Retentive capacity of power output and linear versus non-linear mapping of power loss in the isotonic muscular endurance test.

The limit of dynamic endurance during repetitive contractions has been referred to as the point of muscle fatigue, which can be measured by mechanical and electrophysiological parameters combined with subjective estimates of load tolerance for revealing the human real-world capacity required to work continuously. In this study, an isotonic muscular endurance (IME) testing protocol under a psychophysiological fatigue criterion was developed for measuring the retentive capacity of the power output of lower limb muscles. Additionally, to guide the development of electrophysiological evaluation methods, linear and non-linear techniques for creating surface electromyography (sEMG) models were compared in terms of their ability to estimate muscle fatigue. Forty healthy college-aged males performed three trials of an isometric peak torque test and one trial of an IME test for the plantar flexors and knee and hip extensors. Meanwhile, sEMG activity was recorded from the medial gastrocnemius, lateral gastrocnemius, vastus medialis, rectus femoris, vastus lateralis, gluteus maximus, and biceps femoris of the right leg muscles. Linear techniques (amplitude-based parameters, spectral parameters, and instantaneous frequency parameters) and non-linear techniques (a multi-layer perception neural network) were used to predict the time-dependent power output during dynamic contractions. Two mechanical manifestations of muscle fatigue were observed in the IME tests, including power output reduction between the beginning and end of the test and time-dependent progressive power loss. Compared with linear mapping (linear regression) alone or a combination of sEMG variables, non-linear mapping of power loss during dynamic contractions showed significantly higher signal-to-noise ratios and correlation coefficients between the actual and estimated power output. Muscular endurance required in real-world activities can be measured by considering the amount of work produced or the activity duration via the recommended IME testing protocol under a psychophysiological termination criterion. Non-linear mapping techniques provide more powerful mapping of power loss compared with linear mapping in the IME testing protocol.

Estimation of skeletal muscle mass by bioimpedance and differences among skeletal muscle mass indices for assessing sarcopenia.

BACKGROUND: It is crucial to assess age-related muscle mass changes and derived indices differences in geriatric medicine. We aimed to develop and validate four bioimpedance analysis (BIA) prediction equations against dual-energy X-ray absorptiometry (DEXA) and magnetic resonance image (MRI) in estimating skeletal muscle mass and to compare the differences among skeletal muscle mass indices, cutoff values, and corresponding prevalence rates of low muscle mass for assessing sarcopenia in Chinese adults. METHODS: We measured the height (Ht), weight (Wt), appendicular lean mass (ALM) or skeletal muscle mass (ASM), total lean body mass (LBM) or skeletal muscle mass (TSM) obtained using DEXA or MRI, and a multi-frequency BIA (BCA II;50, 250 kHz), in 371 adults aged 18.0-87.0 years. We also collected gender, age, Ht, Wt, and impedance indexes (Ht2/R50, Ht2/R250, R50/Ht2, R250/Ht2) from 30,500 adults aged 18-96 years living in China. Multiple regression analyses were used to derive four prediction equations by BIA, and double cross-validation techniques and Bland-Altman analyses were used to test agreement. Various muscle mass indices and prevalence rates were depicted by line plots in regard to age trends. RESULTS: Satisfactory results were found in the four prediction models as they had the larger R2 (0.833-0.930) values and low SEE (1.409-2.335 kg) values. The predictive variables included impedance indexes (Ht2/R50, R50/Ht2, R250/Ht2), gender, age, Wt, and Ht. The corresponding prevalence rates of low muscle mass exhibited significant differences according to the various muscle mass indices adjusted for Ht, Wt, or body mass index (BMI), in addition to the cutoff values based on two standard deviations (2SD) of young people or the lower 20% of the study group. CONCLUSIONS: The BIA equations have the potential to be applied as a practical method of quantifying skeletal muscle mass in Chinese adults. However, the operational methods that are most appropriate for determining the degree of low muscle mass that actually contributes to sarcopenia remains inconclusive.