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Objective. To evaluate electrical impedance myography (EIM) in conjunction with machine learning (ML) to detect infantile spinal muscular atrophy (SMA) and disease progression. Approach . Twenty-six infants with SMA and twenty-seven healthy infants had been enrolled and assessed with EIM as part of the NeuroNEXT SMA biomarker study. We applied a variety of modern, supervised ML approaches to this data, first seeking to differentiate healthy from SMA muscle, and then, using the best method, to track SMA progression. Main Results. Several of the ML algorithms worked well, but linear discriminant analysis (LDA) achieved 88.6% accuracy on subject muscles studied. This contrasts with a maximum of 60% accuracy that could be achieved using the single or multifrequency assessment approaches available at the time. LDA scores were also able to track progression effectively, although a multifrequency reactance-based measure also performed very well in this context. Significance. EIM enhanced with ML promises to be effective for providing effective diagnosis and tracking children and adults with SMA treated with currently available therapies. The normative trends identified here may also inform future applications of the technology in very young children. The basic analyses applied here could also likely be applied to other neuromuscular disorders characterized by muscle atrophy., (© 2024 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Objective . The measurement of electromyography (EMG) signals with needle electrodes is widely used in clinical settings for diagnosing neuromuscular diseases. Patients experience pain during needle EMG testing. It is significant to develop alternative diagnostic modalities. Approach . This paper proposes a portable magnetomyography (MMG) measurement system for neuromuscular disease auxiliary diagnosis. Firstly, the design and operating principle of the system are introduced. The feasibility of using the system for auxiliary diagnosis of neuromuscular diseases is then studied. The magnetic signals and needle EMG signals of thirty subjects were collected and compared. Main results . It is found that the amplitude of muscle magnetic field signal increases during mild muscle contraction, and the signal magnitudes of the patients are smaller than those of normal subjects. The diseased muscles tested in the experiment can be distinguished from the normal muscles based on the signal amplitude, using a threshold value of 6 pT. The MMG diagnosis results align well with the needle EMG diagnosis. In addition, the MMG measurement indicates that there is a persistence of spontaneous activity in the diseased muscle. Significance. The experimental results demonstrate that it is feasible to auxiliary diagnose neuromuscular diseases using the portable MMG system, which offers the advantages of non-contact and painless measurements. After more in-depth, systematic, and quantitative research, the portable MMG could potentially be used for auxiliary diagnosis of neuromuscular diseases. The clinical trial registration number is ChiCTR2200067116., (© 2024 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Electrical activity in the sensory-motor and supplementary motor areas of the cerebral cortex is known to occur during a 'readiness interval', extending up to 2 s before the relevant muscle actually contracts. This paper presents evidence that there are also changes in the properties of the muscle itself during a similar preparatory period, as revealed by dynamic electrical impedance myography. 11 healthy subjects aged 23.5 ± 2.5 years were asked to perform a series of isometric gripping exercises during which the force, resistance and reactance of the forearm finger flexor muscles were monitored. A change in reactance, ΔX, or resistance, ΔR, which occurred before the generation of force, ΔF, was dubbed a 'PIC', shorthand for precontraction impedance change (subject to criteria to rule out the possibility of simple 'noise'), of which 1206 qualified in the entire subject cohort. Such PIC's are statistically well correlated when expressed in terms of differences between PIC and force onset times (r ≈ 0.9, p ≈ 0). This is demonstrated using a variation on the 'computer of average transients' method. Precontraction impedance changes (PICs) occurring as much as 2 s before the onset of force generation were found, in qualitative agreement with precontraction EEG activity reported in the literature. Also, a subset of PIC's was found in which the scaled and time-shifted ΔX(t) was virtually identical to ΔF(t). Since the occurrence and timing of all the PICs depend on oral commands, it is clear that the auditory cortex is likely involved, but the detailed mechanism coupling brain activity with PICs is not known.

