Mean Wavelength Research Articles

Enhancing gait recognition in lower limb exoskeletons: adaptive feature selection and random forest with Bayesian optimization

Abstract To improve human-machine cooperation and enhance the accuracy of gait recognition in wearable lower limb exoskeletons, an enhancement method of gait recognition based on adaptive feature selection and an optimized machine learning algorithm was proposed. In this study, surface electromyography (sEMG) signals of rectus femoris, medialis femoris, lateralis femoris, semitendinosus and biceps femoris were recorded during level-ground walking. Then, time domain, frequency domain, time-frequency domain and nonlinear features were extracted. The integrated value of electromyography, variance, root mean square and wavelength were selected as the time domain features, and the mean power frequency and median frequency were selected as the frequency domain features. Wavelet packet energy was selected as the time-frequency domain feature. Nonlinear features including approximate entropy, sample entropy and fuzzy entropy of sEMG were extracted. To reduce feature dimension and improve the calculation efficiency, adaptive feature selection was performed by particle swarm optimization combined with sigmoid function. Then, the feature matrix was determined as the input for a random forest classifier to recognize different gait phases. An adaptive optimization mechanism based on Bayesian optimization was applied to random forest. Compared with random forest, the overall performance of the optimized model was improved. Its accuracy was increased by 3.57%. The feature selection and adaptive optimization mechanisms in gait recognition not only enhance the accuracy of random forest algorithms applied to sEMG for gait prediction, but also facilitate the flexibility and consistency required for lower limb exoskeleton gait control.

Durability Investigation of Ultra-Thin Polyurethane Wearing Course for Asphalt Pavement

In this study, a wear-resistant ultra-thin wear layer was fabricated with polyurethane as an adhesive to investigate its durability for pavement applications. Its road performance was investigated based on indoor tests. First, the abrasion test was performed using a tire–pavement dynamic friction analyzer (TDFA), and the surface elevation information of the wear layer was obtained by laser profile scanning. The relationship between the anti-skid properties of the wear layer and the macro-texture was analyzed. Second, a Fourier infrared spectrometer and scanning electron microscope were employed to analyze the evolution of polyurethane aging properties in the pull-out test and accelerated ultraviolet (UV) aging test. The results showed that the mean profile depth (MPD), arithmetic mean wavelength of contour (λa), surface wear index (SBI), stage mass loss rate (σ), and total stage mass loss rate (ω) of the abrasive layer aggregate had significant multivariate quadratic polynomial relationships with the skidding performance of the abrasive layer. The tensile strength of the polyurethane ultra-thin abrasive layer decreased by only 2.59% after 16 days of UV aging, indicating a minimal effect of UV action on the aggregate and structural spalling of the polyurethane abrasive layer.

Unconventional acoustic wave propagation transitions induced by resonant scatterers in the high-density limit

Experiments on ultrasound propagation through a gel doped with resonant encapsulated microbubbles provided evidence for a discontinuous transition between wave propagation regimes at a critical excitation frequency. Such behavior is unlike that observed for soft materials doped with non-resonant air or through liquid foams, and disagrees with a simple mixture model for the effective sound speed. Here, we study the discontinuous transition by measuring the transition as a function of encapsulated microbubble volume fraction. The results show the transition always occurs in the strong-scattering limit (l/λ < 1, l and λ are the mean free path and wavelength, respectively), that at the critical frequency the effective phase velocity changes discontinuously to a constant value with increasing microbubble volume fraction, and the measured critical frequency shows a power law dependence on microbubble volume fraction. The results cannot be explained by multiple scattering theory, viscous effects, mode decoupling, or a critical density of states. It is hypothesized the transition depends upon the microbubble on-resonance effective properties, and we discuss the results within the context of percolation theory. The results shed light on the discontinuous transition’s physics, and suggest soft materials can be engineered in this manner to achieve a broad range of physical properties with potential application in ultrasonic actuators and switches.

