PTFE-based antistatic coatings by incorporating modified carbon black.

A kind of antistatic coatings which were applied to nonconductive surfaces were prepared with Polytetrafluoroethylene (PTFE) as matrix, modified carbon black (CB) as conductive filler. Compared to sodium dodecyl sulfate, poly(vinyl pyrrolidone), the TMN-10 modified CB has better wettability, dispersion, stability and re-disperse. When CBTMN-10content is 5 wt.%, the surface resistivity of coating reach to 106Ω*cm, which denotes the coating performance good antistatic behavior. The antistatic coating of 5 wt.% CBTMN-10content is found to exhibit excellent hydrophobicity and high HV hardness. Meanwhile, the low average friction coefficients and wear rate were achieved in antistatic coating of 5 wt.% CBTMN-10content. Furthermore, compared to MXene, reduced graphene oxide, carbon nanotube, the modified CB as conductive material in PTFE antistatic materials could be an useful way not only excellent properties but also large-scale production as well as a reduction in unit cost in antistatic materials.

Ratiometric fluorescence probe based on boric acid-modified carbon dots and alizarin red for sensitive and rapid detection of glyphosate.

By combining boric acid-modified carbon dots (p-CDs) and alizarin red (ARS), a double emission probe p-CDs@ARS with fluorescence at 410 nm and 600 nm is designed for the detection of glyphosate. When Cu2+ is added, it binds with ARS to cause ARS release from p-CDs@ARS, which decreases the fluorescence at 600 nm. However, in the presence of glyphosate, glyphosate competes to the binding of Cu2+, releasing ARS to bind with p-CDs again. Therefore, the fluorescence of 600 nm recovers. Based on this, the fluorescence of 410 nm and 600 nm act as the reference and response signal, respectively, achieving the ratiometric fluorescence detection of glyphosate. The linear range of glyphosate detection is 0.5-50 µM with a limit of detection at 0.37 µM which is well below the maximum residue limit for glyphosate in food. When the probe is used to detect the glyphosate residue in Pearl River water and cucumber, the detection results are well consistent with those detected by HPLC. The established method based on p-CDs@ARS has the advantages that the assembly of ratiometric fluorescence probe is simple, and the detection speed is fast. Additionally, a typical INHIBIT logical system has been successfully constructed based on glyphosate, Cu2+, and the fluorescence signal of p-CDs@ARS.

Values of Baseline Posterior Circulation Acute Stroke Prognosis Early Computed Tomography Score for Treatment Decision of Acute Basilar Artery Occlusion.

BACKGROUND AND PURPOSE: This study aimed to analyze the impact of baseline posterior circulation Acute Stroke Prognosis Early Computed Tomography Score (pc-ASPECTS) on the efficacy and safety of endovascular therapy (EVT) for patients with acute basilar artery occlusion. METHODS: The BASILAR was a nationwide prospective registry of consecutive patients with a symptomatic and radiologically confirmed acute basilar artery occlusion within 24 hours of symptom onset. We estimated the effect of standard medical therapy alone (SMT group) versus SMT plus EVT (EVT group) for patients with documented pc-ASPECTS on noncontrast CT, both as a categorical (0-4 versus 5-7 versus 8-10) and as a continuous variable. The primary outcomes included favorable functional outcomes (modified Rankin Scale ≤3) at 90 days and mortality within 90 days. RESULTS: In total, 823 cases were included: 468 with pc-ASPECTS 8 to 10 (SMT: 71; EVT: 397), 317 with pc-ASPECTS 5 to 7 (SMT: 85; EVT: 232), and 38 with pc-ASPECTS 0 to 4 (SMT: 13; EVT: 25). EVT was associated with higher rate of favorable outcomes (adjusted relative risk with 95% CI, 4.35 [1.30-14.48] and 3.20 [1.68-6.09]; respectively) and lower mortality (60.8% versus 77.6%, P=0.005 and 35.0% versus 66.2%, P<0.001; respectively) than SMT in the pc-ASPECTS 5 to 7 and 8 to 10 subgroups. Continuous benefit curves also showed the superior efficacy and safety of EVT over SMT in patients with pc-ASPECTS ≥5. Furthermore, the prognostic effect of onset to puncture time on favorable outcome with EVT was not significant after adjustment for pc-ASPECTS (adjusted odds ratio, 0.98 [95% CI, 0.94-1.02]). CONCLUSIONS: Patients of basilar artery occlusion with pc-ASPECTS ≥5 could benefit from EVT. The baseline pc-ASPECTS appears more important for decision making and predicting prognosis than time to EVT. Registration: URL: http://www.chictr.org.cn. Unique identifier: ChiCTR1800014759.

