The Effect of Jittered Stimulus Onset Interval on Electrophysiological Markers of Attention in a Brain-Computer Interface Rapid Serial Visual Presentation Paradigm.

Brain responses to discrete stimuli are modulated when multiple stimuli are presented in sequence. These alterations are especially pronounced when the time course of an evoked response overlaps with responses to subsequent stimuli, such as in a rapid serial visual presentation (RSVP) paradigm used to control a brain-computer interface (BCI). The present study explored whether the measurement or classification of select brain responses during RSVP would improve through application of an established technique for dealing with overlapping stimulus presentations, known as irregular or "jittered" stimulus onset interval (SOI). EEG data were collected from 24 healthy adult participants across multiple rounds of RSVP calibration and copy phrase tasks with varying degrees of SOI jitter. Analyses measured three separate brain signals sensitive to attention: N200, P300, and occipitoparietal alpha attenuation. Presentation jitter visibly reduced intrusion of the SSVEP, but in general, it did not positively or negatively affect attention effects, classification, or system performance. Though it remains unclear whether stimulus overlap is detrimental to BCI performance overall, the present study demonstrates that single-trial classification approaches may be resilient to rhythmic intrusions like SSVEP that appear in the averaged EEG.

Using jitter analysis with concentric needle electrodes to assess disease status and treatment responses in myasthenia gravis.

Objective: This study assesses the utility of jitter analysis with concentric needles to evaluate disease severity in myasthenia gravis (MG), correlate changes in jitter with clinical status as well as identify reasons for any discordance. Methods: We performed a retrospective chart review of 82 MG patients and extracted data on demographics, MG subtype, antibody status, clinical scales, electrophysiology, and interventions at baseline and follow-up. Results: Baseline MGII scores correlated with jitter (r = 0.25, p = 0.024) and abnormal pairs (r = 0.24, p = 0.03). After 28 months, MGII scores correlated with jitter (r = 0.31, p = 0.006), abnormal pairs (r = 0.29, p = 0.009), and pairs with blocks (r = 0.35, p = 0.001). Changes in MGII scores correlated with changes in jitter (r = 0.35, p = 0.002), abnormal pairs (r = 0.27, p = 0.014), and pairs with blocks (r = 0.36, p = 0.001). Conclusions: Concentric needle jitter analysis may have the potential to evaluate baseline and sequential disease severity in MG. Significance: This study highlights the potential for improved MG patient care through precise assessment and management using concentric needle jitter analysis to improve the accuracy of MG diagnosis and monitoring of disease activity.

Research on high-speed digital optical signal jitter measurement technology based on clock recovery algorithm using eye diagram opening area.

With the rapid development of information technology, high-speed digital optical signal transmission technology has become the core of modern communication networks. However, the increase in transmission rates brings challenges such as noise, distortion, and interference, which affect the accuracy of clock recovery. To address these issues, this study proposes a clock recovery algorithm based on the eye diagram opening area to improve the accuracy and efficiency of high-speed digital optical signal jitter measurement. The proposed method extracts clock information from the signal using the opening area and curvature characteristics of the eye diagram for jitter measurement. Experimental results demonstrate that the clock recovery algorithm based on the eye diagram opening area can stably reconstruct the signal eye diagram and obtain jitter parameters under different optical power conditions. At optical powers of -7.2 dBm, -12.2 dBm, and -17.2 dBm, the Q-factors were 8.8, 7.6, and 4.3, respectively, and the RMS jitter values were 12.2 ps, 13.4 ps, and 21.2 ps, respectively. At optical powers of -2.3 dBm, 0.1 dBm, 2.4 dBm, 4.6 dBm, and 6.0 dBm, the Q-factors were 9.1, 9.3, 9.5, 9.7, and 10.0, respectively, and the average jitter values were 8.9 ps, 8.5 ps, 8.0 ps, 7.5 ps, and 7.0 ps. These results indicate that the proposed algorithm performs excellently under low optical power conditions and maintains high recovery accuracy even when jitter increases at higher optical powers. The clock recovery algorithm based on the eye diagram opening area significantly improves the accuracy and stability of high-speed digital optical signal jitter measurement, enriches the theoretical research of clock recovery algorithms, and shows significant advantages in improving signal transmission quality, reducing bit error rate, and enhancing communication link reliability. The research outcomes provide key technical support for the optimization of modern high-speed optical communication systems.