Validation of the VUV-reflective coating for next-generation liquid xenon detectors

Coating detector materials with films highly reflective in the vacuum ultraviolet region improves sensitivity of the next-generation rare-event detectors that use liquid xenon. In this work, we investigate the MgF2-Al-MgF2 coating designed to achieve high reflectance at 175 nm, the mean wavelength of liquid xenon (LXe) scintillation. The coating was applied to an unpolished, passivated copper substrate mimicking a realistic detector component of the proposed nEXO experiment, as well as to two unpassivated substrates with “high” and “average” levels of polishing. After confirming the composition and morphology of the thin-film coating using TEM and EDS, the samples underwent reflectance measurements in LXe and gaseous nitrogen (GN2). Measurements in LXe exposed the coated samples to -100°C for several hours. No peeling of the coatings was observed after several thermal cycles. Polishing is found to strongly correlate with the measured specular reflectance (R spec). In particular, 5.8(5)% specular spike reflectance in LXe was measured for the realistic sample at 20° of incidence, while the values for similar angles of incidence on the high and average polish samples are 62.3(1.3)% and 27.4(7)%, respectively. At large angles (66°–75°), the R spec in LXe for the three samples increases to 23(5)%, 80(8)%, and 84(18)%, respectively. The R spec at around 45° was measured in both GN2 and LXe for average polish sample and shows a reasonable agreement. Importantly, the total reflectance of the samples is comparable and estimated to be 92(8)%, 85(8)%, and 83(8)% in GN2 for the realistic, average, and high polish samples, respectively. This is considered satisfactory for the next-generation LXe experiments that could benefit from using reflective films, such as nEXO and DARWIN, thus validating the design of the coating.

Towards the understanding of convective dissolution in confined porous media: thin bead pack experiments, two-dimensional direct numerical simulations and physical models

We consider the process of convective dissolution in a homogeneous and isotropic porous medium. The flow is unstable due to the presence of a solute that induces a density difference responsible for driving the flow. The mixing dynamics is thus driven by a Rayleigh–Taylor instability at the pore scale. We investigate the flow at the scale of the pores using Hele-Shaw type experiment with bead packs, two-dimensional direct numerical simulations and physical models. Experiments and simulations have been specifically designed to mimic the same flow conditions, namely matching porosities, high Schmidt numbers and linear dependency of fluid density with solute concentration. In addition, the solid obstacles of the medium are impermeable to fluid and solute. We characterise the evolution of the flow via the mixing length, which quantifies the extension of the mixing region and grows linearly in time. The flow structure, analysed via the centreline mean wavelength, is observed to grow in agreement with theoretical predictions. Finally, we analyse the dissolution dynamics of the system, quantified through the mean scalar dissipation, and three mixing regimes are observed. Initially, the evolution is controlled by diffusion, which produces solute mixing across the initial horizontal interface. Then, when the interfacial diffusive layer is sufficiently thick, it becomes unstable, forming finger-like structures and driving the system into a convection-dominated phase. Finally, when the fingers have grown sufficiently to touch the horizontal boundaries of the domain, the mixing reduces dramatically due to the absence of fresh unmixed fluid. With the aid of simple physical models, we explain the physics of the results obtained numerically and experimentally. The solute evolution presents a self-similar behaviour, and it is controlled by different length scales in each stage of the mixing process, namely the length scale of diffusion, the pore size and the domain height.

Adaptive Random Forest for Gait Prediction in Lower Limb Exoskeleton

To improve the human-machine cooperativity of a wearable lower limb exoskeleton, a gait recognition method based on surface electromyography (sEMG) was proposed. sEMG of rectus femoris, vastus medialis, vastus lateralis, semitendinosus and biceps femoris were acquired. Then, time domain, frequency domain, time-frequency domain and nonlinear features were extracted. The integrated value of electromyography, variance, root mean square and wavelength were selected as the time domain features and the frequency domain feature includes mean power frequency. Wavelet packet energy was selected as the time-frequency domain feature. Nonlinear features including approximate entropy, sample entropy and fuzzy entropy of sEMG were extracted. Classification accuracy of different feature matrices and different muscle groups were constructed and verified. The optimal multi-dimensional fusion feature matrix was determined. Introducing the Bayesian optimization algorithm, the Bayesian optimized Random Forest classification model was constructed to identify different gait phases. Comparing with Random Forest, the accuracy of the optimized Random Forest was improved by 5.89%. Applying Random Forest algorithm with Bayesian optimization to gait prediction based on sEMG, the followership and consistency of gait control in lower limb exoskeleton can be improved. This template explains and demonstrates how to prepare your camera-ready paper for Trans Tech Publications. The best is to read these instructions and follow the outline of this text.