Clinical characteristics of hospitalized mild/moderate COVID-19 patients with a prolonged negative conversion time of SARS-CoV-2 nucleic acid detection.

BACKGROUND: The impact of COVID-19 has been devastating on a global scale. The negative conversion time (NCT) of SARS-CoV-2 RNA is closely related to clinical manifestation and disease progression in COVID-19 patients. Our study aimed to predict factors associated with prolonged NCT of SARS-CoV-2 RNA in mild/moderate COVID-19 patients. METHODS: The clinical features, laboratory data and treatment outcomes of COVID-19 patients were retrospectively analyzed. Then univariate and multivariate analysis were used to screen out risk factors of influencing prolonged NCT of SARS-CoV-2 RNA. RESULTS: Thirty-two hospitalized mild/moderate COVID-19 patients were enrolled. The general clinical symptoms were cough (78.1%), fever (75%), diarrhea (68.8%), expectoration (56.3%), and nausea (37.5%). More than 40% of the patients had decreased erythrocyte, hemoglobin and leucocyte and 93.8% patients were detected in abnormalities of chest CT. The median NCT of SARS-CoV-2 RNA was 19.5 days (IQR: 14.25-25). Univariate analysis found fever, nausea, diarrhea and abnormalities in chest CTs were positively associated with prolonged NCT of viral RNA (P< 0.05). The multivariate Cox proportional hazard model revealed that fever [Exp (B), 0.284; 95% CI, 0.114-0.707; P<0.05] and nausea [Exp (B), 0.257; 95%CI, 0.096-0.689; P<0.05] were two significant independent factors. CONCLUSIONS: Fever and nausea were two significant independent factors in prolonged NCT of viral RNA in mild/moderate COVID-19 patients, which provided a useful references for disease progression and treatment of COVID-19.

Prolonged time course of population excitatory postsynaptic potentials in motoneurons of chronic stroke survivors.

Hyperexcitability of spinal motoneurons may contribute to muscular hypertonia after hemispheric stroke. The origins of this hyperexcitability are not clear, but we hypothesized that prolongation of the Ia excitatory postsynaptic potential (EPSP) in spastic motoneurons may be one potential mechanism, by enabling more effective temporal summation of Ia EPSPs, making action potential initiation easier. Thus, the purpose of this study is to quantify the time course of putative EPSPs in spinal motoneurons of chronic stroke survivors. To estimate the EPSP time course, a pair of low-intensity electrical stimuli was delivered sequentially to the median nerve in seven hemispheric stroke survivors and in six intact individuals, to induce an H-reflex response from the flexor carpi radialis muscle. H-reflex response probability was then used to quantify the time course of the underlying EPSPs in the motoneuron pool. A population EPSP estimate was then derived, based on the probability of evoking an H-reflex from the second test stimulus in the absence of a reflex response to the first conditioning stimulus. Our experimental results showed that in six of seven hemispheric stroke survivors, the apparent rate of decay of the population EPSP was markedly slower in spastic compared with contralateral (stroke) and intact motoneuron pools. There was no significant difference in EPSP time course between the contralateral side of stroke survivors and control subject muscles. We propose that one potential mechanism for hyperexcitability of spastic motoneurons in chronic stroke survivors may be associated with this prolongation of the Ia EPSP time course. Our subthreshold double-stimulation approach could provide a noninvasive tool for quantifying the time course of EPSPs in both healthy and pathological conditions. NEW & NOTEWORTHY Spastic motoneurons in stroke survivors showed a prolonged Ia excitatory postsynaptic potential (EPSP) time course compared with contralateral and intact motoneurons, suggesting that one potential mechanism for hyperexcitability of spastic motoneurons in chronic stroke survivors may be associated with this prolongation of the Ia EPSP time course.

Organization of the motor-unit pool for different directions of isometric contraction of the first dorsal interosseous muscle.

