BACKGROUND: The use of statistical parameter mapping (SPM) to compare gait kinematics of children at different ages seems to be a more appropriate tool to describe the differences than simply describing the maxima and minima on the curves. RESEARCH QUESTION: Does lower limb kinematic waveforms differ during gait in normally developing preschool children? METHODS: In a cross-sectional study, SPM was used to compare kinematic waveforms of typically developing preschool children at ages 2, 3, and 6 years (n = 42). RESULTS: Differences in internal rotation foot angle between 2-year-olds and 3-, 6-year-olds in 22-55 % lower in 2-year-olds but 85-100 % greater in 2-year-olds. Greater internal rotation of the knee in 2-year-olds versus 6-year-olds in 13-25 % of the stance phase. Lower knee abduction in 2-year-olds versus 6-year-olds in the first 13 % of the stance phase. SIGNIFICANCE: Comparison of the waveforms of the angle may provide a clearer understanding of the differences in gait kinematics in children at different ages.
- MeSH
- Biomechanical Phenomena MeSH
- Gait * physiology MeSH
- Child MeSH
- Knee Joint * physiology MeSH
- Humans MeSH
- Child, Preschool MeSH
- Cross-Sectional Studies MeSH
- Range of Motion, Articular * physiology MeSH
- Age Factors MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Male MeSH
- Child, Preschool MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
BACKGROUND: This study investigated the subthalamic nucleus (STN) function and deep brain stimulation (DBS) effects on single-unit activity (SUA) in Parkinson's disease (PD) patients with dysarthria. METHODS: After presurgical speech analysis, we recorded STN neuronal activities while PD patients (n = 16) articulated Chinese Pinyin consonants. The Pinyin consonants were categorized by the manner and place of articulation for SUA cluster analysis. The cohort was then divided into normal articulation and dysarthria groups based on diadochokinetic (DDK) assessments. The STN SUA patterns, represented by the mean firing rate (FR), peak time, and response intensity during articulation, were analyzed and compared between the two groups. Finally, a stimulation cohort of 7 PD patients was included to test articulation and SUA pattern changes following intraoperative DBS. RESULTS: Clustering analysis of STN neuronal firing patterns demonstrated that neurons encode articulation by grouping consonants with the same manner of articulation into distinct clusters. Using k-means clustering, we further classified SUAs into two waveform types: negative spikes (type 1) and positive spikes (type 2). Dysarthria patients exhibited an increased mean FR of type 1 spikes and a reduced response intensity of type 2 spikes. During intraoperative stimulation, PD patients showed accelerated DDK, accompanied by a decrease in type 1 mean FR and an increase in type 2 mean FR. CONCLUSION: Our findings indicate the crucial role of the STN in consonant encoding and dysarthria at the single-unit level. Both SUA firing patterns in the STN and DDK performance can be modulated by DBS.
- MeSH
- Action Potentials physiology MeSH
- Dysarthria * etiology physiopathology MeSH
- Deep Brain Stimulation * methods MeSH
- Middle Aged MeSH
- Humans MeSH
- Neurons * physiology MeSH
- Subthalamic Nucleus * physiopathology MeSH
- Parkinson Disease * physiopathology complications therapy MeSH
- Aged MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
High-frequency waveform recordings of biological signals enable more detailed data analysis and deeper physiological exploration. However, the waveform data—like invasive arterial blood pressure (ABP)—are particularly susceptible to frequent contamination with artifacts that can devalue the subsequent calculations like pressure reactivity index (PRx). This study aimed to verify the ability of the short-time Fourier transform (STFT) based algorithm to detect artifacts in the ABP waveform. Four types of modeled artifacts (rectangular, fast impulse, sawtooth and baseline drift) with different durations and amplitudes were inserted into undisturbed ABP waveforms. Short-time Fourier transform with a 5-second time window is computed on artifact-polluted ABP signals to detect changes in the frequency domain caused by these artifacts. An algorithm with three decision-making rules based on the dominant frequency component, standardized power spectrum, and the value of the second harmonic of the dominant frequency was used. Only segments that passed all three rules were labeled as artifact-free. Results indicated high sensitivity (93.35% and 94.83%) in detecting rectangular and sawtooth artifacts, with specificity exceeding 99% for both. Baseline drift artifact was detected with a low sensitivity of 5.02%, and fast impulse was not detected. This study proposes the application of a short-time Fourier transform-based algorithm to enhance the detection of clinically significant artifacts in arterial blood pressure signals, particularly relevant for PRx and other secondary calculations.