Correcting for ERP latency jitter improves gaze-independent BCI decoding.

Objective.Patients suffering from heavy paralysis or Locked-in-Syndrome can regain communication using a Brain-Computer Interface (BCI). Visual event-related potential (ERP) based BCI paradigms exploit visuospatial attention (VSA) to targets laid out on a screen. However, performance drops if the user does not direct their eye gaze at the intended target, harming the utility of this class of BCIs for patients suffering from eye motor deficits. We aim to create an ERP decoder that is less dependent on eye gaze.Approach.ERP component latency jitter plays a role in covert visuospatial attention (VSA) decoding. We introduce a novel decoder which compensates for these latency effects, termed Woody Classifier-based Latency Estimation (WCBLE). We carried out a BCI experiment recording ERP data in overt and covert visuospatial attention (VSA), and introduce a novel special case of covert VSA termed split VSA, simulating the experience of patients with severely impaired eye motor control. We evaluate WCBLE on this dataset and the BNCI2014-009 dataset, within and across VSA conditions to study the dependency on eye gaze and the variation thereof during the experiment.Main results.WCBLE outperforms state-of-the-art methods in the VSA conditions of interest in gaze-independent decoding, without reducing overt VSA performance. Results from across-condition evaluation show that WCBLE is more robust to varying VSA conditions throughout a BCI operation session.Significance. Together, these results point towards a pathway to achieving gaze independence through suited ERP decoding. Our proposed gaze-independent solution enhances decoding performance in those cases where performing overt VSA is not possible.

Diagnostic accuracy of voluntary and stimulated neuromuscular jitter studies in ocular myasthenia gravis.

INTRODUCTION/AIMS: There is a lack of studies comparing the accuracy of neuromuscular jitter analysis during voluntary activation (v-jitter study) versus axonal stimulation (s-jitter study). The study aimed to compare these two techniques in the same population of patients with suspected ocular myasthenia gravis (OMG). METHODS: Fourteen control subjects (mean age: 55.5 ± 15.2 years) and 34 patients with suspected OMG (mean age: 59 ± 13.9 years) were prospectively evaluated. Twenty spike pairs and 30 individual spikes were analyzed during v-jitter and s-jitter study, respectively. Two different criteria for abnormal individual jitter values were evaluated: ≥ or > than 10% values exceeding the upper normal limit. RESULTS: OMG was diagnosed in 19 patients based on clinical and laboratory findings, without considering jitter measurements. In most patients, v-jitter and s-jitter analyses provided comparable results. The maximum sensitivity (89%) was achieved with s-jitter study using the ≥10% criterion, while the maximum specificity (93%) was found with v-jitter study using the >10% criterion. DISCUSSION: Both v-jitter and s-jitter studies showed good to very good accuracy for the diagnosis of OMG, in the absence of any statistically significant difference. Therefore, the patient's cooperation level and examiner's experience should guide the choice of performing v-jitter or s-jitter analysis in patients with suspected OMG.

Correlation of single-fiber electromyography studies and functional status in patients with amyotrophic lateral sclerosis.

Objective: Our aim was to examine the significance of single-fiber electromyography (SFEMG) in patients diagnosed with amyotrophic lateral sclerosis (ALS) and determine the best correlating parameter with SFEMG parameters and clinical scales across different muscles including facial muscles. Methods: SFEMG examinations were conducted on the extensor digitorum (ED), frontalis, and orbicularis oculi muscles. Mean jitter, percentage of increased jitter, fiber density (FD), and impulse blocking percentage were compared to reference values and functional scales. Results: Significant differences (p < 0.001) were observed between the patients' SFEMG results and reference values in all muscles. Significant correlations were found between SFEMG parameters and clinical scales, particularly when considering both FD and jitter. A notable value of the ALS Functional Rating Scale Revised (ALSFRS-R) was detected in all muscles: 31 points in the ED muscle, 30 in the orbicularis oculi muscle, and 31 in the frontalis muscle. Below this ALSFRS-R threshold, the percentage of increased jitter was higher, while FD remained relatively low. Conclusion: SFEMG examination emerges as a valuable tool for better understanding ALS and holds potential for assessing prognosis. Combined jitter and FD analysis showed the strongest correlation with clinical scales. In addition to the ED muscle, the orbicularis oculi muscle may be important in the assessment.