INTRODUCTION: Muscle force generation involves recruitment and firing rate modulation of motor units (MUs). The control of MUs in producing multidirectional forces remains unclear. METHODS: We studied MU recruitment and firing properties, recorded from the first dorsal interosseous muscle, for 3 different directions of contraction: abduction; abduction/flexion combination; and flexion. RESULTS: MUs were recruited systematically at higher threshold force during flexion. Larger MUs were recruited and firing rates of MUs were lower during abduction. There was an orderly recruitment of MUs according to MU size regardless of contraction direction, obeying the "size principle." Firing rates of earlier-recruited MUs were consistently higher than later-recruited MUs, affirming the "onion-skin" property. DISCUSSION: Our findings suggest that the size principle and onion-skin organization together provide a general description of MU recruitment patterns and firing properties. The directional alternations of MU control properties likely reflect changes in neural drive to the muscle. Muscle Nerve 57: E85-E93, 2018.

Muscle fatigue increases beta-band coherence between the firing times of simultaneously active motor units in the first dorsal interosseous muscle.

Synchronization between the firing times of simultaneously active motor units (MUs) is generally assumed to increase during fatiguing contractions. To date, however, estimates of MU synchronization have relied on indirect measures, derived from surface electromyographic (EMG) interference signals. This study used intramuscular coherence to investigate the correlation between MU discharges in the first dorsal interosseous muscle during and immediately following a submaximal fatiguing contraction, and after rest. Coherence between composite MU spike trains, derived from decomposed surface EMG, were examined in the delta (1-4 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-60 Hz) frequency band ranges. A significant increase in MU coherence was observed in the delta, alpha, and beta frequency bands postfatigue. In addition, wavelet coherence revealed a tendency for delta-, alpha-, and beta-band coherence to increase during the fatiguing contraction, with subjects exhibiting low initial coherence values displaying the greatest relative increase. This was accompanied by an increase in MU short-term synchronization and a decline in mean firing rate of the majority of MUs detected during the sustained contraction. A model of the motoneuron pool and surface EMG was used to investigate factors influencing the coherence estimate. Simulation results indicated that changes in motoneuron inhibition and firing rates alone could not directly account for increased beta-band coherence postfatigue. The observed increase is, therefore, more likely to arise from an increase in the strength of correlated inputs to MUs as the muscle fatigues.

Monolayer g-C3N4 Fluorescent Sensor for Sensitive and Selective Colorimetric Detection of Silver ion from Aqueous Samples.

Rapid and sensitive detection of heavy-metal ions in natural water environments worldwide is urgently needed because of their severe threats to human health. In the present work, monolayer graphite-like flake C3N4 (g-C3N4) materials were applied as a new fluorescent sensor for the detection of trace silver ion in aqueous solution. The thickness of synthesized g-C3N4 was 0.45 nm and obtained by exfoliating twice with ultrasonic. With the presence of ethylene diamine tetraacetic acid as a screening agent, the highly sensitive sensor reached a low detection limit of 52.3 nmol/L for silver (I) ion and there was no disturbance when silver (I) ion coexisted with other metal ions in water samples. Under the optimal conditions, the monolayer g-C3N4 was successfully used to detect trace silver (I) ion in different environmental water and drinking water samples.

Preparation and characterization of an aptamer-functionalized solid-phase microextraction fiber and its application in the selective monitoring of adenosine phosphates with liquid chromatography and tandem mass spectrometry.

An aptamer with adenosine triphosphate as a ligand was immobilized onto the surface of a porous-polymer-coated fiber to obtain an aptamer-functionalized porous-polymer-coated solid-phase microextraction fiber. The fiber was observed with a crosslinked and porous morphological surface structure. It shows specific selectivity to adenosine triphosphate with a selectivity coefficient of 22.1 compared to the scrambled oligonucleotide functionalized fiber, and the selectivity factors over other analogues and reference compounds were from 6.1 to 77.5. When the fiber-based solid-phase microextraction was coupled with liquid chromatography and tandem mass spectrometry, detection limits of 2.7, 29, and 34 µg/L were achieved for adenosine triphosphate, adenosine diphosphate, and adenosine monophosphate, respectively. The spiking recoveries of 77.6-91.9% were achieved for trace adenosine phosphates in human serum sample. Furthermore, the fibers showed high stability and good reusability and could be used over 50 times for the real serum sample pretreatment without remarkable performance reduction.

