Predicted glomerular responses

Predicted glomerular responses using the proposed neural network model. Values in each cell represents the standardized glomerular activity (z-score). Each cell is assigned to the 2D grid with the value "1" shown in the modPos file in the order from upper-left to lower-right

Mol files

Mol files to compute molecular descriptors by Dragon (Kode srl, Italy

An Artificial EMG Generation Model Based on Signal-dependent Noise and Related Application to Motion Classification

The experimental data of measured and artificial EMG signals

DataSheet1_Noninvasive characterization of peripheral sympathetic activation across sensory stimuli using a peripheral arterial stiffness index.PDF

Introduction: The peripheral arterial stiffness index has been proposed and validated as a noninvasive measure quantifying stimulus intensity based on amplitude changes induced by sympathetic innervation of vascular tone. However, its temporal response characteristics remain unclear, thus hindering continuous and accurate monitoring of the dynamic process of sympathetic activation. This paper presents a study aimed at modeling the transient response of the index across sensory stimuli to characterize the corresponding peripheral sympathetic activation.Methods: The index was measured using a continuous arterial pressure monitor and a pulse oximeter during experiments with local pain and local cooling stimuli designed to elicit different patterns of sympathetic activation. The corresponding response of the index was modeled to clarify its transient response characteristics across stimuli.Results: The constructed transfer function accurately depicted the transient response of the index to local pain and local cooling stimuli (Fit percentage: 78.4% ± 11.00% and 79.92% ± 8.79%). Differences in dead time (1.17 ± 0.67 and 0.99 ± 0.56 s, p = 0.082), peak time (2.89 ± 0.81 and 2.64 ± 0.68 s, p = 0.006), and rise time (1.81 ± 0.50 and 1.65 ± 0.48 s, p = 0.020) revealed different response patterns of the index across stimuli. The index also accurately characterized similar vasomotor velocities at different normalized peak amplitudes (0.19 ± 0.16 and 0.16 ± 0.19 a.u., p = 0.007).Discussion: Our findings flesh out the characterization of peripheral arterial stiffness index responses to different sensory stimuli and demonstrate its validity in characterizing peripheral sympathetic activation. This study valorizes a noninvasive method to characterize peripheral sympathetic activation, with the potential to use this index to continuously and accurately track sympathetic activators.</p

Development of a pneumatic artificial muscle driven by low pressure and its application to the unplugged powered suit

<p>Assistive suits reduce human muscle effort by improving human motion. However, most assistive suits are bulky, are expensive, need external power sources, and are impractical to carry everywhere. We present the development of the pneumatic gel muscle, which can be actuated by very low air pressure, and its characteristics by comparing with a commercially available artificial muscle. We also discuss the design of an unplugged powered suit for walking assist that unloads the muscle effort using the pneumatic gel muscle, demonstrating that assistive forces can be applied without the use of a compressor or air tanks. We performed experiments to measure characteristics of the pneumatic gel muscle, such as the actuation and applied force, for various pressure ranges. We measured surface EMG of the lower limb with and without an unplugged powered suit to identify the unloading effect of the suit.</p

A Mathematical Model of the Olfactory Bulb for the Selective Adaptation Mechanism in the Rodent Olfactory System

<div><p>To predict the odor quality of an odorant mixture, the interaction between odorants must be taken into account. Previously, an experiment in which mice discriminated between odorant mixtures identified a selective adaptation mechanism in the olfactory system. This paper proposes an olfactory model for odorant mixtures that can account for selective adaptation in terms of neural activity. The proposed model uses the spatial activity pattern of the mitral layer obtained from model simulations to predict the perceptual similarity between odors. Measured glomerular activity patterns are used as input to the model. The neural interaction between mitral cells and granular cells is then simulated, and a dissimilarity index between odors is defined using the activity patterns of the mitral layer. An odor set composed of three odorants is used to test the ability of the model. Simulations are performed based on the odor discrimination experiment on mice. As a result, we observe that part of the neural activity in the glomerular layer is enhanced in the mitral layer, whereas another part is suppressed. We find that the dissimilarity index strongly correlates with the odor discrimination rate of mice: <i>r</i> = 0.88 (<i>p</i> = 0.019). We conclude that our model has the ability to predict the perceptual similarity of odorant mixtures. In addition, the model also accounts for selective adaptation via the odor discrimination rate, and the enhancement and inhibition in the mitral layer may be related to this selective adaptation.</p></div

Screenshot of the EMG measurement system.

<p>The bar graph shows the muscle activation level of the agonist muscle.</p

Average classification rates of each method.

<p>(a) Muscle activation level of 40%MVC. (b) Muscle activation level of 80%MVC. Error bars in the results of Subjects A–D represent the standard deviations for all trials and those in the average of all subjects represent the standard deviations for all subjects.</p

Location of the electrodes.

<p>EMG signals were recorded using six electrodes (<i>L</i> = 6: Ch. 1: extensor carpi ulnaris; Ch. 2: flexor digitorum profundus; Ch. 3: extensor digitorum; Ch. 4: flexor carpi ulnaris; Ch. 5: triceps brachii; Ch. 6: biceps brachii) at a sampling frequency of 1000 Hz.</p

Scene of the EMG recording.

<p>The subjects were seated with the right upper arm pointing downward, the right forearm bent forward to the horizontal, and the palm turned upward. EMG signals were recorded from a pair of electrodes attached to the biceps brachii while the subjects were weighted with a load on the right wrist and maintained the right elbow on a desk.</p