.0 ± 5.2 years, 23 females) adults. The shape of individual oscillatory cycles was characterised using a recently developed pipeline involving empirical mode decomposition, before being decomposed into waveform motifs using principal component analysis. This revealed four principal components that were uniquely influenced by task and/or age. These described specific dimensions of shape and tended to be modulated during the reaction phase of each task. Our results suggest that although oscillation shape is task-dependent, the nature of this effect is altered by advancing age, possibly reflecting alterations in cortical activity. These outcomes demonstrate the utility of this approach for understanding the neurophysiological effects of ageing.

Ciliary Motility Decreased by a CO2/HCO3--Free Solution in Ciliated Human Nasal Epithelial Cells Having a pH Elevated by Carbonic Anhydrase IV.

An application of CO2/HCO3--free solution (Zero-CO2) did not increase intracellular pH (pHi) in ciliated human nasal epithelial cells (c-hNECs), leading to no increase in frequency (CBF) or amplitude (CBA) of the ciliary beating. This study demonstrated that the pHi of c-hNECs expressing carbonic anhydrase IV (CAIV) is high (7.64), while the pHi of ciliated human bronchial epithelial cells (c-hBECs) expressing no CAIV is low (7.10). An extremely high pHi of c-hNECs caused pHi, CBF and CBA to decrease upon Zero-CO2 application, while a low pHi of c-hBECs caused them to increase. An extremely high pHi was generated by a high rate of HCO3- influx via interactions between CAIV and Na+/HCO3- cotransport (NBC) in c-hNECs. An NBC inhibitor (S0859) decreased pHi, CBF and CBA and increased CBF and CBA in c-hNECs upon Zero-CO2 application. In conclusion, the interactions of CAIV and NBC maximize HCO3- influx to increase pHi in c-hNECs. This novel mechanism causes pHi to decrease, leading to no increase in CBF and CBA in c-hNECs upon Zero-CO2 application, and appears to play a crucial role in maintaining pHi, CBF and CBA in c-hNECs periodically exposed to air (0.04% CO2) with respiration.

Critical care nurses' knowledge and attitudes towards using ventilator waveform monitoring to detect patient-ventilator asynchrony: A cross-sectional online survey.

BACKGROUND: Patient-ventilator asynchrony (PVA) is a condition that commonly affects patients who are mechanically ventilated. PVA happens when the patient's own breathing effort and the ventilator preset settings are out of sync. Ventilator waveform monitoring is viewed as a difficult undertaking, even for experienced practitioners, despite being a non-invasive and reliable tool for diagnosing PVA. AIM: To assess the knowledge levels and attitudes of critical care nurses (CCNs) regarding the use of ventilator waveform monitoring to detect PVA. STUDY DESIGN: A cross-sectional online survey was conducted in three intensive care units (ICUs) in Alexandria, Egypt. The questionnaire consisted of four parts to evaluate CCNs' level of knowledge and attitude regarding ventilator waveform monitoring and assess their ability to detect PVA. RESULTS: Of the 137 CCNs approached, 101 CCNs completed the survey, resulting in a 73.7% response rate. Most nurses (88.1%) demonstrated poor knowledge levels and negative attitudes (93.1%) towards using waveform monitoring to detect PVA. A significant relationship was found between nurses' knowledge of ventilator waveform monitoring and their participation in previous training programmes on mechanical ventilation (MV; p = .031). Additionally, nurses' attitudes towards ventilator waveform monitoring were significantly associated with their level of education (p = .002) and attendance in previous courses on waveform analysis (p = .020). CONCLUSIONS: A majority of CCNs have poor knowledge and negative attitudes regarding ventilator waveform monitoring. Previous training in MV and attendance courses on ventilator waveform analysis showed a significant correlation between nurses' level of knowledge and attitudes regarding ventilator waveform monitoring. RELEVANCE TO CLINICAL PRACTICE: Assessment of CCNs' knowledge and attitudes regarding ventilator waveform monitoring for detecting patient-ventilator asynchrony (PVA) informs the development of future educational programmes, ultimately aiding in the delivery of prompt and high-quality care.

An Intrinsically Explainable Method to Decode P300 Waveforms from EEG Signal Plots Based on Convolutional Neural Networks.

