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BioRxiv : the Preprint Server For... Jun 2024The mammalian spinal locomotor network is composed of diverse populations of interneurons that collectively orchestrate and execute a range of locomotor behaviors....
UNLABELLED
The mammalian spinal locomotor network is composed of diverse populations of interneurons that collectively orchestrate and execute a range of locomotor behaviors. Despite the identification of many classes of spinal interneurons constituting the locomotor network, it remains unclear how the network's collective activity computes and modifies locomotor output on a step-by-step basis. To investigate this, we analyzed lumbar interneuron population recordings and multi-muscle electromyography from spinalized cats performing air stepping and used artificial intelligence methods to uncover state space trajectories of spinal interneuron population activity on single step cycles and at millisecond timescales. Our analyses of interneuron population trajectories revealed that traversal of specific state space regions held millisecond-timescale correspondence to the timing adjustments of extensor-flexor alternation. Similarly, we found that small variations in the path of state space trajectories were tightly linked to single-step, microvolt-scale adjustments in the magnitude of muscle output.
ONE SENTENCE SUMMARY
Features of spinal interneuron state space trajectories capture variations in the timing and magnitude of muscle activations across individual step cycles, with precision on the scales of milliseconds and microvolts respectively.
PubMed: 38948833
DOI: 10.1101/2024.06.20.599927 -
Materials (Basel, Switzerland) May 2024Bimetallic lined pipe (BLP) has been increasingly used in offshore and subsea oil and gas structures, but how to identify the invisible inner defects such as liner wall...
Bimetallic lined pipe (BLP) has been increasingly used in offshore and subsea oil and gas structures, but how to identify the invisible inner defects such as liner wall thinning and interface debonding is a challenge for future development. A nondestructive testing (NDT) method based on pulsed eddy current testing (PECT) has been proposed to face these difficulties. The inspection of the BLP specimen (AISI1020 base tube and SS304 liner) is implemented from outside of the pipe by using a transmitter-receiver-type PECT probe consisting of two induction coils. By simplifying the BLP specimen to stratified conductive plates, the electromagnetic field interaction between the PECT probe and specimen is analytically modeled, and the probe inspection signals due to liner wall thinning and interface debonding are calculated. In order to highlight the weak response (in microvolts) from the liner, the inspection signals are subtracted by the signal, which is calculated in the case of only having a base tube, yielding differential PECT signals. The peak voltage of the differential signal is selected to characterize the liner wall thinning and interface debonding due to its distinguishable and linear variation. Experiment verification is also carried out on a double-walled specimen simulated by a combination of a Q235 casing pipe and SS304 tubes of different sizes. The experimental results basically agree with the analytical predictions. The peak value of the PECT signal has an ascending and descending variation with the increase in the remaining liner wall thickness and debonding gap, respectively, while the negative peak value shows opposite changes. The peak value exhibits a larger sensitivity than the negative peak value. The proposed method shows potential promise in practical applications for the evaluation of the inner defects in BLP lines.
PubMed: 38893916
DOI: 10.3390/ma17112652 -
Wiadomosci Lekarskie (Warsaw, Poland :... 2024Aim: To evaluate the functional connection and the bioelectrical state of the m.masseter and m. sternocleidomastoid using functional tests before and after treatment.
OBJECTIVE
Aim: To evaluate the functional connection and the bioelectrical state of the m.masseter and m. sternocleidomastoid using functional tests before and after treatment.
PATIENTS AND METHODS
Materials and Methods: The sample consisted of 21 individuals with temporomandibular joint dysfunction. Examinations were carried out before and after treatment using repositioning splint therapy and in seated/standing positions.
RESULTS
Results: M. masseter - p=0.072 before treatment and p=0.821 after treatment. Symmetry is also maintained after treatment. After treatment, a significant difference is noted at the level of significance p<0.001 for the right chewing muscle. In seated and standing positions before treatment did not reveal a statistically significant difference (p=0.07, p=0.143) and after (p=0.272, p=0.623).M. sternocleidomastoid- p<0.001 when comparing right and left sides. After treatment, there was no difference between the right and left sides (p=0.169). No statistical difference was found when assessing indicators separately for the right and left muscles in seated and standing positions (p=0.304, p=0.611, p=0.089, p=0.869). When comparing the bioelectric potentials of the right muscle before, after treatment, a statistically significant difference was found p=0.001.