This study examined the mechanomyographic mean power frequency (MMGMPF)-force relationships for five (age = 19.20   ±   0.45 years) aerobically-trained (AT), five (age = 25   ±   4.53 years) resistance-trained (RT), and five (age = 21.20   ±   2.17 years) sedentary (SED) individuals. Participants performed isometric trapezoidal muscle actions at 50, 60, and 70% maximal voluntary contraction (MVC) of the leg extensors that included linearly increasing, steady force, and linearly decreasing segments. MMG was recorded from the vastus lateralis. Linear regressions were fit to the natural-log transformed MMGMPF versus natural log-transformed force relationships (linearly increasing and decreasing segments) with the b (slope) and a (y-intercept) terms used for comparisons. MMGMPF was averaged for the entire steady force segment. The b and a terms were not different among training statuses (P  >  0.05) or linearly increasing and decreasing segments (P  >  0.05). There were muscle action-related differences in the b terms as a function of training status from the 70% MVC. The SED had greater b terms during the linearly increasing than decreasing muscle action (P = 0.010), and the converse was true for the AT (P = 0.013), whereas the RT displayed no muscle action-related differences (P  >  0.05). The unique muscle action-related differences in the b terms as a function of training status may be the result of unique adaptations to motor unit activation and deactivation strategies.

Our aim is to investigate the significance of electrogastrography in the treatment of esophageal variceal hemorrhage with octreotide. Electrogastrography was performed in patients with esophageal variceal hemorrhage before and during the treatment consisting of various doses of octreotide (25 ug h(-1) group and 50 ug h(-1) group). The dominant power of electrogastrography and its relationship with the hemostatic efficacy of octreotide treatment were evaluated. Dominant power of electrogastrography decreased significantly during treatment with octreotide (P < 0.05). The reduction in the amplitude of dominant power in the 50 ug h(-1) group was significantly larger than in the 25 ug h(-1) group (P < 0.05), and it was correlated with hemostatic efficacy of octreotide treatment. We conclude that octreotide treatment in patients with esophageal variceal hemorrhage can result in a significant decrease of dominant power, which correlates with the hemostatic efficacy of octreotide, so the change of dominant power could be used as a predictor of evaluating the treatment efficacy of octreotide in esophageal variceal hemorrhage patients.

The aim of the present study was to determine if the patterns of mechanomyographic (MMG) amplitude across force would change with strength training. Twenty-two healthy men completed an 8-week strength training program. During three separate testing visits (pre-test, week 4, and week 8), the MMG signal was detected from the vastus lateralis as the subjects performed isometric step muscle actions of the leg extensors from 10-100% of maximal voluntary contraction (MVC). During pre-testing, the MMG amplitude increased linearly with force to 66% MVC and then plateaued. Conversely, weeks 4 and 8 demonstrated an increase in MMG amplitude up to ≈ 85% of the subject's original MVC before plateauing. Furthermore, seven of the ten force levels (30-60% and 80-100%) showed a significant decrease in mean MMG amplitude values after training, which consequently led to a decrease in the slope of the MMG amplitude/force relationship. The decreases in MMG amplitude at lower force levels are indicative of hypertrophy, since fewer motor units would be required to produce the same absolute force if the motor units increased in size. However, despite the clear changes in the mean values, analyses of individual subjects revealed that only 55% of the subjects demonstrated a significant decrease in the slope of the MMG amplitude/force relationship.

Myotonometric measurements are quantitative methods of muscle tone assessment and may be used as an alternative for palpation evaluation. The objective of the study was to compare the measurements of brachioradialis muscle tone and stiffness using the Myoton-3 and the Myotonometer. The participants were young males (N = 17, mean age 21 ± 1 years). The skeletal muscle state was expressed by the Myoton-3 parameters stiffness (N m(-1)), frequency (Hz) and decrement (no unit) and the Myotonometer's area under the curve (AUC) parameter (area under the curve, no unit), when muscle was at rest and during activity at 25%, 50%, 80% and 100% of maximal voluntary contraction for elbow flexors. Pearson's correlation between AUC and stiffness is r = -0.89, AUC and frequency r = -0.84 and AUC and decrement r = 0.79, p < 0.01. When comparing the results from each experimental condition separately for frequency and AUC, the correlation was from -0.63 to -0.80, for stiffness and AUC it ranged from -0.25 to -0.75 and for decrement and AUC from 0.27 to 0.74. The degree of correlation between myotonometric measurements depends on whether the measured muscle is at rest or during contraction. The correlation is diverse among related parameters.