BACKGROUND: The same principle behind pulse wave analysis can be applied on the pulmonary artery (PA) pressure waveform to estimate right ventricle stroke volume (RVSV). However, the PA pressure waveform might be influenced by the direct transmission of the intrathoracic pressure changes throughout the respiratory cycle caused by mechanical ventilation (MV), potentially impacting the reliability of PA pulse wave analysis (PAPWA). We assessed a new method that minimizes the direct effect of the MV on continuous PA pressure measurements and enhances the reliability of PAPWA in tracking beat-to-beat RVSV. METHODS: Continuous PA pressure and flow were simultaneously measured for 2-3 min in 5 pigs using a high-fidelity micro-tip catheter and a transonic flow sensor around the PA trunk, both pre and post an experimental ARDS model. RVSV was estimated by PAPWA indexes such as pulse pressure (SVPP), systolic area (SVSystAUC) and standard deviation (SVSD) beat-to-beat from both corrected and non-corrected PA signals. The reference RVSV was derived from the PA flow signal (SVref). RESULTS: The reliability of PAPWA in tracking RVSV on a beat-to-beat basis was enhanced after accounting for the direct impact of intrathoracic pressure changes induced by MV throughout the respiratory cycle. This was evidenced by an increase in the correlation between SVref and RVSV estimated by PAPWA under healthy conditions: rho between SVref and non-corrected SVSD - 0.111 (0.342), corrected SVSD 0.876 (0.130), non-corrected SVSystAUC 0.543 (0.141) and corrected SVSystAUC 0.923 (0.050). Following ARDS, correlations were SVref and non-corrected SVSD - 0.033 (0.262), corrected SVSD 0.839 (0.077), non-corrected SVSystAUC 0.483 (0.114) and corrected SVSystAUC 0.928 (0.026). Correction also led to reduced limits of agreement between SVref and SVSD and SVSystAUC in the two evaluated conditions. CONCLUSIONS: In our experimental model, we confirmed that correcting for mechanical ventilation induced changes during the respiratory cycle improves the performance of PAPWA for beat-to-beat estimation of RVSV compared to uncorrected measurements. This was demonstrated by a better correlation and agreement between the actual SV and the obtained from PAPWA.
- Publication type
- Journal Article MeSH
Laparoscopic surgery with capnoperitoneum brings many advantages to patients, but also emphasizes the negative impact of anesthesia and mechanical ventilation on the lungs. Even though many studies use electrical impedance tomography (EIT) for lung monitoring during these surgeries, it is not clear what the best position of the electrode belt on the patient's thorax is, considering the cranial shift of the diaphragm. We monitored 16 patients undergoing a laparoscopic surgery with capnoperitoneum using EIT with two independent electrode belts at different tomographic levels: in the standard position of the 4th-6th intercostal space, as recommended by the manufacturer, and in a more cranial position at the level of the axilla. Functional residual capacity (FRC) was measured, and a recruitment maneuver was performed at the end of the procedure by raising the positive end-expiratory pressure (PEEP) by 5 cmH2O. The results based on the spectral analysis of the EIT signal show that the ventilation-related impedance changes are not detectable by the belt in the standard position. In general, the cranial belt position might be more suitable for the lung monitoring during the capnoperitoneum since the ventilation signal remains dominant in the obtained impedance waveform. FRC was significantly decreased by the capnoperitoneum and remained lower also after desufflation.