Effect on glycemia in rats with type 2 diabetes induced by streptozotocin: low-frequency electro-pulse needling stimulated Weiwanxiashu (EX-B 3) and Zusanli (ST 36).

OBJECTIVE: To investigate the effect of low frequency electro-pulse acupuncture (EA) on blood glucose in rats with streptozotocin-induced type 2 diabetes, and the possible mechanism underlying the action. METHODS: Rat models were established with high fat feeding and intraperitoneal injection of streptozotocin (STZ) (30 mg/kg). Rats with a random blood glucose > 16.7 mmol/L and blood glucose at 2 h-point of oral glucose tolerance test (OGTT) > 11.1 mmol/L were included as diabetic rats, and randomly divided into model group, EA Weiwanxiashu (EX-B 3) group, EA Zusanli (ST 36) group, glimepiride group, and EA non-acupoint group (n = 12). EA (2 Hz continuous wave, 2 mA, 20 min/day, 6 days/week, 4 weeks) and intra-gastric administration of glimepiride were applied as interventions. With fasting blood glucose and OGTT tested at the end of the intervention, the study observed the patterns of hypoglycemic effects. For mechanism study, it observes hematoxylin and eosin staining and Masson staining of pancreas paraffin sections, protein expression of glucagon- like peptide 1 receptor (GLP-1R) in the pancreas and skeletal muscle, glucose transporter 4 (GLUT4) protein expression in skeletal muscle membrane, to detect whether EA controls blood glucose via regulation of GLP-1R. RESULTS: EA Weiwanxiashu (EX-B 3) significantly increased model rats' pancreas GLP-1R, and GLUT4 of skeletal muscle membrane; the therapy significantly decreased model rats' skeletal muscle GLP-1R, restored pancreas morphology, and reduced fasting blood glucose and insulin resistance indices. CONCLUSION: EA Weiwanxiashu (EX-B 3) alone has significant effect on glycemia. EA Weiwanxiashu (EX-B 3) plus glimepiride further strengthen the effect. The regulation of the GLP-1R in pancreas and skeletal muscle might be mechanism underpinning the effect.

Estimating the time course of population excitatory postsynaptic potentials in motoneurons of spastic stroke survivors.

Hyperexcitable motoneurons are likely to contribute to muscle hypertonia after a stroke injury; however, the origins of this hyperexcitability are not clear. One possibility is that the effective duration of the Ia excitatory postsynaptic potential (EPSP) is prolonged, increasing the potential for temporal summation of EPSPs, making action potential initiation easier. Accordingly, the purpose of this study was to quantify the time course of EPSPs in motoneurons of stroke survivors. The experimental protocol, which was based on parameters derived from simulation, involved sequential subthreshold electrical stimuli delivered to the median nerve of hemispheric stroke survivors. The resulting H-reflex responses were recorded in the flexor carpi radialis muscle. H-reflex response probability was then used to quantify the time course of the underlying EPSPs in the motoneuron pool. A population EPSP was estimated based on the probability of evoking an H reflex from the second electrical stimulus in the absence of a reflex response to the first stimulus. The accuracy of this time-course estimate was quantified using a computer simulation that explored a range of feasible EPSP parameters. Our experimental results showed that in all five hemispheric stroke survivors the rate of decay of the population EPSP was consistently slower in spastic compared with the contralateral motoneuron pools. We propose that one potential mechanism for hyperexcitability of motoneurons in spastic stroke survivors may be linked to this prolongation of the Ia EPSP time course. Our subthreshold double-stimulation approach also provides a noninvasive tool for quantifying the time course of EPSPs in both healthy and pathological conditions.

Changes in motor unit behavior following isometric fatigue of the first dorsal interosseous muscle.