Study of the Bias of the Initial Phase Estimation of a Sinewave of Known Frequency in the Presence of Phase Noise.

The estimation of the parameters of a sinusoidal signal is of paramount importance in various applications in the fields of sensors, signal processing, parameter estimation, and device characterization, among others. The presence, in the measurement system, of non-ideal phenomena such as additive noise in the signals, phase noise in the stimulus generation, jitter in the sampling system, frequency error in the experimental setup, among others, leads to increased uncertainty and bias in the estimated quantities obtained by least squares methods and those derived from them. Therefore, from a metrological point of view, it is important to be able to theoretically predict and quantify those uncertainties in order to properly design the measurement system and its parameters, such as the number of samples to acquire or the stimulus signal amplitude to use to minimize the uncertainty in the estimated values. Previous works have shown that the presence of these non-ideal phenomena leads to increased uncertainty and bias in the estimation of the sinewave amplitude. The present work complements this knowledge by focusing specifically on the effect of phase noise and sampling jitter in the bias of the initial phase estimation of a sinusoidal signal of known frequency (three­parameter sine fitting procedure). A theoretical derivation of the bias of initial phase estimation that takes into consideration the presence of phase noise in the sinewave is presented. Since a Taylor series approximation was used where only the first term was retained, it was necessary to validate the analytical derivations with numerical simulations using a Monte Carlo type of procedure. This process was applied to different conditions regarding the phase noise standard deviation, initial phase value, and number of samples. It is concluded that, in most scenarios, initial phase estimation using sine fitting is unbiased in the presence of phase noise or jitter. It is shown, however, that in cases of extremely high phase noise standard deviation and a very low number of samples, a bias occurs.

A Comparison of the Dysphonia Severity Index and Singing Voice Handicap Index Between Trained and Untrained Male Iranian Traditional Singers.

OBJECTIVES: This study aimed to compare trained and untrained Iranian traditional singers on the Dysphonia Severity Index (DSI) and the Singing Voice Handicap Index. The second objective was to examine the relationship between the DSI and Persian version of the Singing Voice Handicap Index (P-SVHI) scores in each group of trained and untrained Iranian traditional singers. STUDY DESIGN: This study is a comparative cross-sectional study. METHODS: This study included 17 trained male Iranian traditional singers who were compared with 17 untrained ones who were matched in terms of age. The P-SVHI was completed by trained and untrained Iranian traditional singers. Measures of jitter, lowest intensity, highest phonational frequency, and maximum phonation time (MPT) were obtained from each participant. The DSI scores were calculated using these values. RESULTS: Trained male traditional singers had an average age of 33.76 ± 7.45 years, 3.24 ± 1.85 hours of daily practice, 5.24 ± 3.78 years of training, 3.06 ± 2.65 no. of professional performances, and untrained singers had an average age of 32.76 ± 12.92 years, 1.53 ± 1.17 hours of daily practice, and 0.88 ± 1.65 no. of professional performances. Trained singers had lower P-SVHI scores and sub-scores, longer MPT, higher F0 high, lower jitter, and lower I low, resulting in higher DSI values (P < 0.05). There was no significant correlation between P-SVHI scores and DSI values in each group of trained and untrained Iranian traditional singers (P > 0.05). CONCLUSIONS: The results of this study show that the vocal abilities of professional vocalists are enhanced through voice training (higher DSI scores in trained singers vs untrained ones). Voice training can also help to lessen the perception of a handicap related to the singing voice. Hence, it may be necessary to consider alternative norms for the DSI and P-SVHI when administering them to patients who have undergone guided vocal training, such as voice/singing lessons. The current research indicates that the perception of singing voice handicap and DSI values are two distinct characteristics that do not have a significant correlation.

Concentric needle jitter analysis of the genioglossus muscle in patients with motor neuron disease.

