Abstract-The real-time monitoring of human movement can provide valuable information regarding an individual's degree of functional ability and general level of activity. This paper presents the implementation of a real-time classification system for the types of human movement associated with the data acquired from a single, waist-mounted triaxial accelerometer unit. The major advance proposed by the system is to perform the vast majority of signal processing onboard the wearable unit using embedded intelligence. In this way, the system distinguishes between periods of activity and rest, recognizes the postural orientation of the wearer, detects events such as walking and falls, and provides an estimation of metabolic energy expenditure. A laboratory-based trial involving six subjects was undertaken, with results indicating an overall accuracy of 90.8% across a series of 12 tasks (283 tests) involving a variety of movements related to normal daily activities. Distinction between activity and rest was performed without error; recognition of postural orientation was carried out with 94.1% accuracy, classification of walking was achieved with less certainty (83.3% accuracy), and detection of possible falls was made with 95.6% accuracy. Results demonstrate the feasibility of implementing an accelerometry-based, real-time movement classifier using embedded intelligence.

Electrical stimulation of the spinal cord provides effective pain relief to hundreds of thousands of chronic neuropathic pain sufferers. The therapy involves implantation of an electrode array into the epidural space of the subject and then stimulation of the dorsal column with electrical pulses. The stimulation depolarises axons and generates propagating action potentials that interfere with the perception of pain. Despite the long-term clinical experience with spinal cord stimulation, the mechanism of action is not understood, and no direct evidence of the properties of neurons being stimulated has been presented. Here we report novel measurements of evoked compound action potentials from the spinal cords of patients undergoing stimulation for pain relief. The results reveal that Aβ sensory nerve fibres are recruited at therapeutic stimulation levels and the Aβ potential amplitude correlates with the degree of coverage of the painful area. Aβ-evoked responses are not measurable below a threshold stimulation level, and their amplitude increases with increasing stimulation current. At high currents, additional late responses are observed. Our results contribute towards efforts to define the mechanism of spinal cord stimulation. The minimally invasive recording technique we have developed provides data previously obtained only through microelectrode techniques in spinal cords of animals. Our observations also allow the development of systems that use neuronal recording in a feedback loop to control neurostimulation on a continuous basis and deliver more effective pain relief. This is one of numerous benefits that in vivo electrophysiological recording can bring to a broad range of neuromodulation therapies.

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Abstract:In a clinical setting it is necessary to control the speed of rotary blood pumps used as left ventricular assist devices to prevent possible severe complications associated with over-or underpumping. The hypothesis is that by using only the noninvasive measure of instantaneous pump impeller speed to assess flow dynamics, it is possible to detect physiologically significant pumping states (without the need for additional implantable sensors). By varying pump speed in an animal model, five such states were identified: regurgitant pump flow, ventricular ejection (VE), nonopening of the aortic valve over the cardiac cycle (ANO), and partial collapse (intermittent and continuous) of the ventricle wall (PVC-I and PVC-C). These states are described in detail and a strategy for their noninvasive detection has been developed and validated using (n = 6) ex vivo porcine experiments. Employing a classification and regression tree, the strategy was able to detect pumping states with a high degree of sensitivity and specificity: state VE-99.2/100.0% (sensitivity/specificity); state ANO-100.0/100.0%; state PVC-I-95.7/91.2%; state PVC-C-69.7/98.7%. With a simplified binary scheme differentiating suction (PVC-I, PVC-C) and nonsuction (VE, ANO) states, both such states were detected with 100% sensitivity. Current commercially used implantable rotary blood pumps (iRBPs) make little or no attempt to automatically control pump speed to optimize ventricular assistance. In order to achieve such a control strategy, a major design goal for iRBPs is the ability to reliably and accurately detect pumping states that cause such deleterious effects as ventricular collapse due to overpumping, or pump backflow (regurgitation) as a result of underpumping (1). Naturally, the ideal control set point is where left ventricular (LV) ejection is occurring and there is a net positive flow through both the aortic valve (AV) and the pump.A state that would be of long-term concern to a patient would occur at higher relative pump speeds when there is insufficient blood in the ventricle to sustain normal LV ejection and the AV remains closed throughout the entire cardiac cycle. In this instance there is no flow through the AV and the possibility of blood stasis distal to the AV, which could lead to significant patient complications due to clotting. However, it has been recognized (2,3) that the aim of ensuring AV opening is often infeasible in patients with LV failure. The lack of native heart contractility in such patients means that in order to attain a level of pump flow which adequately perfuses the body, a pump speed which produces the state of full AV closure is often required. Even higher speeds would result in partial or total ventricular collapse as the volume of blood drawn from the ventricle chamber is increased to a level at which pulmonary supply cannot meet pump demand. Deleterious outcomes could also occur at lower relative pump speeds where there is regurgitant flow through the pump.Experimentation in the transition of pumping stat...

Abstract:The effect of blood hematocrit (HCT) on a noninvasive flow estimation algorithm was examined in a centrifugal implantable rotary blood pump (iRBP) used for ventricular assistance. An average flow estimator, based on three parameters, input electrical power, pump speed, and HCT, was developed. Data were collected in a mock loop under steady flow conditions for a variety of pump operating points and for various HCT levels. Analysis was performed using three-dimensional polynomial surfaces to fit the collected data for each different HCT level. The polynomial coefficients of the surfaces were then analyzed as a function of HCT. Linear correlations between estimated and measured pump flow over a flow range from 1.0 to 7.5 L/min resulted in a slope of 1.024 L/min (R 2 = 0.9805). Early patient data tested against the estimator have shown promising consistency, suggesting that consideration of HCT can improve the accuracy of existing flow estimation algorithms. Key Words: Implantable rotary blood pump-Noninvasive flow estimation-Control strategyLeft ventricular assist device-Hematocrit-Rotary blood pump.