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Muscle quality defined as the ratio of muscle strength to muscle mass disregards underlying factors which influence muscle strength. The aim of this review was to investigate the relationship of phase angle (PhA), echo intensity (EI), muscular adipose tissue (MAT), muscle fiber type, fascicle pennation angle (θf), fascicle length (lf), muscle oxidative capacity, insulin sensitivity (IS), neuromuscular activation, and motor unit to muscle strength. PubMed search was performed in 2021. The inclusion criteria were: (i) original research, (ii) human participants, (iii) adults (≥18 years). Exclusion criteria were: (i) no full-text, (ii) non-English or -German language, (iii) pathologies. Forty-one studies were identified. Nine studies found a weak–moderate negative (range r: [−0.26]–[−0.656], p < 0.05) correlation between muscle strength and EI. Four studies found a weak–moderate positive correlation (range r: 0.177–0.696, p < 0.05) between muscle strength and PhA. Two studies found a moderate-strong negative correlation (range r: [−0.446]–[−0.87], p < 0.05) between muscle strength and MAT. Two studies found a weak-strong positive correlation (range r: 0.28–0.907, p < 0.05) between θf and muscle strength. Muscle oxidative capacity was found to be a predictor of muscle strength. This review highlights that the current definition of muscle quality should be expanded upon as to encompass all possible factors of muscle quality.
Background and Aims Wearable inertial sensors may offer additional kinematic parameters of the shoulder compared to traditional instruments such as goniometers when elaborate and time-consuming data processing procedures are undertaken. However, in clinical practice simple-real time motion analysis is required to improve clinical reasoning. Therefore, the aim was to assess the criterion validity between a portable "off-the-shelf" sensor-software system (IMU) and optical motion (Mocap) for measuring kinematic parameters during active shoulder movements. Methods 24 healthy participants (9 female, 15 male, age 29 +/- 4 years, height 177 +/- 11 cm, weight 73 +/- 14 kg) were included. Range of motion (ROM), total range of motion (TROM), peak and mean angular velocity of both systems were assessed during simple (abduction/adduction, horizontal flexion/horizontal extension, vertical flexion/extension, and external/internal rotation) and complex shoulder movements. Criterion validity was determined using intraclass-correlation coefficients (ICC), root mean square error (RMSE) and Bland and Altmann analysis (bias; upper and lower limits of agreement). Results ROM and TROM analysis revealed inconsistent validity during simple (ICC: 0.040-0.733, RMSE: 9.7 degrees-20.3 degrees, bias: 1.2 degrees-50.7 degrees) and insufficient agreement during complex shoulder movements (ICC: 0.104-0.453, RMSE: 10.1 degrees-23.3 degrees, bias: 1.0 degrees-55.9 degrees). Peak angular velocity (ICC: 0.202-0.865, RMSE: 14.6 degrees/s-26.7 degrees/s, bias: 10.2 degrees/s-29.9 degrees/s) and mean angular velocity (ICC: 0.019-0.786, RMSE:6.1 degrees/s-34.2 degrees/s, bias: 1.6 degrees/s-27.8 degrees/s) were inconsistent. Conclusions The "off-the-shelf" sensor-software system showed overall insufficient agreement with the gold standard. Further development of commercial IMU-software-solutions may increase measurement accuracy and permit their integration into everyday clinical practice.