- MeSH
- Electric Impedance MeSH
- Electrodes MeSH
- Laparoscopy * MeSH
- Humans MeSH
- Tomography, X-Ray Computed * MeSH
- Tomography methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
OBJECTIVES: The electroretinogram is a clinical test commonly used in the diagnosis of retinal disorders with the peak time and amplitude of the a- and b-waves used as the main indicators of retinal function. However, subtle changes that affect the shape of the electroretinogram waveform may occur in the early stages of disease or in conditions that have a neurodevelopmental or neurodegenerative origin. In such cases, we introduce a statistical approach to mathematically model the shape of the electroretinogram waveform that may aid clinicians and researchers using the electroretinogram or other biological signal recordings to identify morphological features in the waveforms that may not be captured by the time or time-frequency domains of the waveforms. We present a statistical graphics-based analysis of the ascending limb of the b-wave (AL-b) of the electroretinogram in children with and without a diagnosis of autism spectrum disorder (ASD) with a narrative explanation of the statistical approach to illustrate how different features of the waveform based on location and scale derived from raw and registered time series can reveal subtle differences between the groups. RESULTS: Analysis of the raw time trajectories confirmed findings of previous studies with a reduced and delayed b-wave amplitude in ASD. However, when the individual time trajectories were registered then group differences were visible in the mean amplitude at registered time ~ 0.6 suggesting a novel method to differentiate groups using registration of the ERG waveform.
- MeSH
- Time Factors MeSH
- Child MeSH
- Electroretinography methods MeSH
- Humans MeSH
- Autism Spectrum Disorder * MeSH
- Retina MeSH
- Photic Stimulation methods MeSH
- Research Design MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Publication type
- Journal Article MeSH
BACKGROUND: Presentation of visual stimuli can induce changes in EEG signals that are typically detectable by averaging together data from multiple trials for individual participant analysis as well as for groups or conditions analysis of multiple participants. This study proposes a new method based on the discrete wavelet transform with Huffman coding and machine learning for single-trial analysis of evenal (ERPs) and classification of different visual events in the visual object detection task. METHODS: EEG single trials are decomposed with discrete wavelet transform (DWT) up to the [Formula: see text] level of decomposition using a biorthogonal B-spline wavelet. The coefficients of DWT in each trial are thresholded to discard sparse wavelet coefficients, while the quality of the signal is well maintained. The remaining optimum coefficients in each trial are encoded into bitstreams using Huffman coding, and the codewords are represented as a feature of the ERP signal. The performance of this method is tested with real visual ERPs of sixty-eight subjects. RESULTS: The proposed method significantly discards the spontaneous EEG activity, extracts the single-trial visual ERPs, represents the ERP waveform into a compact bitstream as a feature, and achieves promising results in classifying the visual objects with classification performance metrics: accuracies 93.60[Formula: see text], sensitivities 93.55[Formula: see text], specificities 94.85[Formula: see text], precisions 92.50[Formula: see text], and area under the curve (AUC) 0.93[Formula: see text] using SVM and k-NN machine learning classifiers. CONCLUSION: The proposed method suggests that the joint use of discrete wavelet transform (DWT) with Huffman coding has the potential to efficiently extract ERPs from background EEG for studying evoked responses in single-trial ERPs and classifying visual stimuli. The proposed approach has O(N) time complexity and could be implemented in real-time systems, such as the brain-computer interface (BCI), where fast detection of mental events is desired to smoothly operate a machine with minds.
- MeSH
- Algorithms MeSH
- Electroencephalography * methods MeSH
- Evoked Potentials physiology MeSH
- Humans MeSH
- Area Under Curve MeSH
- Signal Processing, Computer-Assisted MeSH
- Machine Learning MeSH
- Wavelet Analysis * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Procedural aspects of compassionate care such as the terminal extubation are understudied. We used machine learning methods to determine factors associated with the decision to extubate the critically ill patient at the end of life, and whether the terminal extubation shortens the dying process. We performed a secondary data analysis of a large, prospective, multicentre, cohort study, death prediction and physiology after removal of therapy (DePPaRT), which collected baseline data as well as ECG, pulse oximeter and arterial waveforms from WLST until 30 min after death. We analysed a priori defined factors associated with the decision to perform terminal extubation in WLST using the random forest method and logistic regression. Cox regression was used to analyse the effect of terminal extubation on time from WLST to death. A total of 616 patients were included into the analysis, out of which 396 (64.3%) were terminally extubated. The study centre, low or no vasopressor support, and good respiratory function were factors significantly associated with the decision to extubate. Unadjusted time to death did not differ between patients with and without extubation (median survival time extubated vs. not extubated: 60 [95% CI: 46; 76] vs. 58 [95% CI: 45; 75] min). In contrast, after adjustment for confounders, time to death of extubated patients was significantly shorter (49 [95% CI: 40; 62] vs. 85 [95% CI: 61; 115] min). The decision to terminally extubate is associated with specific centres and less respiratory and/or vasopressor support. In this context, terminal extubation was associated with a shorter time to death.