OBJECTIVES: Difficulty relaxing the genioglossus muscle makes the evaluation of spontaneous activity problematic in patients with motor neuron disease (MND). We performed jitter analysis using conventional disposable concentric needle electrodes (CNEs) of the voluntarily activated genioglossus muscle in patients with and without MND to detect the denervation-reinnervation process. METHODS: CNE jitter analysis was performed at the genioglossus muscle in 21 MND(+) patients and 22 MND(-) subjects. The jitter analysis was considered abnormal if the jitter values exceeded these limits for the mean consecutive difference (MCD) or the individual MCD in more than 10% of readings. RESULTS: Seventeen MND(+) patients (81%) had at least three abnormal individual jitter values whereas denervation findings were obtained in eleven of them during the needle electromyographic examination at genioglossus muscle. None of the MND(-) subjects showed CNE jitter abnormality. CONCLUSION: CNE jitter analysis of genioglossus muscle may provide an useful information that may be suggestive of a diagnosis of MND/ALS.

Voice aspects in children with precocious puberty.

PURPOSE: In this prospective study, we aimed to investigate the difference in voice acoustic parameters between girls with idiopathic central precocious puberty (ICPP) and those who developed normally during prepuberty. MATERIALS AND METHODS: Our study recruited 54 girls diagnosed with ICPP and randomly sampled 51 healthy prepubertal girls as the control. Tanner stages, circulating hormone levels and bone ages of the girls with ICPP and the age and body mass index (BMI) of all participants were recorded. Acoustic analyses were performed using PRAAT computer-based voice analysis software and the mean pitch (F0), jitter, shimmer, noise-to harmonic-ratio (NHR) and harmonic-to-noise ratio (HNR) values were compared in the patient and control groups. RESULTS: The two groups did not significantly differ in age or BMI. In the evaluation of the F0 and jitter values, we were found to be lower in the control group than in the patient group. However, we did not find a statistical significance. The mean shimmer values of the patient group were significantly higher than those of the control group. In addition, a statistically significant difference was noted for the mean HNR and NHR values (P < 0.001). A moderate negative correlation was found between shimmer and hormone levels in the patient group. CONCLUSIONS: Voice acoustic parameters one of the defining features of girls with ICPP. Voice changes in acoustic parameters could reflect hormonal changes during puberty. Clinicians should suspect ICPP when there is a change in the voice.

Jitter solution in parameter identification based on cross-time scale fusion algorithm of lithium-ion batteries.

Accurate state-of-charge (SOC) estimation is the core index of battery management system (BMS). When the battery equivalent circuit model (ECM) identifies the parameters under complex operating conditions, there is more jitter or even divergence, which will affect the estimation accuracy of battery SOC. To solve this problem, this paper proposes a new algorithm, namely the cross time scale fusion (CTSF) algorithm. Firstly, the cross-time scales Δt1 and Δt2 are determined, the number of cross-time cycles is calculated according to the total amount of complex operating condition data N. Then the ECM parameters are identified in Δt1 by using forgetting factor recursive least square (FFRLS), and the battery SOC is estimated in Δt2 based on the identified parameters, finally the battery parameters are identified and the SOC is estimated by cycling in the cross-time. The experimental results show that, no matter at the same temperature in different conditions or at different temperatures in the same condition, The proposed algorithm not only effectively solves the ECM parameter identification jitter problem, but also improves the accuracy of SOC estimation, the Mean Absolute Error (MAE) minimum of SOC result is 1.42% for different operating conditions at the same temperature and 0.25% for different temperatures at the same operating conditions, respectively.

Bias dependence in statistical random telegraph noise analysis based on nanoscale CMOS ring oscillators.

Random Telegraph Noise (RTN) is one of the major reliability concerns in nanoscale complementary metal-oxide semiconductor (CMOS) technologies. In this paper, we discuss the characterization of RTN in 40 nm CMOS technology using Ring Oscillators (ROSCs). We used different types of ROSCs to study the temporal and spectral characteristics of the RTN. We conducted measurements on one of the arrays with 128 identical ROSC cells. These results enabled statistical characterization of the RTN amplitude strength and its frequency characteristics in different supply voltage variations from 0.5 V to 0.7 V. At power supply of 0.65 V, dominant and observable RTN amplitude above 0.37% Δf/fmean is found in 60% of cells in the array. Further, the capture and emission time constant τe//c can be extracted from the measurements, the values observed ranging from 0.2 µs to 10 ms.

Automatic Tracking Based on Weighted Fusion Back Propagation in UWB for IoT Devices.