The neuromuscular strategies employed to compensate for fatigue-induced muscle force deficits are not clearly understood. This study utilizes surface electromyography (sEMG) together with recordings of a population of individual motor unit action potentials (MUAPs) to investigate potential compensatory alterations in motor unit (MU) behavior immediately following a sustained fatiguing contraction and after a recovery period. EMG activity was recorded during abduction of the first dorsal interosseous in 12 subjects at 20% maximum voluntary contraction (MVC), before and directly after a 30% MVC fatiguing contraction to task failure, with additional 20% MVC contractions following a 10-min rest. The amplitude, duration and mean firing rate (MFR) of MUAPs extracted with a sEMG decomposition system were analyzed, together with sEMG root-mean-square (RMS) amplitude and median frequency (MPF). MUAP duration and amplitude increased immediately postfatigue and were correlated with changes to sEMG MPF and RMS, respectively. After 10 min, MUAP duration and sEMG MPF recovered to prefatigue values but MUAP amplitude and sEMG RMS remained elevated. MU MFR and recruitment thresholds decreased postfatigue and recovered following rest. The increase in MUAP and sEMG amplitude likely reflects recruitment of larger MUs, while recruitment compression is an additional compensatory strategy directly postfatigue. Recovery of MU MFR in parallel with MUAP duration suggests a possible role for metabolically sensitive afferents in MFR depression postfatigue. This study provides insight into fatigue-induced neuromuscular changes by examining the properties of a large population of concurrently recorded single MUs and outlines possible compensatory strategies involving alterations in MU recruitment and MFR.

Permethylated-ß-Cyclodextrin Capped CdTe Quantum Dot and its Sensitive Fluorescence Analysis of Malachite Green.

In the present work, the CdTe quantum dots were covalently conjugated with permethylated-ß-cyclodextrin (OMe-ß-CD) using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride as cross-linking reagent. The obtained functional quantum dots (OMe-ß-CD/QDs) showed highly luminescent, water solubility and photostability as well as good inclusion ability to malachite green. A sensitive fluorescence method was developed for the analysis of malachite green in different samples. The good linearity was 2.0 × 10(-7)-1.0 × 10(-5) mol/L and the limit of detect was 1.7 × 10(-8) mol/L. The recoveries for three environmental water samples were 92.0-108.2 % with relative standard deviation (RSD) of 0.24-1.87 %, while the recovery for the fish sample was 94.3 % with RSD of 1.04 %. The results showed that the present method was sensitive and convenient to determine malachite green in complex samples. Graphical Abstract The analytical mechanism of OMe-ß-CD/QDs and its linear response to MG.

In situ detection of salicylic acid binding sites in plant tissues.

The determination of hormone-binding sites in plants is essential in understanding the mechanisms behind hormone function. Salicylic acid (SA) is an important plant hormone that regulates responses to biotic and abiotic stresses. In order to label SA-binding sites in plant tissues, a quantum dots (QDs) probe functionalized with a SA moiety was successfully synthesized by coupling CdSe QDs capped with 3-mercaptopropionic acid (MPA) to 4-amino-2-hydroxybenzoic acid (PAS), using 1-ethyl-3-(3-dimethyllaminopropyl) carbodiimide (EDC) as the coupling agent. The probe was then characterized by dynamic light scattering and transmission electron microscopy, as well as UV/vis and fluorescence spectrophotometry. The results confirmed the successful conjugation of PAS to CdSe QDs and revealed that the conjugates maintained the properties of the original QDs, with small core diameters and adequate dispersal in solution. The PAS-CdSe QDs were used to detect SA-binding sites in mung bean and Arabidopsis thaliana seedlings in vitro and in vivo. The PAS-CdSe QDs were effectively transported into plant tissues and specifically bound to SA receptors in vivo. In addition, the effects of the PAS-CdSe QDs on cytosolic Ca(2+) levels in the tips of A. thaliana seedlings were investigated. Both SA and PAS-CdSe QDs had similar effects on the trend in cytosolic-free Ca(2+) concentrations, suggesting that the PAS-CdSe QDs maintained the bioactivity of SA. To summarize, PAS-CdSe QDs have high potential as a fluorescent probe for the in vitro/in vivo labeling and imaging of SA receptors in plants.

Changes in motoneuron afterhyperpolarization duration in stroke survivors.