Knowledge of muscle activity timing is critical to many clinical applications, such as the assessment of muscle coordination and the prescription of muscle-activated switches for individuals with disabilities. In this study, we introduce a continuous wavelet transform (CWT) algorithm for the detection of muscle activity via mechanomyogram (MMG) signals. CWT coefficients of the MMG signal were compared to scale-specific thresholds derived from the baseline signal to estimate the timing of muscle activity. Test signals were recorded from the flexor carpi radialis muscles of 15 able-bodied participants as they squeezed and released a hand dynamometer. Using the dynamometer signal as a reference, the proposed CWT detection algorithm was compared against a global-threshold CWT detector as well as amplitude-based event detection for sensitivity and specificity to voluntary contractions. The scale-specific CWT-based algorithm exhibited superior detection performance over the other detectors. CWT detection also showed good muscle selectivity during hand movement, particularly when a given muscle was the primary facilitator of the contraction. This may suggest that, during contraction, the compound MMG signal has a recurring morphological pattern that is not prevalent in the baseline signal. The ability of CWT analysis to be implemented in real time makes it a candidate for muscle-activity detection in clinical applications.

The purpose of the present study was to examine the stationarity of surface mechanomyographic (MMG) signals from the vastus lateralis, rectus femoris and vastus medialis during concentric isokinetic, eccentric isokinetic and isometric muscle actions of the leg extensors. Eleven healthy men (mean +/- SD age = 20.1 +/- 1.1 years) performed submaximal to maximal concentric isokinetic, eccentric isokinetic and isometric muscle actions of the leg extensors, and surface MMG signals were detected from the vastus lateralis, rectus femoris and vastus medialis. All surface MMG signals were tested for stationarity with a procedure that examined changes in the mean value, variance, mean frequency and standard deviation of the power spectrum over time. The results showed that the three muscle action types resulted in similar levels of signal nonstationarity. Thus, despite the fact that the isometric muscle actions were performed at a constant force level and with no change in muscle length, the level of signal nonstationarity was similar to that for the concentric and eccentric isokinetic muscle actions. Future studies need to be done to identify the mechanism(s) causing MMG signal nonstationarity during isometric muscle actions.

The purpose of this study was to use laser displacement sensors to examine the cross-correlation of surface mechanomyographic (MMG) signals detected from the rectus femoris muscle in perpendicular and transverse axes during isometric muscle actions of the leg extensors. Ten healthy men (mean +/- SD age = 22.1 +/- 1.6 years) and ten healthy women (age = 24.4 +/- 2.8 years) volunteered to perform submaximal to maximal isometric muscle actions of the dominant leg extensors. During each muscle action, two separate MMG signals were detected from the rectus femoris with laser displacement sensors. One MMG sensor was oriented in an axis that was perpendicular (PERP) to the muscle surface, and the second sensor was oriented in an axis that was transverse (TRAN) to the muscle surface. For each subject and force level, the MMG signals from the PERP and TRAN sensors were cross-correlated. The results showed maximum cross-correlation coefficients that ranged from R(x)(,y) = 0.273 to 0.989, but all subjects demonstrated at least one coefficient greater than 0.89. These findings showed a high level of association between the MMG signals detected in the perpendicular and transverse axes. Thus, it may not be necessary to detect MMG signals in multiple axes.

The objective of this study was to assess the gait variability of lumbar spinal stenosis (LSS) patients and to evaluate its postoperative progression. The hypothesis was that LSS patients' preoperative gait variability in the frequency domain was higher than the corresponding postoperative. A tri-axial accelerometer sensor was used for the gait measurement and a spectral differential entropy algorithm was used to measure the gait variability. Twelve subjects with LSS were measured before and after surgery. Preoperative measurements were performed 2 days before surgery. Postoperative measurements were performed 6 and 12 months after surgery. Preoperative gait variability was higher than the corresponding postoperative. Also, in most cases, gait variability appeared to decrease throughout the year.

The objective of this study is to compare the gait variability of patients with lumbar spinal stenosis (experimental group) with healthy individuals (control group). The hypothesis is that the preoperative gait variability of the experimental group is higher than the control group. The experimental group consisted of 35 adults (18 males, 17 females). The subjects of the experimental group suffered exclusively from spinal stenosis. The patients were determined by MRI scans. A tri-axial accelerometer sensor was used for the gait measurement, and differential entropy algorithm was used to quantify the gait acceleration signal. The Oswestry Low Back Pain Questionnaire was used to determine the condition on the day of the measurement. Receiver operating characteristic (ROC) was utilized to assess the diagnostic value of the method and determine a cut-off value. There is a statistically significant difference between gait variability in the control group and the experimental group. ROC analysis determines a cut-off differential entropy value. The cut-off value has a 97.6% probability of separating patients with spinal stenosis from healthy subjects. The Oswestry Low Back Questionnaire is well correlated with the spectral differential entropy values.