CONCLUSION
Conclusions: Biostatistical analysis of the indicators of bioelectrical activity of m. masseter and sternocleidomastoid indicates no changes in muscle microvolt indicators with changes in body position in patients. However, repositioning splint therapy is associated with reduced muscle tone in initially more spasmodic muscles. It is worth noting that the symmetry of interaction between muscles improves.
Topics: Humans; Masseter Muscle; Female; Male; Adult; Middle Aged; Electromyography; Temporomandibular Joint Disorders; Young Adult
PubMed: 38691797
DOI: 10.36740/WLek202403123 -
IEEE Transactions on Biomedical... Apr 2024This work presents a bi-directional brain-computer interface (BD-BCI) including a high-dynamic-range (HDR) two-step time-domain neural acquisition (TTNA) system and a...
This work presents a bi-directional brain-computer interface (BD-BCI) including a high-dynamic-range (HDR) two-step time-domain neural acquisition (TTNA) system and a high-voltage (HV) multipolar neural stimulation system incorporating dual-mode time-based charge balancing (DTCB) technique. The proposed TTNA includes four independent recording modules that can sense microvolt neural signals while tolerating large stimulation artifacts. In addition, it exhibits an integrated input-referred noise of 2.3 μVrms from 0.1- to 250-Hz and can handle a linear input-signal swing of up to 340 mVPP. The multipolar stimulator is composed of four standalone stimulators each with a maximum current of up to 14 mA (±20-V of voltage compliance) and 8-bit resolution. An inter-channel interference cancellation circuitry is introduced to preserve the accuracy and effectiveness of the DTCB method in the multipolar-stimulation configuration. Fabricated in an HV 180-nm CMOS technology, the BD-BCI chipset undergoes extensive in-vitro and in-vivo evaluations. The recording system achieves a measured SNDR, SFDR, and CMRR of 84.8 dB, 89.6 dB, and >105 dB, respectively. The measurement results verify that the stimulation system is capable of performing high-precision charge balancing with ±2 mV and ±7.5 mV accuracy in the interpulse-bounded time-based charge balancing (TCB) and artifactless TCB modes, respectively.
PubMed: 38635379
DOI: 10.1109/TBCAS.2024.3391190 -
IEEE Transactions on Bio-medical... Apr 2024The aim of this work is to demonstrate the performance of the ECG noise extraction tool (ECGNExT) which provides estimates of ECG noise that are not significantly...
OBJECTIVE
The aim of this work is to demonstrate the performance of the ECG noise extraction tool (ECGNExT) which provides estimates of ECG noise that are not significantly different from the inherent noise in an ECG generated by motion artifacts and other sources. In addition, this paper elaborates on use of ECGNExT in an algorithm evaluation context comparing two QRS detection algorithms.
METHODS
140 simultaneous pairs of clean ECGs and ECGs corrupted with motion-induced noise from 29 participants under five different and separate motion conditions were collected and analyzed. Estimates of the noise component of the ECGs recorded with noise were obtained using ECGNExT and were then added to the clean ECGs yielding estimated ECGs with noise. Root mean squared error (RMSE) between the recorded and estimated ECGs with noise was calculated for temporal comparison, and band powers of the signals were calculated for spectral comparison.
RESULTS
A t-test revealed that the mean RMSE < 150-microvolts with p-value < 0.001 and, and equivalence tests showed that the band powers of the two ECGs were statistically equivalent with .
CONCLUSION
ECGNExT can reliably estimate the underlying ECG noise while preserving temporal and spectral features.
SIGNIFICANCE
We previously proposed ECGNExT as a component of ECG analysis algorithm testing during noise conditions and reported its performance based on simulated ECG data. This work provides additional support of the performance and functionality of the ECGNExT algorithm from a study with pairs of simultaneously recorded ECGs with and without noise from human subjects.
