Objectives: This study sought to investigate the temporal association between changes in physiologic heart failure (HF) sensors, atrial fibrillation (AF) progression, and clinical HF in patients with cardiac resynchronization therapy implantable defibrillators (CRT-D) designed to monitor AF and HF daily.
Background: AF is a common comorbidity in HF; however, it is unclear if HF triggers AF, or vice-versa. Current implantable cardiac devices have sensors capable of quantifying HF status, which permits a greater understanding of the impact of AF on HF status and may help guide treatment.
Background: We compared the relationship between the third heart sound (S3) measured by an implantable cardiac device (devS3) and auscultation (ausS3) and evaluated their prognostic powers for predicting heart failure events (HFEs).
Methods And Results: In the MultiSENSE study, devS3 was measured daily with continuous values, whereas ausS3 was assessed at study visits with discrete grades. They were compared among patients with and without HFEs at baseline and against each other directly.
Background: Care of heart failure (HF) patients results in a high burden on healthcare resources, and estimating prognosis is becoming increasingly important to triage resources wisely. Natriuretic peptides are recommended prognosticators in chronic HF. Our objective was to evaluate whether a multisensor HF index and alert algorithm (HeartLogic) replaces or augments current HF risk stratification.
View Article and Find Full Text PDFAim: The aim of this study was to evaluate the haemodynamic correlates of heart sound (HS) parameters such as third HS (S3), first HS (S1), and HS-based systolic time intervals (HSTIs) from an implantable cardiac device.
Methods And Results: Two unique animal models (10 swine with myocardial ischaemia and 11 canines with pulmonary oedema) were used to evaluate haemodynamic correlates of S1, S3, and HSTIs, namely, HS-based pre-ejection period (HSPEP), HS-based ejection time (HSET), and the ratio HSPEP/HSET during acute haemodynamic perturbations. The HS was measured using implanted cardiac resynchronization therapy defibrillator devices simultaneously with haemodynamic references such as left atrial (LA) pressure and left ventricular (LV) pressure.
Objectives: The aim of this study was to develop and validate a device-based diagnostic algorithm to predict heart failure (HF) events.
Background: HF involves costly hospitalizations with adverse impact on patient outcomes. The authors hypothesized that an algorithm combining a diverse set of implanted device-based sensors chosen to target HF pathophysiology could detect worsening HF.
The tactile perception of the shape of objects critically guides our ability to interact with them. In this review, we describe how shape information is processed as it ascends the somatosensory neuraxis of primates. At the somatosensory periphery, spatial form is represented in the spatial patterns of activation evoked across populations of mechanoreceptive afferents.
View Article and Find Full Text PDFThe classical view of somatosensory processing holds that proprioceptive and cutaneous inputs are conveyed to cortex through segregated channels, initially synapsing in modality-specific areas 3a (proprioception) and 3b (cutaneous) of primary somatosensory cortex (SI). These areas relay their signals to areas 1 and 2 where multimodal convergence first emerges. However, proprioceptive and cutaneous maps have traditionally been characterized using unreliable stimulation tools.
View Article and Find Full Text PDFObjective: The feasibility of detecting heart sounds (HS) from an accelerometer sensor enclosed within an implantable cardioverter defibrillator (ICD) pulse generator (PG) was explored in a noninvasive pilot study on heart failure (HF) patients with audible third HS (S3).
Methods: Accelerometer circuitry enhanced for HS was incorporated into non-functional ICDs. A study was conducted on 30 HF patients and 10 normal subjects without history of cardiac disease.
Linear receptive field (RF) models of area 3b neurons reveal a three-component structure: a central excitatory region flanked by two inhibitory regions that are spatially and temporally nonoverlapping with the excitation. Previous studies also report that there is an "infield" inhibitory region throughout the neuronal RF, which is a nonlinear interactive (second order) effect whereby stimuli lagging an input to the excitatory region are suppressed. Thus linear models may be inaccurate approximations of the neurons' true RFs.
View Article and Find Full Text PDFAlthough the human hand has a complex structure with many individual degrees of freedom, joint movements are correlated. Studies involving simple tasks (grasping) or skilled tasks (typing or finger spelling) have shown that a small number of combined joint motions (i.e.
View Article and Find Full Text PDFDetermination of single unit spikes from multiunit spike trains plays a critical role in neurophysiological coding studies which require information about the precise timing of events underlying the neural codes that are the basis of behavior. Searching for optimal spike detection strategies has therefore been the focus of many studies over the past two decades. In this study we describe and implement an algorithm for the optimal real time detection and classification of neural spikes.
View Article and Find Full Text PDFSpike sorting of neural data from single electrode recordings is a hard problem in machine learning that relies on significant input by human experts. We approach the task of learning to detect and classify spike waveforms in additive noise using two stages of large margin kernel classification and probability regression. Controlled numerical experiments using spike and noise data extracted from neural recordings indicate significant improvements in detection and classification accuracy over linear amplitude- and template-based spike sorting techniques.
View Article and Find Full Text PDFWe investigate the position invariant receptive field properties of neurons in the macaque second somatosensory (SII) cortical region. Previously we reported that many SII region neurons show orientation tuning in the center of multiple finger pads of the hand and further that the tuning is similar on different pads, which can be interpreted as position invariance. Here we study the receptive field properties of a single finger pad for a subset (n = 61) of those 928 neurons, using a motorized oriented bar that we positioned at multiple locations across the pad.
View Article and Find Full Text PDFThe detailed structure of multidigit receptive fields (RFs) in somatosensory cortical areas such as the SII region has not been investigated previously using systematically controlled stimuli. Recently (Fitzgerald et al., 2004), we showed that the SII region comprises three adjoining fields: posterior, central, and anterior.
View Article and Find Full Text PDFOrientation tuning has been studied extensively in the visual system, but little is known about it in the somatosensory system. Here we investigate tuning in the second somatosensory (SII) region using a motorized stimulator that presented a small oriented bar to the 12 finger pads of digits 2-5 (D2-D5) of the macaque monkey. A subset (23%; n = 218) of the 928 SII region neurons [the same 928 neurons studied by Fitzgerald et al.
View Article and Find Full Text PDFThe detailed functional organization of the macaque second somatosensory cortex (SII) is not well understood. Here we report the results of a study of the functional organization of the SII hand region that combines microelectrode mapping using hand-held stimuli with single-unit recordings using a motorized, computer-controlled tactile oriented bar. The data indicate that the SII hand region extends approximately 10 mm in the anteroposterior (AP) dimension, primarily within the upper bank of the lateral sulcus.
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