We propose a multi-stage approach using Wavelet and Hilbert transforms to identify uterine contraction bursts in magnetomyogram (MMG) signals measured using a 151 magnetic sensor array. In the first stage, we decompose the MMG signals by wavelet analysis into multilevel approximate and detail coefficients. In each level, the signals are reconstructed using the detail coefficients followed by the computation of the Hilbert transform. The Hilbert amplitude of the reconstructed signals from different frequency bands (0.1-1 Hz) is summed up over all the sensors to increase the signal-to-noise ratio. Using a novel clustering technique, affinity propagation, the contractile bursts are distinguished from the noise level. The method is applied on simulated MMG data, using a simple stochastic model to determine its robustness and to seven MMG datasets.

The primary purpose of this study was to examine the consistency of ordinary least-squares (OLS) and generalized least-squares (GLS) polynomial regression analyses utilizing linear, quadratic and cubic models on either five or ten data points that characterize the mechanomyographic amplitude (MMG(RMS)) versus isometric torque relationship. The secondary purpose was to examine the consistency of OLS and GLS polynomial regression utilizing only linear and quadratic models (excluding cubic responses) on either ten or five data points. Eighteen participants (mean +/- SD age = 24 +/- 4 yr) completed ten randomly ordered isometric step muscle actions from 5% to 95% of the maximal voluntary contraction (MVC) of the right leg extensors during three separate trials. MMG(RMS) was recorded from the vastus lateralis during the MVCs and each submaximal muscle action. MMG(RMS) versus torque relationships were analyzed on a subject-by-subject basis using OLS and GLS polynomial regression. When using ten data points, only 33% and 27% of the subjects were fitted with the same model (utilizing linear, quadratic and cubic models) across all three trials for OLS and GLS, respectively. After eliminating the cubic model, there was an increase to 55% of the subjects being fitted with the same model across all trials for both OLS and GLS regression. Using only five data points (instead of ten data points), 55% of the subjects were fitted with the same model across all trials for OLS and GLS regression. Overall, OLS and GLS polynomial regression models were only able to consistently describe the torque-related patterns of response for MMG(RMS) in 27-55% of the subjects across three trials. Future studies should examine alternative methods for improving the consistency and reliability of the patterns of response for the MMG(RMS) versus isometric torque relationship.

Extension of the frequency range of electrical impedance myography (EIM) to 2 MHz discloses a major rise in the reactance of muscle above 3-500 kHz, together with a slow decrease in the resistance consonant with the Kramers-Kronig relations. This 'upturn' phenomenon is found when the distant current electrode configuration of EIM is employed, but not when the current electrodes are placed close to the voltage measuring area. In that case the impedance qualitatively mimics the commonly used 3-element resistor-capacitor model. The possibility that the upturn is an artifact of the measuring system rather than a true property of the tissue is examined in detail. In particular, experiments are reported which argue against the transmission line mechanism proposed to explain similar increases in reactance in some high frequency whole-body BIA studies. Also, scaling of X versus R plots for muscle segments of different lengths strongly suggests that the upturn is as much a property of the underlying tissue as is the low frequency maximum in reactance.

Electrical impedance myography (EIM) is a painless and non-invasive technique for the assessment of muscle which we apply here to the effects of normal aging. The paper presents a cross-sectional analysis of EIM data from the quadriceps and tibialis anterior of 100 healthy subjects (44 men, 56 women, ages 18-90 years). The principal EIM parameter, the spatially averaged phase theta(avg), shows a roughly quadratic reduction with increasing age, declining more steeply beyond 60 years. The correlation was stronger in men (quadriceps: r2 = 0.68 for men, 0.52 for women; tibialis anterior: r2 = 0.74 for men, 0.38 for women; p < 0.001 throughout). Additionally, four subjects (age greater than 75 years) were asked to return for repeat testing several years after their initial assessment. These longitudinal results qualitatively confirm the cross-sectional data, though with greater reductions in theta(avg) at high age. The findings of this study support the potential use of EIM as a simple and effort-independent test of muscle health in the elderly.