Hemispheric brain injury resulting from a stroke is often accompanied by muscle weakness in limbs contralateral to the lesion. In the present study, we investigated whether weakness in contralesional hand muscle in stroke survivors is partially attributable to alterations in motor unit activation, including alterations in firing rate modulation range. The afterhyperpolarization (AHP) potential of a motoneuron is a primary determinant of motoneuron firing rate. We examined differences in AHP duration in motoneurons innervating paretic and less impaired (contralateral) limb muscles of hemiparetic stroke survivors as well as in control subjects. A novel surface EMG (sEMG) electrode was used to record motor units from the first dorsal interosseous muscle. The sEMG data were subsequently decomposed to derive single-motor unit events, which were then utilized to produce interval (ISI) histograms of the motoneuron discharges. A modified version of interval death rate (IDR) analysis was used to estimate AHP duration. Results from data analyses performed on both arms of 11 stroke subjects and in 7 age-matched control subjects suggest that AHP duration is significantly longer for motor units innervating paretic muscle compared with units in contralateral muscles and in units of intact subjects. These results were supported by a coefficient of variation (CV) analysis showing that paretic motor unit discharges have a lower CV than either contralateral or control units. This study suggests that after stroke biophysical changes occur at the motoneuron level, potentially contributing to lower firing rates and potentially leading to less efficient force production in paretic muscles.

Unsupervised neural decoding for concurrent and continuous multi-finger force prediction.

Reliable prediction of multi-finger forces is crucial for neural-machine interfaces. Various neural decoding methods have progressed substantially for accurate motor output predictions. However, most neural decoding methods are performed in a supervised manner, i.e., the finger forces are needed for model training, which may not be suitable in certain contexts, especially in scenarios involving individuals with an arm amputation. To address this issue, we developed an unsupervised neural decoding approach to predict multi-finger forces using spinal motoneuron firing information. We acquired high-density surface electromyogram (sEMG) signals of the finger extensor muscle when subjects performed single-finger and multi-finger tasks of isometric extensions. We first extracted motor units (MUs) from sEMG signals of the single-finger tasks. Because of inevitable finger muscle co-activation, MUs controlling the non-targeted fingers can also be recruited. To ensure an accurate finger force prediction, these MUs need to be teased out. To this end, we clustered the decomposed MUs based on inter-MU distances measured by the dynamic time warping technique, and we then labeled the MUs using the mean firing rate or the firing rate phase amplitude. We merged the clustered MUs related to the same target finger and assigned weights based on the consistency of the MUs being retained. As a result, compared with the supervised neural decoding approach and the conventional sEMG amplitude approach, our new approach can achieve a higher R2 (0.77 ± 0.036 vs. 0.71 ± 0.11 vs. 0.61 ± 0.09) and a lower root mean square error (5.16 ± 0.58 %MVC vs. 5.88 ± 1.34 %MVC vs. 7.56 ± 1.60 %MVC). Our findings can pave the way for the development of accurate and robust neural-machine interfaces, which can significantly enhance the experience during human-robotic hand interactions in diverse contexts.

Towards Efficient Neural Decoder for Dexterous Finger Force Predictions.

OBJECTIVE: Dexterous control of robot hands requires a robust neural-machine interface capable of accurately decoding multiple finger movements. Existing studies primarily focus on single-finger movement or rely heavily on multi-finger data for decoder training, which requires large datasets and high computation demand. In this study, we investigated the feasibility of using limited single-finger surface electromyogram (sEMG) data to train a neural decoder capable of predicting the forces of unseen multi-finger combinations. METHODS: We developed a deep forest-based neural decoder to concurrently predict the extension and flexion forces of three fingers (index, middle, and ring-pinky). We trained the model using varying amounts of high-density EMG data in a limited condition (i.e., single-finger data). RESULTS: We showed that the deep forest decoder could achieve consistently commendable performance with 7.0% of force prediction errors and R2 value of 0.874, significantly surpassing the conventional EMG amplitude method and convolutional neural network approach. However, the deep forest decoder accuracy degraded when a smaller amount of data was used for training and when the testing data became noisy. CONCLUSION: The deep forest decoder shows accurate performance in multi-finger force prediction tasks. The efficiency aspect of the deep forest lies in the short training time and small volume of training data, which are two critical factors in current neural decoding applications. SIGNIFICANCE: This study offers insights into efficient and accurate neural decoder training for advanced robotic hand control, which has the potential for real-life applications during human-machine interactions.

Unsupervised separation of nonlinearly mixed event-related potentials using manifold clustering and non-negative matrix factorization.