PubMed: 38587945
DOI: 10.1109/TBME.2024.3386493 -
Frontiers in Human Neuroscience 2024Volume conduction models of the human head are used in various neuroscience fields, such as for source reconstruction in EEG and MEG, and for modeling the effects of...
INTRODUCTION
Volume conduction models of the human head are used in various neuroscience fields, such as for source reconstruction in EEG and MEG, and for modeling the effects of brain stimulation. Numerous studies have quantified the accuracy and sensitivity of volume conduction models by analyzing the effects of the geometrical and electrical features of the head model, the sensor model, the source model, and the numerical method. Most studies are based on simulations as it is hard to obtain sufficiently detailed measurements to compare to models. The recording of stereotactic EEG during electric stimulation mapping provides an opportunity for such empirical validation.
METHODS
In the study presented here, we used the potential distribution of volume-conducted artifacts that are due to cortical stimulation to evaluate the accuracy of finite element method (FEM) volume conduction models. We adopted a widely used strategy for numerical comparison, i.e., we fixed the geometrical description of the head model and the mathematical method to perform simulations, and we gradually altered the head models, by increasing the level of detail of the conductivity profile. We compared the simulated potentials at different levels of refinement with the measured potentials in three epilepsy patients.
RESULTS
Our results show that increasing the level of detail of the volume conduction head model only marginally improves the accuracy of the simulated potentials when compared to sEEG measurements. The mismatch between measured and simulated potentials is, throughout all patients and models, maximally 40 microvolts (i.e., 10% relative error) in 80% of the stimulation-recording combination pairs and it is modulated by the distance between recording and stimulating electrodes.
DISCUSSION
Our study suggests that commonly used strategies used to validate volume conduction models based solely on simulations might give an overly optimistic idea about volume conduction model accuracy. We recommend more empirical validations to be performed to identify those factors in volume conduction models that have the highest impact on the accuracy of simulated potentials. We share the dataset to allow researchers to further investigate the mismatch between measurements and FEM models and to contribute to improving volume conduction models.
PubMed: 38410258
DOI: 10.3389/fnhum.2024.1279183 -
Advances in Neonatal Care : Official... Jun 2024Skin-to-skin contact (SSC) is widely implemented in the neonatal intensive care unit (NICU) due to its established role in reducing mortality and morbidity. However, the... (Observational Study)
Observational Study
BACKGROUND
Skin-to-skin contact (SSC) is widely implemented in the neonatal intensive care unit (NICU) due to its established role in reducing mortality and morbidity. However, the impact of SSC on diaphragmatic electrical activity (Edi) in premature infants undergoing noninvasive pressure control (NIV-PC) for respiratory management remains insufficiently explored.
PURPOSE
To assess the effects of SSC on Edi and vital signs in preterm infants managed with NIV-PC.
METHODS
A prospective, observational, crossover study was conducted, involving preterm infants admitted to a level III NICU between May 2020 and August 2021, who were receiving respiratory support with NIV-PC. Data were collected at 3 distinct time points: before SSC (pre-SSC period), during SSC (SSC period), and after SSC (post-SSC period). Thirty-minute periods of stable data were extracted for analysis.
RESULTS
A total of 21 SSC sessions were performed on 14 preterm infants, with a median age at the initiation of SSC of 62 days. The median (interquartile range) Edi peak (in microvolts) before, during, and after SSC was 7.1 (5.8-10.8), 6.8 (4.3-8.8), and 7.1 (5.5-8.8), respectively. No statistically significant differences were observed in Edi peak or minimum values during SSC, when compared with the periods before and after the SSC procedure. Likewise, no significant changes were noted in respiratory rate, oxygen saturation, heart rate, or the incidence of apnea.
IMPLICATIONS FOR PRACTICE AND RESEARCH
SSC in preterm infants undergoing NIV-PC does not exacerbate their clinical condition. Further investigations involving diverse patient cohorts are warranted.
