RESUMEN

Magnetic tunnel junction-based molecular spintronics device (MTJMSD) may enable novel magnetic metamaterials by chemically bonding magnetic molecules and ferromagnets (FM) with a vast range of magnetic anisotropy. MTJMSD have experimentally shown intriguing microscopic phenomenon such as the development of highly contrasting magnetic phases on a ferromagnetic electrode at room temperature. This paper focuses on Monte Carlo Simulations (MCS) on MTJMSD to understand the potential mechanism and explore fundamental knowledge about the impact of magnetic anisotropy. The selection of MCS is based on our prior study showing the potential of MCS in explaining experimental results (Tyagi et al. in Nanotechnology 26:305602, 2015). In this paper, MCS is carried out on the 3D Heisenberg model of cross-junction-shaped MTJMSDs. Our research represents the experimentally studied cross-junction-shaped MTJMSD where paramagnetic molecules are covalently bonded between two FM electrodes along the exposed side edges of the magnetic tunnel junction (MTJ). We have studied atomistic MTJMSDs properties by simulating a wide range of easy-axis anisotropy for the case of experimentally observed predominant molecule-induced strong antiferromagnetic coupling. Our study focused on understanding the effect of anisotropy of the FM electrodes on the overall MTJMSDs at various temperatures. This study shows that the multiple domains of opposite spins start to appear on an FM electrode as the easy-axis anisotropy increases. Interestingly, MCS results resembled the experimentally observed highly contrasted magnetic zones on the ferromagnetic electrodes of MTJMSD. The magnetic phases with starkly different spins were observed around the molecular junction on the FM electrode with high anisotropy.

RESUMEN

Increasing balance confidence in older individuals is important towards improving their quality of life and reducing activity avoidance. Here, we investigated if balance confidence (perceived ability) and balance performance (ability) in older adults were related to one another and would improve after balance training. The relationship of balance confidence in conjunction with balance performance for varied conditions (such as limiting vision, modifying somatosensory cues, and also base of support) was explored. We sought to determine if balance confidence and ability, as well as their relationship, could change after several weeks of training. Twenty-seven healthy participants were trained for several weeks during standing and walking exercises. In addition, seven participants with a higher risk of imbalance leading to falls (survivors of stroke) were also trained. Prior to and after training, balance ability and confidence were assessed via the Balance Error Scoring System (BESS) and Activities Specific Balance Confidence (ABC) Scale, respectively. Both groups showed improvements in balance abilities (i.e., BESS errors significantly decreased after training). Balance confidence was significantly higher in the healthy group than in the stroke group; however, ABC results reflected that balance confidence did not significantly increase after training for each. The correlations between balance ability and balance confidence were explored. Encouragingly, healthy participants displayed a negative correlation between BESS errors and ABC (i.e., enhancements in balance confidence (increases in ABC Scale results) were related to improvements in balance ability (decreases in BESS errors)). For the stroke participants, despite improvements in balance ability, our results showed that there was no relation to balance confidence (i.e., no correlation between BESS errors and ABC) in this group.

RESUMEN

For the rapidly growing aging demographic worldwide, robotic training methods could be impactful towards improving balance critical for everyday life. Here, we investigated the hypothesis that non-bodyweight supportive (nBWS) overground robotic balance training would lead to improvements in balance performance and balance confidence in older adults. Sixteen healthy older participants (69.7 ± 6.7 years old) were trained while donning a harness from a distinctive NaviGAITor robotic system. A control group of 11 healthy participants (68.7 ± 5.0 years old) underwent the same training but without the robotic system. Training included 6 weeks of standing and walking tasks while modifying: (1) sensory information (i.e., with and without vision (eyes-open/closed), with more and fewer support surface cues (hard or foam surfaces)) and (2) base-of-support (wide, tandem and single-leg standing exercises). Prior to and post-training, balance ability and balance confidence were assessed via the balance error scoring system (BESS) and the Activities specific Balance Confidence (ABC) scale, respectively. Encouragingly, results showed that balance ability improved (i.e., BESS errors significantly decreased), particularly in the nBWS group, across nearly all test conditions. This result serves as an indication that robotic training has an impact on improving balance for healthy aging individuals.

RESUMEN

With the massive growth of the aging population worldwide, of utmost importance is reducing falls. Critical to reducing fall risk is one's ability to weight incoming sensory information towards maintaining balance. The purpose of this research was to investigate if simple, targeted sensory training on aging individuals (50 - 80 years old), including twelve healthy and eight individuals with chronic stroke, could improve their balance. Repeated sensory training targeted visual (via eyesopen/closed) and somatosensory inputs (via light touch to the fingertip as well as hard, soft foam, and hard foam support surfaces to the feet) during standing and dynamic base-ofsupport (BOS) exercises. Study participants underwent six weeks of training. Prior to and post training, standing balance was assessed via a simple, clinical measure: the balance error scoring system (BESS). Following several weeks of training, participants showed significant improvements in BESS errors: healthy participants for small BOS with limited somatosensory information (i.e., tandem and single-leg standing on foam) and participants with stroke in all conditions.Clinical Relevance- This research study demonstrated that simple, accessible exercises, can positively impact balance in the aging population, a pressing need.

Asunto(s)

Envejecimiento , Equilibrio Postural , Accidentes por Caídas/prevención & control , Anciano , Anciano de 80 o más Años , Ejercicio Físico , Terapia por Ejercicio , Humanos , Persona de Mediana Edad

RESUMEN

This study investigates the properties of the brain electrical activity from different recording regions and physiological states for seizure detection. Neurophysiologists will find the work useful in the timely and accurate detection of epileptic seizures of their patients. We explored the best way to detect meaningful patterns from an epileptic Electroencephalogram (EEG). Signals used in this work are 23.6 s segments of 100 single channel surface EEG recordings collected with the sampling rate of 173.61 Hz. The recorded signals are from five healthy volunteers with eyes closed and eyes open, and intracranial EEG recordings from five epilepsy patients during the seizure-free interval as well as epileptic seizures. Feature engineering was done using; i) feature extraction of each EEG wave in time, frequency and time-frequency domains via Butterworth filter, Fourier Transform and Wavelet Transform respectively and, ii) feature selection with T-test, and Sequential Forward Floating Selection (SFFS). SVM and KNN learning algorithms were applied to classify preprocessed EEG signal. Performance comparison was based on Accuracy, Sensitivity and Specificity. Our experiments showed that SVM has a slight edge over KNN.