Surface electromyogram, kinematic, and kinetic dataset of lower limb walking for movement intent recognition.

Surface electromyogram (sEMG) offers a rich set of motor information for decoding limb motion intention that serves as a control input to Intelligent human-machine synergy systems (IHMSS). Despite growing interest in IHMSS, the current publicly available datasets are limited and can hardly meet the growing demands of researchers. This study presents a novel lower limb motion dataset (designated as SIAT-LLMD), comprising sEMG, kinematic, and kinetic data with corresponding labels acquired from 40 healthy humans during 16 movements. The kinematic and kinetic data were collected using a motion capture system and six-dimensional force platforms and processed using OpenSim software. The sEMG data were recorded using nine wireless sensors placed on the subjects' thigh and calf muscles on the left limb. Besides, SIAT-LLMD provides labels to classify the different movements and different gait phases. Analysis of the dataset verified the synchronization and reproducibility, and codes for effective data processing are provided. The proposed dataset can serve as a new resource for exploring novel algorithms and models for characterizing lower limb movements.

A Novel Flexible Sensor for Muscle Shape Change Monitoring in Limb Motion Recognition.

Human limb movement intent recognition fundamentally provides the control mechanism for assistive devices such as exoskeleton and limb prosthesis. While different biopotential signals have been utilized for limb movement intent decoding, they seldom could account for spatial information associated with changes in muscle shape that could also be used to characterize the limb motor intent. Therefore, this study developed a novel nano gold stretchable-flexible sensor that captures spatial information associated with the muscle shape change signal (MSCS) during different muscle activation patterns. The novel sensor consists of 2-channels to acquire MSCS at a sampling rate of 125 Hz, corresponding to multiple classes of upper limb movements acquired across six able-bodied subjects. By utilizing the linear discriminant analysis algorithm on the acquired data with a single extracted feature, an overall average motion decoding accuracy of 90.9% was achieved. In addition, the waveform analysis results show that the novel sensor's recordings were less affected by external interferences, thus yielding high quality signals. This study is the first to utilize nano gold stretchable-flexible material for sensor fabrication in pattern recognition of upper limb movement intent, which may facilitate the development of effective assistive devices.

A Long Noncoding RNA ZEB1-AS1 Promotes Tumorigenesis and Predicts Poor Prognosis in Glioma.

Emerging studies show that long noncoding RNAs (lncRNAs) have important roles in carcinogenesis. lncRNA ZEB1 antisense 1 (ZEB1-AS1) is a novel lncRNA, whose clinical significance, biological function, and underlying mechanism remains unclear in glioma. Here, we found that ZEB1-AS1 was highly expressed in glioma tissues, being closely related to clinical stage of glioma. Moreover, patients with high ZEB1-AS1 levels had poor prognoses, with the evidence provided by multivariate Cox regression analysis indicating that ZEB1-AS1 expression could serve as an independent prognostic factor in glioma patients. Functionally, silencing of ZEB1-AS1 could significantly inhibit cell proliferation, migration, and invasion, as well as promote apoptosis. Knockdown of ZEB1-AS1 significantly induced the G0/G1 phase arrest and correspondingly decreased the percentage of S phase cells. Further analysis indicated that ZEB1-AS1 could regulate the cell cycle by inhibiting the expression of G1/S transition key regulators, such as Cyclin D1 and CDK2. Furthermore, ZEB1-AS1 functioned as an important regulator of migration and invasion via activating epithelial to mesenchymal transition (EMT) through up-regulating the expression of ZEB1, MMP2, MMP9, N-cadherin, and Integrin-ß1 as well as decreasing E-cadherin levels in the metastatic progression of glioma. Additionally, forced down-regulation of ZEB1-AS1 could dramatically promote apoptosis by increasing the expression level of Bax and reducing Bcl-2 expression in glioma. Taken together, our data suggest that ZEB1-AS1 may serve as a new prognostic biomarker and therapeutic target of glioma.