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[IEEE ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Calgary, AB (2018.4.15-2018.4.20)] 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Robust Beat-To-Beat Detection Algorithm for Pulse Rate Variability Analysis from Wrist Photoplethysmography Signals
摘要： Heart rate variability (HRV) from electrocardiograms (ECG) is a well-known diagnostic method for the assessment of autonomic nervous function of the heart. A more convenient approach to assess cardiac function is by using Photoplethysmography (PPG) waveforms where pulse rate variability (PRV) replaces HRV. However, the unavailability of robust detection algorithms for PPG signals has prevented the medical market from providing clinical diagnosis using PRV and from measuring biological information for wellness purposes, such as sleep stage, stress state, and fatigue. This paper provides a robust peak and onset detection algorithm for beat-to-beat (B2B) pulse interval analysis using PPG signals. We demonstrate our method through large data collection with the Analog Devices (ADI) multi-sensory watch platform with high coverage, sensitivity, and low Root Mean Square of Successive Difference (RMSSD) as compared to the B2B results from ECG signals.
关键词： Delineation,Pulse Rate Variability (PRV),Heart Rate Variability,Beat-to-Beat,Photoplethysmography (PPG)
更新于2025-09-10 09:29:36
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[IEEE 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Honolulu, HI, USA (2018.7.18-2018.7.21)] 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Reliability of Short-Term Heart Rate Variability Indexes Assessed through Photoplethysmography
摘要： The gold standard method to monitor heart rate variability (HRV) comprises measuring the time series of interbeat interval durations from electrocardiographic (ECG) recordings. However, due to the widespread use, simplicity and usability of photoplethysmographic (PPG) techniques, monitoring pulse rate variability (PRV) from pulse wave recordings has become a viable alternative to standard HRV analysis. The present study investigates the accuracy of PRV, measured as a surrogate of HRV, for the quantification of descriptive indexes computed in the time domain (mean, variance), frequency domain (low-to-high frequency power ratio LF/HF, HF band central frequency) and information domain (entropy, conditional entropy). We analyze short time series (300 intervals) of HRV measured from the ECG and of PRV acquired from Finometer device in 76 subjects monitored in the resting supine position (SU) and in the upright position during head-up tilt (HUT). Time, frequency and information domain indexes are computed for each HRV and PRV series and, for each index, the comparison between the two approaches is performed through statistical comparison of the distributions across subjects, robust linear regression, and Bland-Altman plots. Results of the comparison indicate an overall good agreement between PRV-based and HRV-based indexes, with an accuracy that is slightly lower during HUT than during SU, and for the band-power ratio and conditional entropy. These results suggest the feasibility of PRV-based assessment of HRV descriptive indexes, and suggest to further investigate the agreement in conditions of physiological stress.
关键词： information domain,photoplethysmography,time domain,pulse rate variability,frequency domain,heart rate variability
更新于2025-09-10 09:29:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Relative Attribute Based Unmixing
摘要： The abundance of a mixed pixel of certain class can be understood as to get the relative score referring to the pure representative of this class, while not be classified with two absolute and discrete value as “1 or 0”. This is in accordance with the Relative Attribute Learning (RAL) problem in computer vision. In RAL, the concept of “relative attribute” is used to describe the belonging level of an object to certain class with a score which is achieved from a learn-to-rank problem using rankSVM framework. To utilize information between data samples and even of mixed pixels, Relative Attribute based Unmixing (RAU) is proposed first time by using relative attribute to describe the abundance of mixed pixel as relative purity of certain class and learn the abundance with rankSVM. The mixed data sample are used to construct training comparisons set in rankSVM with archetypes generated by the reported Kernel Archetypal Analysis (KAA) unmixing method. In addition, spectral variability is also addressed by constructing comparisons set with synonyms spectrum achieved from KAA. Experiments on both synthetic and real hyperspectral mixed image have demonstrated the potential value of proposed method for mixed pixel analysis.
关键词： relative attribute,spectral unmixing,Hyperspectral image,NMF,spectral variability
更新于2025-09-10 09:29:36
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[IEEE 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) - Boise, ID, USA (2018.6.24-2018.6.28)] 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) - Understanding Inter-Annual Variability of PV Energy Production in the Contiguous United States
摘要： Year-to-year variability of photovoltaic (PV) generation is an important factor for project financing as well as for modeling the reliability and resource adequacy of power systems. In this work, we analyze inter-annual variability of PV generation across the contiguous United States using the National Solar Radiation Database (NSRDB) from 1998 to 2014. We compare typical meteorological year (TMY) against the long-term mean, and find that on average the TMY tends to overpredict estimated PV production. However, we also found significant regional bias and spatial clustering in that comparison, such that there are many regional pockets of underprediction as well. Finally, we show that there is not a single year of data that most closely approximates a representative “resource year” for all regions of the United States. These results point to the need to understand inter-annual variability at individual sites and to be aware of the shortcomings of using TMY or a single year of data for project or grid modeling.
