Deep Learning Algorithms to Detect Murmurs Associated With Structural Heart Disease.

Background The success of cardiac auscultation varies widely among medical professionals, which can lead to missed treatments for structural heart disease. Applying machine learning to cardiac auscultation could address this problem, but despite recent interest, few algorithms have been brought to clinical practice. We evaluated a novel suite of Food and Drug Administration-cleared algorithms trained via deep learning on >15 000 heart sound recordings.

Automated detection of low ejection fraction from a one-lead electrocardiogram: application of an AI algorithm to an electrocardiogram-enabled Digital Stethoscope.

Aims: Electrocardiogram (ECG)-enabled stethoscope (ECG-Scope) acquires a single-lead ECGs during cardiac auscultation and may facilitate real-time screening for pathologies not routinely identified by cardiac auscultation alone. We previously demonstrated an artificial intelligence (AI) algorithm can identify left ventricular dysfunction (LVSD) [defined as ejection fraction (EF) ≤ 40%] with an area under the curve (AUC) of 0.91 using a 12-lead ECG.

Deep Learning Algorithm for Automated Cardiac Murmur Detection via a Digital Stethoscope Platform.

Background Clinicians vary markedly in their ability to detect murmurs during cardiac auscultation and identify the underlying pathological features. Deep learning approaches have shown promise in medicine by transforming collected data into clinically significant information. The objective of this research is to assess the performance of a deep learning algorithm to detect murmurs and clinically significant valvular heart disease using recordings from a commercial digital stethoscope platform.

Dependence of brown adipose tissue function on CD36-mediated coenzyme Q uptake.

Brown adipose tissue (BAT) possesses the inherent ability to dissipate metabolic energy as heat through uncoupled mitochondrial respiration. An essential component of the mitochondrial electron transport chain is coenzyme Q (CoQ). While cells synthesize CoQ mostly endogenously, exogenous supplementation with CoQ has been successful as a therapy for patients with CoQ deficiency.

Active sensing of target location encoded by cortical microstimulation.

Cortical microstimulation has been proposed as a method to deliver sensory percepts to circumvent damaged sensory receptors or pathways. However, much of perception involves the active movement of sensory organs and the integration of information across sensory and motor modalities. The efficacy of cortical microstimulation in such an active sensing paradigm has not been demonstrated.

In vitro and in vivo evaluation of PEDOT microelectrodes for neural stimulation and recording.

Cortical neural prostheses require chronically implanted small-area microelectrode arrays that simultaneously record and stimulate neural activity. It is necessary to develop new materials with low interface impedance and large charge transfer capacity for this application and we explore the use of conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) for the same. We subjected PEDOT coated electrodes to voltage cycling between -0.

Decoder remapping to counteract neuron loss in brain-machine interfaces.

Variability of single-unit neural recordings can significantly affect the overall performance achieved by brain machine interfaces (BMI). In this paper, we present a novel technique to adapt a linear filter commonly used in BMI to compensate for loss of neurons from the recorded neural ensemble, thus minimizing loss in performance. We simulate the gains achieved by this technique using a model of the learning process during closed-loop BMI operation.

Wireless channel characterization for mm-size neural implants.

This paper discusses an approach to modeling and characterizing wireless channel properties for mm-size neural implants. Full-wave electromagnetic simulation was employed to model signal propagation characteristics in biological materials. Animal tests were carried out, proving the validity of the simulation model over a wide range of frequency from 100MHz to 6GHz.

Investigating neural correlates of behavior in freely behaving rodents using inertial sensors.

Simultaneous behavior and multielectrode neural recordings in freely behaving rodents holds great promise to study the neural bases of behavior and disease models in combination with genetic manipulations. Here, we introduce the use of three-axis accelerometers to characterize the behavior of rats and mice during chronic neural recordings. These sensors were small and light enough to be worn by rodents and were used to record three-axis acceleration during freely moving behavior.

Exploiting the 1/f structure of neural signals for the design of integrated neural amplifiers.

Neural amplifiers require a large time-constant high-pass filter at approximately 1Hz to reject large DC offsets while amplifying low frequency neural signals. This high pass filter is typically realized using large area capacitors and teraohm resistances which makes integration difficult. In this paper, we present a novel topology for a neural amplifier which exploits the (1/f)(n) power spectra of local field potentials (LFP).

Behavioral modulation of stimulus-evoked oscillations in barrel cortex of alert rats.

Stimulus-evoked oscillations have been observed in the visual, auditory, olfactory and somatosensory systems. To further our understanding of these oscillations, it is essential to study their occurrence and behavioral modulation in alert, awake animals. Here we show that microstimulation in barrel cortex of alert rats evokes 15-18 Hz oscillations that are strongly modulated by motor behavior.

A system for neural recording and closed-loop intracortical microstimulation in awake rodents.

There is growing interest in intracortical microstimulation as a means of providing sensory input in neuroprosthetic systems. We believe that precisely controlling the timing and parameters of stimulation in closed loop can significantly improve the efficacy of this technique. Here, we present a system for closed-loop microstimulation in awake rodents chronically implanted with multielectrode arrays.

Wireless inertial sensors for monitoring animal behavior.

Wireless sensors were designed which are small and light enough to be worn by small animals such as rats. These sensors are used to record three axes acceleration data from animals during natural behavior in a cage. The behavior of the animal is further extracted from the recorded acceleration data using neural network based pattern recognition algorithms.