In this study, a simple mathematical-statistical based metric called Multiple Higher Order Moments (MHOM) is introduced enabling the electrocardiogram (ECG) detection-delineation algorithm to yield acceptable results in the cases of ambulatory holter ECG including strong noise, motion artifacts, and severe arrhythmia(s). In the MHOM measure, important geometric characteristics such as maximum value to minimum value ratio, area, extent of smoothness or being impulsive and distribution skewness degree (asymmetry), occult. In the proposed method, first three leads of high resolution 24-h holter data are extracted and preprocessed using Discrete Wavelet Transform (DWT). Next, a sample to sample sliding window is applied to preprocessed sequence and in each slid, mean value, variance, skewness, and kurtosis of the excerpted segment are superimposed called MHOM. The MHOM metric is then used as decision statistic to detect and delineate ECG events. To show advantages of the presented method, it is applied to MIT-BIH Arrhythmia Database, QT Database, and T-Wave Alternans Database and as a result, the average values of sensitivity and positive predictivity Se = 99.95% and P+ = 99.94% are obtained for the detection of QRS complexes, with the average maximum delineation error of 6.1, 4.1, and 6.5 ms for P-wave, QRS complex, and T-wave, respectively showing marginal improvement of detectiondelineation performance. In the next step, the proposed method is applied to DAY hospital high resolution holter data (more than 1,500,000 beats including Bundle Branch Blocks-BBB, Premature Ventricular Complex-PVC, and Premature Atrial Complex-PAC) and average values of Se = 99.97% and P+ = 99.95% are obtained for QRS detection. In summary, marginal performance improvement of ECG events detection-delineation process, reliable robustness against strong noise, artifacts, and probable severe arrhythmia(s) of high resolution holter data can be mentioned as important merits and capabilities of the proposed algorithm.
With the extensive application of air-conditioning/refrigeration (A/C-R) systems in homes, industry, and vehicles, many efforts have been put toward the controller development for A/C-R systems. Therefore, this paper proposes an energy-saving model predictive controller (MPC) via a comparative study of several control approaches that could be applied in automotive A/C-R systems. The on/off controller is first presented and used as a basis to compare with others. The conventional proportional-integral (PI) as well as a set-point controller follows. In the set-point controller, the sliding mode control (SMC) strategies are also employed. Then, the MPC is elaborated upon. Finally, the simulation and experimental results under the same scenario are compared to demonstrate how the advanced MPC can bring more benefits in terms of performance and energy saving (10%) over the conventional controllers.
ObjectiveThe Development of a Novel Mixed Reality (MR) Simulation.An evolving training environment emphasizes the importance of simulation. Current haptic temporal bone simulators have difficulty representing realistic contact forces and while 3D printed models convincingly represent vibrational properties of bone, they cannot reproduce soft tissue. This paper introduces a mixed reality model, where the effective elements of both simulations are combined; haptic rendering of soft tissue directly interacts with a printed bone model.This paper addresses one aspect in a series of challenges, specifically the mechanical merger of a haptic device with an otic drill. This further necessitates gravity cancelation of the work assembly gripper mechanism. In this system, the haptic end-effector is replaced by a high-speed drill and the virtual contact forces need to be repositioned to the drill tip from the mid wand.Previous publications detail generation of both the requisite printed and haptic simulations.MethodCustom software was developed to reposition the haptic interaction point to the drill tip. A custom fitting, to hold the otic drill, was developed and its weight was offset using the haptic device. The robustness of the system to disturbances and its stable performance during drilling were tested. The experiments were performed on a mixed reality model consisting of two drillable rapid-prototyped layers separated by a free-space. Within the free-space, a linear virtual force model is applied to simulate drill contact with soft tissue.ResultsTesting illustrated the effectiveness of gravity cancellation. Additionally, the system exhibited excellent performance given random inputs and during the drill’s passage between real and virtual components of the model. No issues with registration at model boundaries were encountered.ConclusionThese tests provide a proof of concept for the initial stages in the development of a novel mixed-reality temporal bone simulator.
Vehicles are a major source of fuel consumption and air pollution. Any improvement in their efficiency impacts the environment and economy positively. Service vehicles such as food delivery trucks have many loading and unloading stops during their daily work cycle. In these stops, their auxiliary devices need to be active and hence the engines run at its idling speed resulting in extremely low fuel efficiency. A regenerative auxiliary power system is proposed for anti-idling of service vehicles. This system reduces the engine idling and maximizes the regenerative braking energy by utilizing an additional battery. In this paper, different system configurations and possible options for integration of regenerative auxiliary power system to the vehicle powertrain are studied. Backward-looking scalable powertrain components modeling approach is utilized to create a flexible system model which can be easily modified for different vehicles. The full system model has scalability and composability features. A library for common components used in service vehicles is developed for ease of development of such anti-idling systems. Hardware-in-the-loop tests and a prototype model of regenerative auxiliary power system have been utilized for the laboratory evaluation in order to validate the model and characterize the regenerative auxiliary power system components.
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