关键词： Capacity Value,National Solar Radiation Database,PV,Probability Exceedance,Long-term Variability
更新于2025-09-10 09:29:36
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Glaucoma Increases Retinal Surface Contour Variability as Measured by Optical Coherence Tomography
摘要： We investigated the feasibility of glaucoma detection by measuring retinal surface contour variability (RSCV) using optical coherence tomography (OCT). The peripapillary region in one eye of each participant was scanned over an 8 3 8 mm area with a swept source OCT prototype. The retinal surface contour was sampled at approximately 1.5- to 3.5-mm radius circles centered on the optic nerve head. The RSCV is defined as the average log value within a middle spatial frequency band of the Fourier transform to the elevation profile of the inner retinal surface. The spatial frequency band was optimized to distinguish glaucoma from normal. Nerve fiber layer thickness (NFLT) was sampled around a 1.7-mm radius circle. Glaucoma severity was assessed by automated static perimetry. We enrolled 17 glaucomatous eyes and 17 healthy eyes. A great majority of the glaucoma group were in the early stage (visual field mean deviation average (cid:2)2.48 6 3.73 dB). Significant differences were found for RSCV between glaucoma and control eyes (P < 0.003) at all radii. The area under the receiver operating characteristic curve (AROC ? 0.90) of RSCV was best at the 3.5-mm radius. This was not significantly better than NFLT (AROC ? 0.84). With the 99% specificity, the glaucoma detection sensitivity was 53% for RSCV and 29% for NFLT (P ? 0.13). Retinal surface contour variability was significantly increased in glaucoma patients. The diagnostic accuracy of RSCV was equal to NFLT in early glaucoma. Since the RSCV detects small-scale focal damage and the average NFLT measures global damage, they provide different diagnostic information that may be synergistic.
关键词： optical coherence tomography,glaucoma,nerve fiber layer,retinal surface contour variability
更新于2025-09-10 09:29:36
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Diel variability of vertical distributions of chlorophyll a at the SEATS and ALOHA stations: implications on remote sensing interpretations
摘要： The effects of the diel (involving a 24 hour period) variations in the surface concentrations of chlorophyll a (C) on the use of once-daily remotely sensed C as the diel average were assessed from the diel records in the derived depth-weighted C (Cd) that should be detected by remote sensing and the in situ surface C at two time-series stations in the North Pacific: the SEATS (SouthEast Asian Time-series Study) station in the northern South China Sea and the ALOHA (A Long-Term Oligotrophic Habitat Assessment) station in the North Pacific subtropical gyre. In situ surface C varied by a factor of about 2.0 and 1.3 over a diel cycle, and by ±20% and ±9% over the diel average at the SEATS and ALOHA stations, respectively. As the overpass-times of the different satellites were not identical, Cd was satellite-dependent. While the Cd corresponding to MODerate resolution Imaging Spectroradiometer on Aqua (MODIS-Aqua) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) overpass-times agreed to ±10%, the Cd corresponding to MEdium Resolution Imaging Spectrometer (MERIS) overpass-time could differ from the other two by ?22% to +28% at the SEATS station and ?1% to +12% at the ALOHA station. In addition, Cd corresponding to the overpass-times of the three satellites deviated from the observed diel average in situ surface C by ?19% to +32% at the SEATS station and by ?6% to +13% at the ALOHA station. These results indicate that, as a result of diel variations, neither a one-time remotely-sensed nor a one-time observed in situ surface C can represent the diel average in situ surface C accurately. Furthermore, diel variations are an inherent source of uncertainty when data from multiple satellites are pooled for use. The magnitudes of these discrepancies can be comparable to the commonly claimed uncertainties in remotely sensed C and thus should be taken into consideration in its interpretation and use.
关键词： remote sensing,diel variability,chlorophyll a,ALOHA station,SEATS station
更新于2025-09-10 09:29:36
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Variance Analysis in 3-D Integration: A Statistically Unified Model With Distance Correlations
摘要： Variability is a challenge for future scaling as process dimensions reduce. The emerging 3-D sequential stacking technology is more than Moore’s scaling alternative. The 3-D design ?ow requires the partitioning of the netlist between the tiers. This paper presents the variability analysis of circuits partitioned into different levels. A comparison among local and global variations effects on ring oscillators (ROs) and SRAM is demonstrated. The across-chip variations and correlation range are shown as a critical point for the 3-D very large-scale integrated circuits, where the local variability is dominant. The correlations between devices due to the distances or the allocation into different tiers are directly taken into account in the SPICE model due to a statically uni?ed model applied to 3-D circuits based on Monte Carlo simulations. Design wise, the 3-D integration can further decrease the circuit variability as shown in RO output frequency and SRAM static noise margin.