The global population is progressively entering an aging phase, with population aging likely to emerge as one of the most-significant social trends of the 21st Century, impacting nearly all societal domains. Addressing the challenge of assisting vulnerable groups such as the elderly and disabled in carrying or transporting objects has become a critical issue in this field. We developed a mobile Internet of Things (IoT) device leveraging Ultra-Wideband (UWB) technology in this context. This research directly benefits vulnerable groups, including the elderly, disabled individuals, pregnant women, and children. Additionally, it provides valuable references for decision-makers, engineers, and researchers to address real-world challenges. The focus of this research is on implementing UWB technology for precise mobile IoT device localization and following, while integrating an autonomous following system, a robotic arm system, an ultrasonic obstacle-avoidance system, and an automatic leveling control system into a comprehensive experimental platform. To counteract the potential UWB signal fluctuations and high noise interference in complex environments, we propose a hybrid filtering-weighted fusion back propagation (HFWF-BP) neural network localization algorithm. This algorithm combines the characteristics of Gaussian, median, and mean filtering, utilizing a weighted fusion back propagation (WF-BP) neural network, and, ultimately, employs the Chan algorithm to achieve optimal estimation values. Through deployment and experimentation on the device, the proposed algorithm's data preprocessing effectively eliminates errors under multi-factor interference, significantly enhancing the precision and anti-interference capabilities of the localization and following processes.

A Segmented Cross-Correlation Algorithm for Dynamic North Finding Using Fiber Optic Gyroscopes.

Fiber optic gyroscope (FOG)-based north finding is extensively applied in navigation, positioning, and various fields. In dynamic north finding, an accelerated turntable speed shortens the time required for north finding, resulting in a rapid north-finding response. However, with an increase in turntable speed, the turntable's jitter contributes to signal contamination in the FOG, leading to a deterioration in north-finding accuracy. This paper introduces a divide-and-conquer algorithm, the segmented cross-correlation algorithm, designed to mitigate the impact of turntable speed jitter. A model for north-finding error is established and analyzed, incorporating FOG's self-noise and the turntable's speed jitter. To validate the feasibility of our method, we implemented the algorithm on a FOG. The simulation and experimental results exhibited a strong concordance, affirming the validity of our proposed north-finding error model. The experimental findings indicate that, at a turntable speed of 180°/s, the north-finding bias error within a 360 s duration is 0.052°, representing a 64% improvement over the traditional algorithm. These results indicate the effectiveness of the proposed algorithm in mitigating the impact of unstable turntable speeds, offering a solution for north finding with both prompt response and enhanced accuracy.

Efficacy of platelet-rich plasma (PRP) in benign vocal fold lesions: a systematic review and meta-analysis.

OBJECTIVES: To evaluate the efficacy of platelet-rich plasma (PRP) in benign vocal fold lesions. METHODS: MEDLINE, Cochrane Central, Web of Science, and Scopus databases were searched in April 2023 for relevant clinical trials. Inclusion criteria were clinical trials evaluating the efficacy of PRP in benign vocal fold lesions. We conducted a comparative double-arm analysis using the pooled mean difference (MD) and 95% confidence interval (CI). Outcomes of interest included the vocal handicap index (VHI), the Jitter and Shimmer percentages, and the noise-to-harmonic ratio (NHR). RESULTS: Six studies matched the inclusion criteria. The pooled analysis shows that PRP was associated with significantly lower VHI scores compared with the control (MD = - 5.06, p < 0.01). Regarding the Jitter percentage, the PRP group was not superior to the control group at 2 and 4 weeks. However, the results revealed that PRP significantly reduced the Jitter percentage at 3 months (MD = - 0.61, p = 0.0008). The overall analysis favored the PRP arm significantly (p < 0.001). As for the Shimmer percentage, the combined effect estimate favored the PRP group (MD = - 1.22, p = 0.002). Subgroup analysis according to the time did not reveal any significant differences between studies at 2 weeks, 4 weeks, and 3 months. The analysis of the NHR outcome revealed a significant difference between both groups (MD = -1.09, p = 0.01). However, at 4 weeks, the treatment group had a significantly lower NHR % compared to the control group (MD = - 0.61, p = 0.02). There was no significant difference at 3 months (MD = - 2.14, p = 0.14). CONCLUSIONS: Platelet-rich plasma is effective in reducing VHI scores, Jitter and Shimmer percentages, and NHR values. This effect is more evident after follow-up, especially 3 months.