Topics: Humans; Infant, Premature; Infant, Newborn; Prospective Studies; Diaphragm; Female; Cross-Over Studies; Male; Intensive Care Units, Neonatal; Noninvasive Ventilation; Kangaroo-Mother Care Method
PubMed: 38241690
DOI: 10.1097/ANC.0000000000001141 -
Journal of Electrical Bioimpedance Jan 2023Biomedical engineering stands at the forefront of medical innovation, with electroencephalography (EEG) signal analysis providing critical insights into neural...
Biomedical engineering stands at the forefront of medical innovation, with electroencephalography (EEG) signal analysis providing critical insights into neural functions. This paper delves into the utilization of EEG signals within the MILimbEEG dataset to explore their potential for machine learning-based task recognition and diagnosis. Capturing the brain's electrical activity through electrodes 1 to 16, the signals are recorded in the time-domain in microvolts. An advanced feature extraction methodology harnessing Hjorth Parameters-namely Activity, Mobility, and Complexity-is employed to analyze the acquired signals. Through correlation analysis and examination of clustering behaviors, the study presents a comprehensive discussion on the emergent patterns within the data. The findings underscore the potential of integrating these features into machine learning algorithms for enhanced diagnostic precision and task recognition in biomedical applications. This exploration paves the way for future research where such signal processing techniques could revolutionize the efficiency and accuracy of biomedical engineering diagnostics.
PubMed: 38162817
DOI: 10.2478/joeb-2023-0009 -
Biological Psychology Jan 2024In behavioral studies, facial electromyographic (EMG) responses to external stimuli or internal events are usually quantified relative to the resting state, presumed to...
In behavioral studies, facial electromyographic (EMG) responses to external stimuli or internal events are usually quantified relative to the resting state, presumed to represent a neutral baseline condition. In the large majority of recent studies, EMG responses were expressed as a difference score in terms of microvolts with the resting state. We argue that since EMG activity is measured on a ratio scale rather than on an interval scale, percentage scores should be used instead of difference scores. Reanalyzing results from an earlier study on the relationships between facial EMG responses and affective empathic responses to emotional video clips, we found that the two different types of EMG response quantification were differently related to affective empathy. Relationships between EMG responses and affective empathy were more consistent or stronger for percentage scores than for difference scores. In another study, facial EMG mimicry responses to pictures of emotional facial expressions were stronger for percentage scores than for difference scores. The adequacy of percentage scores relative to difference scores as indices of psychological variables may be simply checked by comparing both types of scores.
Topics: Humans; Facial Muscles; Electromyography; Emotions; Empathy; Facial Expression; Reference Standards
PubMed: 38134999
DOI: 10.1016/j.biopsycho.2023.108737 -
Small (Weinheim An Der Bergstrasse,... Jun 2024In order to reveal the dynamic response characteristic of thin film thermocouples (TFTCs), the nichrome/nisil (NiCr/NiSi) TFTCs are prepared onto the glass substrate....
In order to reveal the dynamic response characteristic of thin film thermocouples (TFTCs), the nichrome/nisil (NiCr/NiSi) TFTCs are prepared onto the glass substrate. With short pulse infrared laser system, NiCr/NiSi TFTCs are dynamically calibrated. The thermoelectric electromotive force (TEF) curves of NiCr/NiSi TFTCs are recorded by the memory hicorder system, which could reflect TEF signals with resolution ratio in nanosecond and microvolt, simultaneously. With increasing laser energy from 15.49 to 29.59 mJ, TEF curves display more and more violent oscillation, even negative value. The results show that the bounce of thermal energy happens between two interfaces of TFTCs because the thermal conductivity of glass and air is significantly lower than that of NiSi/NiCr TFTCs. The bounce of thermal energy results in the obvious decrease of n and n, as well as oscillation of TEF. For laser energy in 29.59 mJ, the bounce of thermal energy in NiCr film could result in n < n. Then, TEF value appears abnormal negative value. Based on the results, the complex thermal energy transport process in TFTCs dynamic calibration is revealed, which results in the oscillation of thermal energy and TEF signal.
PubMed: 38084459
DOI: 10.1002/smll.202308002