In this paper, we introduce the nonstationary signal analysis methods to analyze the myoelectric (ME) signals during dynamic contractions by estimating the time-dependent spectral moments. The time-frequency analysis methods including the short-time Fourier transform, the Wigner-Ville distribution, the Choi-Williams distribution, and the continuous wavelet transform were compared for estimation accuracy and precision on synthesized and real ME signals. It is found that the estimates provided by the continuous wavelet transform have better accuracy and precision than those obtained with the other time-frequency analysis methods on simulated data sets. In addition, ME signals from four subjects during three different tests (maximum static voluntary contraction, ramp contraction, and repeated isokinetic contractions) were also examined.

Introduces wavelet packets as an alternative method for spectral analysis of surface myoelectric (ME) signals. Both computer synthesized and real ME signals are used to investigate the performance. The authors' simulation results show that wavelet packet estimate has slightly less mean square error (MSE) than Fourier method, and both methods perform similarly on the real data. Moreover, wavelet packets give one some advantages over the traditional methods such as multiresolution of frequency, as well as its potential use for effecting time-frequency decomposition of the nonstationary signals such as the ME signals during dynamic contractions. The authors also introduce wavelet shrinkage method for improving spectral estimates by significantly reducing the MSE's for both Fourier and wavelet packet methods.

The central nervous system coordinates movement through forces generated by motor units (MUs) in skeletal muscles. To analyze MUs function is essential in sports, rehabilitation medicine applications, and neuromuscular diagnostics. The MUs and their function are studied using electromyography. Typically, these methods study only a small muscle volume (1 mm3) or only a superficial (< 1 cm) volume of the muscle. Here we introduce a method to identify so-called mechanical units, i.e., the mechanical response of electrically active MUs, in the whole muscle (4x4 cm, cross-sectional) under voluntary contractions by ultrafast ultrasound imaging and spatiotemporal decomposition. We evaluate the performance of the method by simulation of active MUs’ mechanical response under weak contractions. We further test the experimental feasibility on eight healthy subjects. We show the existence of mechanical units that contribute to the tissue dynamics in the biceps brachii at low force levels and that these units are similar to MUs described by electromyography with respect to the number of units, territory sizes, and firing rates. This study introduces a new potential neuromuscular functional imaging method, which could be used to study a variety of questions on muscle physiology that previously were difficult or not possible to address.

Summary: Stable isotope abundances convey valuable information about plant physiological processes and underlying environmental controls. Central gaps in our mechanistic understanding of hydrogen isotope abundances impede their widespread application within the plant and biogeosciences. To address these gaps, we analysed intramolecular deuterium abundances in glucose of Pinus nigra extracted from an annually resolved tree‐ring series (1961–1995). We found fractionation signals (i.e. temporal variability in deuterium abundance) at glucose H¹ and H² introduced by closely related metabolic processes. Regression analysis indicates that these signals (and thus metabolism) respond to drought and atmospheric CO₂ concentration beyond a response change point. They explain ≈ 60% of the whole‐molecule deuterium variability. Altered metabolism is associated with below‐average yet not exceptionally low growth. We propose the signals are introduced at the leaf level by changes in sucrose‐to‐starch carbon partitioning and anaplerotic carbon flux into the Calvin–Benson cycle. In conclusion, metabolism can be the main driver of hydrogen isotope variation in plant glucose.

Measurements of carbon isotope contents of plant organic matter provide important information in diverse fields such as plant breeding, ecophysiology, biogeochemistry and paleoclimatology. They are currently based on¹³C/¹²C ratios of specific, whole metabolites, but we show here that intramolecular ratios provide higher resolution information. In the glucose units of tree-ring cellulose of 12 tree species, we detected large differences in¹³C/¹²C ratios (>10‰) among carbon atoms, which provide isotopically distinct inputs to major global C pools, including wood and soil organic matter. Thus, considering position-specific differences can improve characterisation of soil-to-atmosphere carbon fluxes and soil metabolism. In aPinus nigratree-ring archive formed from 1961 to 1995, we found novel¹³C signals, and show that intramolecular analysis enables more comprehensive and precise signal extraction from tree rings, and thus higher resolution reconstruction of plants’ responses to climate change. Moreover, we propose an ecophysiological mechanism for the introduction of a¹³C signal, which links an environmental shift to the triggered metabolic shift and its intramolecular¹³C signature. In conclusion, intramolecular¹³C analyses can provide valuable new information about long-term metabolic dynamics for numerous applications.