Euclid preparation

The technique of photometric redshifts has become essential for the exploitation of multi-band extragalactic surveys. While the requirements on photometric redshifts for the study of galaxy evolution mostly pertain to the precision and to the fraction of outliers, the most stringent requirement in their use in cosmology is on the accuracy, with a level of bias at the sub-percent level for the Euclid cosmology mission. A separate, and challenging, calibration process is needed to control the bias at this level of accuracy. The bias in photometric redshifts has several distinct origins that may not always be easily overcome. We identify here one source of bias linked to the spatial or time variability of the passbands used to determine the photometric colours of galaxies. We first quantified the effect as observed on several well-known photometric cameras, and found in particular that, due to the properties of optical filters, the redshifts of off-axis sources are usually overestimated. We show using simple simulations that the detailed and complex changes in the shape can be mostly ignored and that it is sufficient to know the mean wavelength of the passbands of each photometric observation to correct almost exactly for this bias; the key point is that this mean wavelength is independent of the spectral energy distribution of the source. We use this property to propose a correction that can be computationally efficiently implemented in some photometric-redshift algorithms, in particular template-fitting. We verified that our algorithm, implemented in the new photometric-redshift code Phosphoros, can effectively reduce the bias in photometric redshifts on real data using the CFHTLS T007 survey, with an average measured bias Δz over the redshift range 0.4 ≤ z ≤ 0.7 decreasing by about 0.02, specifically from Δz ≃ 0.04 to Δz ≃ 0.02 around z = 0.5. Our algorithm is also able to produce corrected photometry for other applications.

Formation of Billowed Structures Along Margins of Basaltic Intrusions: Insights from Big Bend National Park, Texas and 71 Gulch, Idaho

Billowed margins of basaltic intrusions provide opportunity to study the conditions of non-explosive magma-pore water interactions and how magma propagates and interacts with unconsolidated sediment in the subsurface. Basaltic intrusions exhibiting billowed structures that formed at different paleodepths in Big Bend National Park, Texas (200–500 m) and 71 Gulch, Idaho (≤24 m) have been examined and reconstructed in three dimensions (3D) using structure for motion (SfM) techniques. To characterize billowed structure diversity, a classification system was developed utilizing 21 high-resolution 3D models of outcrops from both locations. Seven structure types are recognized: linear, sinuous, teardrop, bulbous, circular, transitional, and overprinted. Relative abundances of each structure type are similar between both localities. All structures identified were recognized along dikes, apart from one sill. Each site hosts ≥3 structure types, no one structure type is dependent on another, and the dimensions of structure types are similar at both localities with insignificant variation in mean wavelength and amplitude of crests and troughs (≤6 cm), suggesting that depth of intrusion is not a major influence in the occurrence of different structure types. Aligned plagioclase laths and stretched vesicles along margins are evidence that billow formation occurred while margins were fluid, deformable, and flowing. These observations indicate billowed structures likely form during the initial stages of intrusion while the margins are experiencing Kelvin-Helmholtz instabilities during cooling. As billowed intrusions from varying paleodepths at the two localities both occur near phreatomagmatic diatreme structures, changes in the rate or flux of magma intrusion or local heterogeneities in the host sediment and/or pore fluid content may be more responsible for explosive vs. non-explosive interactions rather than simple arrival of magma.

The BarYon Cycle project (ByCycle): identifying and localizing Mg ii metal absorbers with machine learning

ABSTRACT The upcoming ByCycle project on the VISTA/4MOST multi-object spectrograph will offer new prospects of using a massive sample of ∼1 million high spectral resolution (R = 20 000) background quasars to map the circumgalactic metal content of foreground galaxies (observed at R = 4000–7000), as traced by metal absorption. Such large surveys require specialized analysis methodologies. In the absence of early data, we instead produce synthetic 4MOST high-resolution fibre quasar spectra. To do so, we use the TNG50 cosmological magnetohydrodynamical simulation, combining photo-ionization post-processing and ray tracing, to capture Mg ii (λ2796, λ2803) absorbers. We then use this sample to train a convolutional neural network (CNN) which searches for, and estimates the redshift of, Mg ii absorbers within these spectra. For a test sample of quasar spectra with uniformly distributed properties ($\lambda _{\rm {Mg\, {\small II},2796}}$, $\rm {EW}_{\rm {Mg\, {\small II},2796}}^{\rm {rest}} = 0.05\!-\!5.15$ Å, $\rm {SNR} = 3\!-\!50$), the algorithm has a robust classification accuracy of 98.6 per cent and a mean wavelength accuracy of 6.9 Å. For high signal-to-noise (SNR) spectra ($\rm {SNR \gt 20}$), the algorithm robustly detects and localizes Mg ii absorbers down to equivalent widths of $\rm {EW}_{\rm {Mg\, {\small II},2796}}^{\rm {rest}} = 0.05$ Å. For the lowest SNR spectra ($\rm {SNR=3}$), the CNN reliably recovers and localizes EW$_{\rm {Mg\, {\small II},2796}}^{\rm {rest}}$ ≥0.75 Å absorbers. This is more than sufficient for subsequent Voigt profile fitting to characterize the detected Mg ii absorbers. We make the code publicly available through GitHub. Our work provides a proof-of-concept for future analyses of quasar spectra data sets numbering in the millions, soon to be delivered by the next generation of surveys.