Event-related potentials (ERPs) can quantify brain responses to reveal the neural mechanisms of sensory perception. However, ERPs often reflect nonlinear mixture responses to multiple sources of sensory stimuli, and an accurate separation of the response to each stimulus remains a challenge. This study aimed to separate the ERP into nonlinearly mixed source components specific to individual stimuli. We developed an unsupervised learning method based on clustering of manifold structures of mixture signals combined with channel optimization for signal source reconstruction using non-negative matrix factorization (NMF). Specifically, we first implemented manifold learning based on Local Tangent Space Alignment (LTSA) to extract the spatial manifold structure of multi-resolution sub-signals separated via wavelet packet transform. We then used fuzzy entropy to extract the dynamical process of the manifold structures and performed a k-means clustering to separate different sources. Lastly, we used NMF to obtain the optimal contributions of multiple channels to ensure accurate source reconstructions. We evaluated our developed approach using a simulated ERP dataset with known ground truth of two components of ERP mixture signals. Our results show that the correlation coefficient between the reconstructed source signal and the true source signal was 92.8 % and that the separation accuracy in ERP amplitude was 91.6 %. The results show that our unsupervised separation approach can accurately separate ERP signals from nonlinear mixture source components. The outcomes provide a promising way to isolate brain responses to multiple stimulus sources during multisensory perception.

Decomposing Task-Relevant Information From Surface Electromyogram for User-Generic Dexterous Finger Force Decoding.

Existing electromyographic (EMG) based motor intent detection algorithms are typically user-specific, and a generic model that can quickly adapt to new users is highly desirable. However, establishing such a model remains a challenge due to high inter-person variability and external interference with EMG signals. In this study, we present a feature disentanglement approach, implemented by an autoencoder-like architecture, designed to decompose user-invariant, motor-task-sensitive high-level representations from user-sensitive, task-irrelevant representations in EMG amplitude features. Our method is user-generic and can be applied to unseen users for continuous multi-finger force predictions. We evaluated our approach on eight subjects, predicting the force of three fingers (index, middle, and ring-pinky) concurrently. We assessed the decoder's performance through a rigorous leave-one-subject-out validation. Our developed approach consistently outperformed both the conventional EMG amplitude method and a commonly used feature projection approach, principal component analysis (PCA), with a lower force prediction error (RMSE: 6.91 ± 0.45 % MVC; R2: 0.835 ± 0.026) and a higher finger classification accuracy (83.0 ± 4.5%). The comparison with the state-of-the-art neural networks further demonstrated the superior performance of our method in user-generic force predictions. Overall, our methods provide novel insights into the development of user-generic and accurate neural decoding for myoelectric control of assistive robotic hands.

Quantifying Muscle Co-Activation for Impaired Finger Independence in Stroke Survivors.

OBJECTIVE: Hand impairment frequently occurs in individuals following a stroke. There is evidence of abnormal muscle co-activation that contributes to impaired control of finger independence. This study quantitatively analyzed hand muscle co-activation patterns of chronic stroke survivors. Systematically quantifying the degree of muscle co-activation patterns in stroke survivors can help us to better understand the mechanisms behind compromised finger independence and enables a more accurate assessment of hand impairment. METHODS: We analyzed muscle co-activation patterns both macroscopically and microscopically using high-density surface electromyographic (HD-sEMG) signals and decomposed motor unit signals from extrinsic and intrinsic flexor/extensor muscles. The muscle co-activation patterns between both sides of stroke survivors and neurologically intact controls were compared. RESULTS: We observed increased levels of co-activation in the affected sides of stroke survivors compared with their contralateral sides and the control groups, with a higher degree in the extrinsic muscles than the intrinsic muscles. The asymmetry in muscle co-activation between hands correlated with impaired finger force independence and clinical assessment scales. In the micro-level analysis of motor unit action potentials (MUAPs) distributions, we observed a notable increase in action potential spread of MUAPs in the individual affected extrinsic muscles, but the altered MUAP distribution did not correlate with clinical assessment scales. CONCLUSION: We systematically quantified abnormal muscle co-activation patterns in impaired finger independence after stroke. SIGNIFICANCE: With further development, the outcomes provide a comprehensive understanding of hand dexterity deficits in stroke survivors, which may provide guidance for targeted rehabilitation strategies and offer a potential for automated impairment evaluations.