Two common issues in synchronized multimodal recordings with EEG: Jitter and latency.

Multimodal recording using electroencephalogram (EEG) and other biological signals (e.g., muscle activities, eye movement, pupil diameters, or body kinematics data) is ubiquitous in human neuroscience research. However, the precise time alignment of multiple data from heterogeneous sources (i.e., devices) is often arduous due to variable recording parameters of commercially available research devices and complex experimental setups. In this review, we introduced the versatility of a Lab Streaming Layer (LSL)-based application that can overcome two common issues in measuring multimodal data: jitter and latency. We discussed the issues of jitter and latency in multimodal recordings and the benefits of time-synchronization when recording with multiple devices. In addition, a computer simulation was performed to highlight how the millisecond-order jitter readily affects the signal-to-noise ratio of the electrophysiological outcome. Together, we argue that the LSL-based system can be used for research requiring precise time-alignment of datasets. Studies that detect stimulus-induced transient neural responses or test hypotheses regarding temporal relationships of different functional aspects with multimodal data would benefit most from LSL-based systems.

Investigation of Ongoing Denervation and Reinnervation in Amyotrophic Lateral Sclerosis by Using Concentric Needle Electrode with Single Fiber Electromyography Method.

Introduction: The aim of this study is to demonstrate the conduction disturbance at the neuromuscular junction in a cranial muscle by measuring jitter with a concentric needle (CN) electrode in the diagnosis of Amyotrophic Lateral Sclerosis (ALS) and to investigate the utility of evaluating the peak number as an ongoing reinnervation marker. Method: Twelve patients diagnosed with ALS were included in this study. Single fiber electromyography (SFEMG) was performed using a CN electrode during the voluntary contraction of the right extensor digitorum communis (EDC) and left frontalis muscles. Results: In SFEMG from the right EDC muscle, the mean jitter value was high in all of them. The average jitter calculated in EDC muscles was 57.76±24.17 µs. The mean jitter value in the frontal muscles was 28.91±10.21 µs. In all patients, the number of CN electrode peaks was more than 4 in the EDC muscle and above 4 in 91.67% of the frontal muscle. Conclusion: Detection of high jitter in SFEMG examination indicates that the examined muscle undergoes a denervation-reinnervation process in the case of increased peak number values. When such a determination is made in the extremity muscles, it becomes important for the diagnosis of ALS.

Electrophysiological evaluation of the neuromuscular junction: a brief review / Avaliação eletrofisiológica da junção neuromuscular: breve revisão

Abstract The nerve terminal and muscle membrane compose the neuromuscular junction. After opening the voltage-gated calcium channels, action potentials from the motor axons provoke a cascade for the acetylcholine release from synaptic vesicles to the synaptic cleft, where it binds to its receptor at the muscle membrane for depolarization. Low amplitude compound muscle action potential typically presents in presynaptic disorders, increasing by more than 100% after a 10-second effort in the Lambert-Eaton myasthenic syndrome and less in botulism. Needle electromyography may show myopathic motor unit action potentials and morphological instability ("jiggle") due to impulse blocking. Low-frequency repetitive nerve stimulation (RNS) is helpful in postsynaptic disorders, such as myasthenia gravis and most congenital myasthenic syndromes, where the number of functioning acetylcholine receptors is reduced. Low-frequency RNS with a decrement >10% is abnormal when comparing the 4th to the first compound muscle action potential amplitude. High-frequency RNS is helpful in presynaptic disorders like Lambert-Eaton myasthenic syndrome, botulism, and some rare congenital myasthenic syndromes. The high-frequency RNS releases more calcium, increasing the acetylcholine with a compound muscle action potential increment. Concentric needle records apparent single-fiber action potentials (spikes). A voluntary activation measures the jitter between spikes from two endplates. An electrical activation measures the jitter of one spike (one endplate). The jitter is the most sensitive test for detecting a neuromuscular junction dysfunction. Most neuromuscular junction disorders are responsive to treatment.