On the Consistent Parametric Description of the Wave Age Dependence of the Sea Surface Roughness

Abstract The wind drag on the sea surface is characterized by the aerodynamic roughness of the sea surface, z0, which is regulated by surface wind waves. Many studies have related the dimensionless form of z0 to the wave age parameter estimated from spectral peak information. These parametric relationships have been well developed for the wind-driven sea but not for mixed seas. Based on an analysis using observations from a fixed platform in the northern South China Sea, the deficiency of the spectral peak information in the parametric description z0 when swells dominate is indicated. Instead, a consistent parametric description of z0 can be obtained by using the wave age estimated from the mean wave period, and normalizing z0 by the mean wavelength. Normalizing z0 by the significant wave height introduces a spurious residual dependence of z0 on the wave steepness. A parametric relationship is developed between the dimensionless z0 (normalized by the mean wavelength) and the wave age from the mean wave period. A comparison of this new relationship to the wind-speed-only formulation in COARE 3.5 is provided. Significance Statement In this paper, a consistent parametric description of the wave age dependence of the surface aerodynamic roughness is presented, with a wide range of sea states from dominant wind-driven seas to mixed seas in which the swells are dominant.

Discovery of a 760 nm P Cygni line in AT2017gfo: Identification of yttrium in the kilonova photosphere

Neutron star mergers are believed to be a major cosmological source of rapid neutron-capture elements. The kilonovae associated with neutron star mergers have to date yielded only a single well-identified spectral signature: the P Cygni line of Sr+ at about 1 μm in the spectra of the optical transient, AT2017gfo. Such P Cygni lines are important because they provide significant information not just potentially on the elemental composition of the merger ejecta, but also on the velocity, geometry, and abundance stratification of the explosion. In this paper, we show evidence for a previously unrecognised P Cygni line in the spectra of AT2017gfo that emerges several days after the explosion, located at λ ≈ 760 nm. We show that the feature is well-reproduced by 4d2–4d5p transitions of Y+, which have a weighted mean wavelength of around 760–770 nm, with the most prominent line at 788.19 nm. While the observed line is weaker than the Sr+ feature, the velocity stratification of the new line provides an independent constraint on the expansion rate of the ejecta, similar to the constraints from Sr+.

An Erbium-Doped Fiber Source with Near-Gaussian-Shaped Spectrum Based on Double-Stage Energy Matching and LPFGs

An Erbium-doped fiber source with a near-Gaussian-shaped spectrum consisting of only a single peak, based on the double-stage energy matching and LPFGs, is proposed and demonstrated. A double-stage Erbium-doped fiber source system is built. The first-stage structure adopts the single-pass forward pumping method with a 15 m Erbium-doped fiber, while the second-stage structure adopts the backward-pumping method with a 26.5 m Erbium-doped fiber. The energy of the output spectrum is concentrated near the long wavelength (1560 nm) through the double-pump energy matching of the two stages. Long period fiber gratings (LPFGs) are used to filter the excess light near the short wavelength (1530 nm) in order to obtain a near-Gaussian-shaped spectrum consisting of only a single peak. The output power, pump conversion efficiency, line width, 3 dB bandwidth and mean wavelength of this near-Gaussian-shaped spectrum are tested and analyzed. When the pump powers of the first and second stages are 50 mW and 360 mW, respectively, the results show that a near-Gaussian-shaped spectrum with a power of 10.17 mW, spectral line width of 19.767 nm, and mean wavelength stability of −0.978 ppm/mW can be obtained. This research provides a method for the generation of a near-Gaussian-shaped spectrum with high output power and excellent mean wavelength stability, and it can produce multiple forms and energies of near-Gaussian-shaped spectra via this Erbium-doped fiber source.