This study aimed to compare the angle-specific (AS) and non-angle-specific (NAS) hamstring to quadriceps conventional and functional ratios between healthy, hamstring- and ACL-injured elite soccer players. One hundred and eleven players (27.42 ± 8.01 years, 182.11 ± 6.79 cm, 75.93 ± 7.25 kg) completed a series of concentric knee flexor and extensor strength in addition to eccentric knee flexor strength was measured at an angular velocity of 60°.s-1. Normalized and raw peak torque values, and the torque-angle profiles were extracted for analysis. Conventional and functional NAS (peak values) and AS (waveform ratios) hamstring to quadriceps ratios were calculated and compared between the groups. Healthy players produced greater functional and conventional ratios compared to players with either ACL or hamstring injury. Players with hamstring injury produced a lower AS functional ratios between 46° and 54° of knee flexion. Players suffering from ACL injury depicted a lower value for the AS functional ratio between 33° and 56° of knee flexion. Although NAS can identify soccer players with previous hamstring or ACL injury, the range where there is a strength deficiency is eluded. With the use of AS the range where the deficiency is present can be identified, and clinicians can benefit from this analysis to design robust rehabilitation protocols.
- MeSH
- Quadriceps Muscle MeSH
- Soccer * MeSH
- Humans MeSH
- Anterior Cruciate Ligament Injuries * MeSH
- Retrospective Studies MeSH
- Muscle Strength MeSH
- Torque MeSH
- Hamstring Muscles * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Czech physiologist Penaz tried to overcome limitations of invasive pulse-contour methods (PCM) in clinical applications by a non-invasive method (finger mounted BP cuff) for continuous arterial waveform detection and beat-to-beat analysis. This discovery resulted in significant interest in human physiology and non-invasive examination of hemodynamic parameters, however has limitations because of the distal BP recording using a volume-clamp method. Thus, we propose a validation of beat-to-beat signal analysis acquired by novel a brachial occlusion-cuff (suprasystolic) principle and signal obtained from Finapres during a forced expiratory effort against an obstructed airway (Valsalva maneuver). Twelve healthy adult subjects [2 females, age = (27.2 ± 5.1) years] were in the upright siting position, breathe through the mouthpiece (simultaneously acquisition by brachial blood pressure monitor and Finapres) and at a defined time were asked to generate positive mouth pressure for 20 s (Valsalva). For the purpose of signal analysis, we proposed parameter a "Occlusion Cuff Index" (OCCI). The assumption about similarities between measured signals (suprasystolic brachial pulse waves amplitudes and Finapres's MAP) were proved by averaged Pearson's correlation coefficient (r- = 0.60, p < 0.001). The averaged Pearson's correlation coefficient for the comparative analysis of OCCI between methods was r- = 0.88, p < 0.001. The average percent change of OCCI during maneuver: 8% increase, 19% decrease and percent change of max/min ratio is 35%. The investigation of brachial pulse waves measured by novel brachial blood pressure monitor shows positive correlation with Finapres and the parameter OCCI shows promise as an index, which could describe changes during beat-to-beat cardiac cycles.
- MeSH
- Pulse Wave Analysis * MeSH
- Brachial Artery * physiology MeSH
- Adult MeSH
- Blood Pressure physiology MeSH
- Humans MeSH
- Blood Pressure Determination methods MeSH
- Young Adult MeSH
- Fingers MeSH
- Heart Rate MeSH
- Feasibility Studies MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Young Adult MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