This work proposes an intrinsically explainable, straightforward method to decode P300 waveforms from electroencephalography (EEG) signals, overcoming the black box nature of deep learning techniques. The proposed method allows convolutional neural networks to decode information from images, an area where they have achieved astonishing performance. By plotting the EEG signal as an image, it can be both visually interpreted by physicians and technicians and detected by the network, offering a straightforward way of explaining the decision. The identification of this pattern is used to implement a P300-based speller device, which can serve as an alternative communication channel for persons affected by amyotrophic lateral sclerosis (ALS). This method is validated by identifying this signal by performing a brain-computer interface simulation on a public dataset from ALS patients. Letter identification rates from the speller on the dataset show that this method can identify the P300 signature on the set of 8 patients. The proposed approach achieves similar performance to other state-of-the-art proposals while providing clinically relevant explainability (XAI).

Design and implementation of a cost-effective, open-source, and programmable pulsatile flow system.

The primary objective of this research was to design, implement, and validate a programmable open-source pulsatile flow system to cost-effectively simulate vascular flows. We employed an Arduino-compatible microcontroller combined with a motor driver to control a centrifugal direct current (DC) motor pump. The system was programmed to produce pulsatile flows with an arterial pulse waveform. Validation with Doppler ultrasound and flow measurements confirmed that our Arduino-based system successfully replicated arterial vascular flow. The materials are easily accessible, with a total bill of materials as low as $99. This open-source programmable pulsatile pump platform offers superior cost-effectiveness and adaptability relative to commercial offerings.

Validation of inertial measurement units based on waveform similarity assessment against a photogrammetry system for gait kinematic analysis.

When assessing gait analysis outcomes for clinical use, it is indispensable to use an accurate system ensuring a minimal measurement error. Inertial Measurement Units (IMUs) are a versatile motion capture system to evaluate gait kinematics during out-of-lab activities and technology-assisted rehabilitation therapies. However, IMUs are susceptible to distortions, offset and drifting. Therefore, it is important to have a validated instrumentation and recording protocol to ensure the reliability of the measurements, to differentiate therapy effects from system-induced errors. A protocol was carried out to validate the accuracy of gait kinematic assessment with IMUs based on the similarity of the waveform of concurrent signals captured by this system and by a photogrammetry reference system. A gait database of 32 healthy subjects was registered synchronously with both devices. The validation process involved two steps: 1) a preliminary similarity assessment using the Pearson correlation coefficient, and 2) a similarity assessment in terms of correlation, displacement and gain by estimating the offset between signals, the difference between the registered range of motion (∆ROM), the root mean square error (RMSE) and the interprotocol coefficient of multiple correlation (CMCP). Besides, the CMCP was recomputed after removing the offset between signals (CMCPoff). The correlation was strong (r > 0.75) for both limbs for hip flexion/extension, hip adduction/abduction, knee flexion/extension and ankle dorsal/plantar flexion. These joint movements were studied in the second part of the analysis. The ∆ROM values obtained were smaller than 6°, being negligible relative to the minimally clinically important difference (MCID) estimated for unaffected limbs, and the RMSE values were under 10°. The offset for hips and ankles in the sagittal plane reached -9° and -8°, respectively, whereas hips adduction/abduction and knees flexion/extension were around 1°. According to the CMCP, the kinematic pattern of hip flexion/extension (CMCP > 0.90) and adduction/abduction (CMCP > 0.75), knee flexion/extension (CMCP > 0.95) and ankle dorsi/plantar flexion (CMCP > 0.90) were equivalent when captured by each system synchronously. However, after offset correction, only hip flexion/extension (CMCPoff = 1), hip adduction/abduction (CMCPoff > 0.85) and knee flexion/extension (CMCPoff > 0.95) satisfied the conditions to be considered similar.

Mass-selective instability and resonance ejection modes for DIT with rectangular asymmetric wave shape.

We consider the operation of a digital linear ion trap with resonance radial ejection and mass selective instability modes. Periodic wave shape has a positive part with amplitude V+=V0 and duration 0.8T and negative part with amplitude V-=-4V0 and duration 0.2T, where T is the period. The mapping of the stability diagram, calculations of the well's depth and ion oscillations spectra are presented. The process of resonant excitation of ion oscillations by a dipole sinusoidal signal is studied, as well as ion ejection at the stability boundary. The trajectory method is used for this purpose. It is shown that the mass selectivity of dipole excitation is twice as large for rectangular wave shape compared to sinusoidal wave shape. Increasing the diameter of the round rods of the linear trap gives an increase in the resolving power. The possibility of DIT operation in mass-selective instability mode at the boundary point qb=0.39 is discussed.