The Astrodust+PAH Model: A Unified Description of the Extinction, Emission, and Polarization from Dust in the Diffuse Interstellar Medium

We present a new model of interstellar dust in which large grains are a single composite material, “astrodust,” and nanoparticle-sized grains come in distinct varieties including polycyclic aromatic hydrocarbons (PAHs). We argue that a single-composition model for grains larger than ∼0.02 μm most naturally explains the lack of frequency dependence in the far-infrared (FIR) polarization fraction and the characteristic ratio of optical to FIR polarization. We derive a size distribution and alignment function for 1.4:1 oblate astrodust grains that, with PAHs, reproduce the mean wavelength dependence and polarization of Galactic extinction and emission from the diffuse interstellar medium while respecting constraints on solid-phase abundances. All model data and Python-based interfaces are made publicly available.

Snapshot multispectral imaging using a diffractive optical network

Multispectral imaging has been used for numerous applications in e.g., environmental monitoring, aerospace, defense, and biomedicine. Here, we present a diffractive optical network-based multispectral imaging system trained using deep learning to create a virtual spectral filter array at the output image field-of-view. This diffractive multispectral imager performs spatially-coherent imaging over a large spectrum, and at the same time, routes a pre-determined set of spectral channels onto an array of pixels at the output plane, converting a monochrome focal-plane array or image sensor into a multispectral imaging device without any spectral filters or image recovery algorithms. Furthermore, the spectral responsivity of this diffractive multispectral imager is not sensitive to input polarization states. Through numerical simulations, we present different diffractive network designs that achieve snapshot multispectral imaging with 4, 9 and 16 unique spectral bands within the visible spectrum, based on passive spatially-structured diffractive surfaces, with a compact design that axially spans ~72λm, where λm is the mean wavelength of the spectral band of interest. Moreover, we experimentally demonstrate a diffractive multispectral imager based on a 3D-printed diffractive network that creates at its output image plane a spatially repeating virtual spectral filter array with 2 × 2 = 4 unique bands at terahertz spectrum. Due to their compact form factor and computation-free, power-efficient and polarization-insensitive forward operation, diffractive multispectral imagers can be transformative for various imaging and sensing applications and be used at different parts of the electromagnetic spectrum where high-density and wide-area multispectral pixel arrays are not widely available.

Improvement of the Temperature Stability of the Erbium-Doped Superfluorescent Fiber Source by Tuning the Reflectivity of the Fiber End

A novel and simple way of improving the mean wavelength temperature stability of the erbium-doped superfluorescent source is described and demonstrated. We show that by introducing small reflectivity feedback at the unpumped fiber end in the backward-pump superfluorescent source configuration, we can affect an overall temperature dependency of the mean wavelength of the output spectrum. The reflectivity adjustment can be made by an angled fiber cleave, varying the reflectivity between 0 to 4 %, or by a fusion arc, allowing its finer adjustment. With this approach, we were able to arbitrarily adjust the mean wavelength temperature trend from −4.38 to 5.23 ppm/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> C. Furthermore, an optimal reflectivity was attained, providing almost zero trend and reducing the total mean wavelength variation to 130 ppm over the temperature range of −40 to +100 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> C, which is a 5.7-fold and 4.4-fold improvement compared to 0 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> and a standard 8 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> fiber cleave angle, respectively. By avoiding any filtering components, a wide bandwidth of 37.8 nm and a power efficiency of 22% was reached. Since the proposed configuration does not include any extra components compared to the basic backward-pump configuration, it can be a viable solution for cost-efficient applications, such as, e.g., medium-grade fiber-optic gyroscopes. A benefit for these gyroscopes is the tunability of the source wavelength temperature dependency which can conveniently compensate the gyro coil temperature sensitivity.

Measurement uncertainty of phase measuring deflectometry.

Phase measuring deflectometry (PMD) is a proven optical measurement method for measuring the shapes of objects. This method is suitable for measuring the shape of an object with an optically smooth (mirror-like) surface. The measured object is used as a mirror through which the camera observes a defined geometric pattern. We derive the theoretical limit of measurement uncertainty using the Cramér-Rao inequality. It shows that the measurement uncertainty is expressed in the form of an uncertainty product. The factors of the product are the angular uncertainty and lateral resolution. The magnitude of the uncertainty product depends on the mean wavelength of the light used and the number of photons detected. The calculated measurement uncertainty is compared with the measurement uncertainty of other deflectometry methods.