关键词： across-chip variations (ACVs),variability,3-D very large-scale integration (VLSI),SRAM,noise margins,Monte Carlo (MC),3-D integration
更新于2025-09-10 09:29:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Extended Linear Mixing Model in an Ecosytem with High Spectral Variability
摘要： Hyperspectral imagery (HSI) has become an important tool in ecosystem conservation due to its capability to perform accurate spectral unmixing, for vegetation mapping and ecosystem monitoring. An issue to be solved is the spectral variability of endmembers that can be induced by sensor noise and topographic changes. This spectral variability is considered by the Extended Linear Mixing Model (ELMM), which is applied to a mountainous ecosystem with high spectral variability and radiometric changes in each swath. The results obtained are very satisfactory, achieving reasonable abundance estimations and accurate characterization of the variability within the scene. ELMM allows studying the features of each pixel, including additional information about the characterization of the mixed pixels, in HSI by taking spectral variability into account. Moreover, it is observed that ELMM is robust to the absence of pure pixels as well as to noise.
关键词： ecosystem management,spectral unmixing,Hyperspectral imagery,spectral variability
更新于2025-09-09 09:28:46
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[ASME ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Quebec City, Quebec, Canada (Sunday 26 August 2018)] Volume 2A: 44th Design Automation Conference - Design Exploration of Reliably Manufacturable Materials and Structures With Applications to a Microstereolithography System
摘要： One of the challenges in designing for additive manufacturing (AM) is accounting for the differences between as-designed and as-built geometries and material properties. From a designer’s perspective, these differences can lead to degradation of part performance, which is especially difficult to accommodate in small-lot or one-of-a-kind production. In this context, each part is unique, and therefore, extensive iteration is costly. Designers need a means of exploring the design space while simultaneously considering the reliability of additively manufacturing particular candidate designs. In this work, a design exploration approach, based on Bayesian network classifiers (BNC), is extended to incorporate manufacturability explicitly into the design exploration process. The example application is the design of negative stiffness (NS) metamaterials, in which small volume fractions of negative stiffness (NS) inclusions are embedded within a host material. The resulting metamaterial or composite exhibits macroscopic mechanical stiffness and loss properties that exceed those of the base matrix material. The inclusions are fabricated with microstereolithography with features on the scale of tens of microns, but variability is observed in material properties and dimensions from specimen to specimen. In this work, the manufacturing variability of critical features of a NS inclusion fabricated via microstereolithography are characterized experimentally and modelled mathematically. Specifically, the variation in the geometry of the NS inclusions and the Young’s modulus of the photopolymer are measured and modeled by both nonparametric and parametric joint probability distributions. Finally, the quantified manufacturing variability is incorporated into the BNC approach as a manufacturability classifier to identify candidate designs that achieve performance targets reliably, even when manufacturing variability is taken into account.
关键词： negative stiffness metamaterials,Bayesian network classifiers,additive manufacturing,microstereolithography,manufacturing variability
更新于2025-09-09 09:28:46
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[American Society of Agricultural and Biological Engineers 2018 Detroit, Michigan July 29 - August 1, 2018 - ()] 2018 Detroit, Michigan July 29 - August 1, 2018 - <i>The Assessment of Accuracy and Stability for a UAS Sensor Platform as a Precision Agriculture Management Tool in Detecting and Mapping Geospatial Field Variability</i>
摘要： The unmanned aerial system (UAS), that is used as a precision agricultural management tool for detecting and mapping geospatial variability in the crop health of the agricultural row field, is dependent on global positioning system (GPS) receivers and remote sensor (RS) systems. Unlike a ground platform, the UAS is subject to additional platform factors such as autonomous flight system, inertial navigational system (INS), aerodynamics, and aerial climate conditions which can affect flight path accuracy and stability. Such factors can result in diminished quality of trajectory accuracy or aerial Nadir stability that is needed for the precision mapping of geospatial variability zones that are used in the management decisions for geospatial input of treatments. The diminished quality of the UAS flight path can in turn cause RS image-stitching distortions that will render a precision treatment zone map geospatially insufficient. Using the scientific method, this project proposes bringing geospatial assessment tools to the agricultural field that serve to independently verify the flight path accuracy and stability aspects of any UAS sensor platform apart from sole reliance on ortho-stitching processing or sole reliance on on-board platform systems. In a field, a set pattern of elevation posts with global navigational satellite system (GNSS) obtained coordinates will be erected to be viewed from the Nadir orientation of any UAS. With any UAS autonomous platform equipped for optically tracking geospatial flight path metrics, the UAS flight path will follow the posted field pattern at various altitudes. The expected result will be a repeatable testing regimen that will be suitable in standardizing the assessment of any UAS sensor platform for flight path stability and accuracy where precision mapping and true global accuracy are needed such as in the management decisions for the geospatial input of treatments.
关键词： sensor platform,timeliness,unmanned aerial system (UAS),Accuracy,Nadir view stability,testing regimen,geospatial variability (GSV),site specific management (SSM)
更新于2025-09-09 09:28:46