Resumo O nervo terminal e a membrana muscular compõem a junção neuromuscular. Após a abertura dos canais de cálcio dependentes de voltagem, os potenciais de ação do axônio motor provocam uma cascata de eventos que libera acetilcolina das vesículas para a fenda sináptica, ligando-se ao receptor na membrana muscular para despolarização. O potencial de ação muscular composto de baixa amplitude ocorre nas desordens pré-sinápticas, aumentando em mais de 100% após esforço de 10 segundos na síndrome miastênica de Lambert-Eaton e menos no botulismo. A eletromiografia pode mostrar potenciais de ação da unidade motora miopáticos e instabilidade morfológica ("jiggle") devido ao bloqueio do impulso. Estimulação nervosa repetitiva (ENR) de baixa frequência é útil nos distúrbios pós-sinápticos, como miastenia gravis e a maioria das síndromes miastênicas congênitas, quando há número reduzido de receptores de acetilcolina funcionantes. ENR de baixa frequência com decremento >10% é anormal comparando-se à amplitude do quarto com o primeiro potencial de ação muscular composto. ENR de alta frequência é útil nas doenças pré-sinápticas, como síndrome miastênica de Lambert-Eaton, botulismo e algumas síndromes miastênicas congênitas raras. ENR de alta frequência libera mais cálcio, aumenta acetilcolina, resultando em incremento do potencial de ação muscular composto. O eletrodo de agulha concêntrico registra potenciais de ação aparente de fibra única (PAAFU). Ativação voluntária mede jitter entre dois PAAFUs (duas junções neuromusculares). Ativação elétrica mede jitter de um PAAFU (uma junção neuromuscular). Jitter é o teste mais sensível para detectar disfunção de junção neuromuscular. A maioria dos distúrbios juncionais é responsiva ao tratamento.

Embracing off-the-grid samples.

Many empirical studies suggest that samples of continuous-time signals taken at locations randomly deviated from an equispaced grid (i.e., off-the-grid) can benefit signal acquisition, e.g., undersampling and anti-aliasing. However, explicit statements of such advantages and their respective conditions are scarce in the literature. This paper provides some insight on this topic when the sampling positions are known, with grid deviations generated i.i.d. from a variety distributions. By solving a square-root LASSO decoder with an interpolation kernel we demonstrate the capabilities of nonuniform samples for compressive sampling, an effective paradigm for undersampling and anti-aliasing. For functions in the Wiener algebra that admit a discrete s-sparse representation in some transform domain, we show that O(spolylogN) random off-the-grid samples are sufficient to recover an accurate N2-bandlimited approximation of the signal. For sparse signals (i.e., s≪N), this sampling complexity is a great reduction in comparison to equispaced sampling where O(N) measurements are needed for the same quality of reconstruction (Nyquist-Shannon sampling theorem). We further consider noise attenuation via oversampling (relative to a desired bandwidth), a standard technique with limited theoretical understanding when the sampling positions are non-equispaced. By solving a least squares problem, we show that O(NlogN) i.i.d. randomly deviated samples provide an accurate N2-bandlimited approximation of the signal with suppression of the noise energy by a factor ∼1log(N).

Quantitative electrodiagnosis of the motor unit.

Electromyography (EMG) focuses on assessment of the motor unit (MU), and a given muscle has several hundred MUs, each innervating hundreds of muscle fibers. Assessment is limited by the recording radius of electrodes, 1-2 fibers with single-fiber electrodes and 7-15 fibers with concentric or monopolar electrodes. Routine qualitative EMG studies rely on observing MUs in free-run mode and qualitatively estimating common metrics. In contrast, quantitative EMG (QEMG) applied to routine studies includes assessment of individual MUs by software available in modern EMG machines with extraction of discrete values for common metrics, and also derived metrics. This results in greater precision and statistical interpretation. Other QEMG techniques assess muscle fiber density within the MU and time variability at the neuromuscular junction. The interference pattern can also be assessed. The number of MUs innervating a muscle can be estimated. Advanced signal processing, called near-fiber EMG, allows for extraction of underlying muscle fiber contributions to MU waveforms. It is also possible to use QEMG to make statistical probabilities of the state of a muscle as to whether normal, myopathic, or neuropathic. Time to acquire QEMG data is minimal. QEMG is most useful in situations where pathology is uncertain.