Wavelength selection for spectrally combined laser beams propagating in free space and the atmosphere

Wavelength selection has a major impact on spectral beam combining (SBC) of laser beams that propagate in free space and in the atmosphere. We derive analytical expressions for the intensity and four characteristic quality parameters of free-space SBC beams. We show that the peak intensity, the mean-square beam width, and the M 2 factor of an SBC beam at the target are all larger than those of one single laser beam of the same power and average wavelength. The peak intensity can be made higher by increasing the wavelength spacing but reducing the mean wavelength. However, when an SBC laser beam propagates in the atmosphere, the beam quality depends on the absorption coefficient of the multi-wavelength field due to thermal blooming. A thermal distortion number is introduced for an SBC beam and its validity is confirmed. We show that the power proportion of a high-absorption element within an SBC beam should be as low as possible to reduce the thermal blooming effect.

Dynamic Mechanisms Associated with the Structure and Evolution of Roll Vortices and Coherent Turbulence in the Hurricane Boundary Layer: A Large Eddy Simulation During the Landfall of Hurricane Harvey

Roll vortices are a series of large-scale turbulent eddies that nearly align with the mean wind direction and prevail in the hurricane boundary layer. In this study, the one-way nested WRF-LES model simulation results from Li et al. (J Atmos Sci 78(6):1847–1867, https://doi.org/10.1175/JAS-D-20-0270.1, 2021) are used to examine the structure and generation mechanism of roll vortices and associated coherent turbulence in the hurricane boundary layer during the landfall of Hurricane Harvey from 00 UTC 25 to 18 UTC 27 August 2017. Results indicate that roll vortices prevail in the hurricane boundary layer. The intense roll vortices and associated large turbulent eddies above them (at a height of ~ 200 to 3000 m) accumulate within a hurricane radius of 20–40 km. Their intensity is proportional to hurricane intensity during the simulation period. Before and during hurricane landfall, strong inflow convergence leads to horizontal advection of roll vortices throughout the entire hurricane boundary layer. Combined with the strong wind shear, the strongest roll vortices and associated large turbulent eddies are generated near the eyewall with suitable thermodynamic (Richardson number at around − 0.2 to 0.2) and dynamic conditions (strong negative inflow wind shear). After landfall, the decayed inflow weakens the inflow convergence and quickly reduces the strong roll vortices and associated large turbulent eddies. Diagnosis of vertical turbulent kinetic energy indicates that atmospheric pressure perturbation, caused by horizontal convergence, transfers the horizontal component of turbulence to the vertical component with a mean wavelength of about 1 km. The buoyancy term is weak and negative, and the large turbulent eddies are suppressed.

Compound motion decoding based on sEMG consisting of gestures, wrist angles, and strength

This study aimed to highlight the demand for upper limb compound motion decoding to provide a more diversified and flexible operation for the electromyographic hand. In total, 60 compound motions were selected, which were combined with four gestures, five wrist angles, and three strength levels. Both deep learning methods and machine learning classifiers were compared to analyze the decoding performance. For deep learning, three structures and two ways of label encoding were assessed for their training processes and accuracies; for machine learning, 24 classifiers, seven features, and a combination of classifier chains were analyzed. Results show that for this relatively small sample multi-target surface electromyography (sEMG) classification, feature combination (mean absolute value, root mean square, variance, 4th-autoregressive coefficient, wavelength, zero crossings, and slope signal change) with Support Vector Machine (quadric kernel) outstood because of its high accuracy, short training process, less computation cost, and stability (p < 0.05). The decoding result achieved an average test accuracy of 98.42 ± 1.71% with 150 ms sEMG. The average accuracy for separate gestures, wrist angles, and strength levels were 99.35 ± 0.67%, 99.34 ± 0.88%, and 99.04 ± 1.16%. Among all 60 motions, 58 showed a test accuracy greater than 95%, and one part was equal to 100%.

Stabilization of the mean wavelength of an erbium-doped fiber source as part of high-accuracy FOG with increased spectrum width.

The mean wavelength, spectrum width, and optical power of the output light of an erbium-doped fiber source (EDFS) are key parameters for navigation systems based on navigation-grade and strategic-grade fiber optic gyroscopes (FOGs). We propose a method of simultaneous stabilization for EDFS parameters. The essence of this method is to stabilize the constant values of the mean wavelength and optical power by real-time adjustment of the two laser diodes' pump ratios during temperature changes using an EDFS double-pass bidirectional optical scheme with the unpumped erbium-doped fiber. The achieved temperature stability of the EDFS mean wavelength as a component of the FOG was 0.32 ppm/°C, and the spectrum width at half-maximum was more than 16.5 nm.