Towards Subject-Specific Strength Training Design through Predictive Use of Musculoskeletal Models

Supervision during resistance training positively influences muscular adaptations in resistance-trained individuals

This study compared the effects of supervised versus unsupervised resistance training (RT) on measures of muscle strength and hypertrophy in resistance-trained individuals. Thirty-six young men and women were randomly assigned to one of two experimental, parallel groups to complete an 8-week RT programme: One group received direct supervision for their RT sessions (SUP); the other group performed the same RT programme in an unsupervised manner (UNSUP). Programme variables were kept constant between groups. We obtained pre- and post-study assessments of body composition via multi-frequency bioelectrical impedance analysis (MF-BIA), muscle thickness of the upper and lower limbs via ultrasound, 1 repetition maximum (RM) in the back squat and bench press, isometric knee extension strength, and countermovement jump (CMJ) height. Results showed the SUP group generally achieved larger increases in muscle thickness for the triceps brachii, all sites of the rectus femoris, and the proximal region of the vastus lateralis. MF-BIA indicated increases in lean mass favoured SUP. Squat 1RM was greater for SUP; bench press 1RM and isometric knee extension were similar between conditions. CMJ increases modestly favoured UNSUP. In conclusion, our findings suggest that supervised RT promotes greater muscular adaptations and enhances exercise adherence in young, resistance-trained individuals.

From fibre to function: are we accurately representing muscle architecture and performance?

The size and arrangement of fibres play a determinate role in the kinetic and energetic performance of muscles. Extrapolations between fibre architecture and performance underpin our understanding of how muscles function and how they are adapted to power specific motions within and across species. Here we provide a synopsis of how this 'fibre to function' paradigm has been applied to understand muscle design, performance and adaptation in animals. Our review highlights the widespread application of the fibre to function paradigm across a diverse breadth of biological disciplines but also reveals a potential and highly prevalent limitation running through past studies. Specifically, we find that quantification of muscle architectural properties is almost universally based on an extremely small number of fibre measurements. Despite the volume of research into muscle properties, across a diverse breadth of research disciplines, the fundamental assumption that a small proportion of fibre measurements can accurately represent the architectural properties of a muscle has never been quantitatively tested. Subsequently, we use a combination of medical imaging, statistical analysis, and physics-based computer simulation to address this issue for the first time. By combining diffusion tensor imaging (DTI) and deterministic fibre tractography we generated a large number of fibre measurements (>3000) rapidly for individual human lower limb muscles. Through statistical subsampling simulations of these measurements, we demonstrate that analysing a small number of fibres (n < 25) typically used in previous studies may lead to extremely large errors in the characterisation of overall muscle architectural properties such as mean fibre length and physiological cross-sectional area. Through dynamic musculoskeletal simulations of human walking and jumping, we demonstrate that recovered errors in fibre architecture characterisation have significant implications for quantitative predictions of in-vivo dynamics and muscle fibre function within a species. Furthermore, by applying data-subsampling simulations to comparisons of muscle function in humans and chimpanzees, we demonstrate that error magnitudes significantly impact both qualitative and quantitative assessment of muscle specialisation, potentially generating highly erroneous conclusions about the absolute and relative adaption of muscles across species and evolutionary transitions. Our findings have profound implications for how a broad diversity of research fields quantify muscle architecture and interpret muscle function.

A Systematic Review and Meta-Analysis on the Longitudinal Effects of Unilateral Knee Extension Exercise on Muscle Strength

The aim of the study was to investigate the time-dependent increase in the knee extensors' isometric strength as a response to voluntary, unilateral, isometric knee extension exercise (UIKEE). To do so, a systematic review was carried out to obtain data for a Bayesian longitudinal model-based meta-analysis (BLMBMA). For the systematic review, PubMed, Web of Science, SCOPUS, Chochrane Library were used as databases. The systematic review included only studies that reported on healthy, young individuals performing UIKEE. Studies utilizing a bilateral training protocol were excluded as the focus of this review lied on unilateral training. Out of the 3,870 studies, which were reviewed, 20 studies fulfilled the selected inclusion criteria. These 20 studies were included in the BLMBMA to investigate the time-dependent effects of UIKEE. If compared to the baseline strength of the trained limb, these data reveal that UKIEE can increase the isometric strength by up to 46%. A meta-analysis based on the last time-point of each available study was employed to support further investigations into UIKEE-induced strength increase. A sensitivity analysis showed that intensity of training (%MVC), fraction of male subjects and the average age of the subject had no significant influence on the strength gain. Convergence of BLMBMA revealed that the peak strength increase is reached after ~4 weeks of UIKEE training.

The Capacity of Generic Musculoskeletal Simulations to Predict Knee Joint Loading Using the CAMS-Knee Datasets

Musculoskeletal models enable non-invasive estimation of knee contact forces (KCFs) during functional movements. However, the redundant nature of the musculoskeletal system and uncertainty in model parameters necessitates that model predictions are critically evaluated. This study compared KCF and muscle activation patterns predicted using a scaled generic model and OpenSim static optimization tool against in vivo measurements from six patients in the CAMS-knee datasets during level walking and squatting. Generally, the total KCFs were under-predicted (RMS: 47.55%BW, R²: 0.92) throughout the gait cycle, but substiantially over-predicted (RMS: 105.7%BW, R²: 0.81) during squatting. To understand the underlying etiology of the errors, muscle activations were compared to electromyography (EMG) signals, and showed good agreement during level walking. For squatting, however, the muscle activations showed large descrepancies especially for the biceps femoris long head. Errors in the predicted KCF and muscle activation patterns were greatest during deep squat. Hence suggesting that the errors mainly originate from muscle represented at the hip and an associated muscle co-contraction at the knee. Furthermore, there were substaintial differences in the ranking of subjects and activities based on peak KCFs in the simulations versus measurements. Thus, future simulation study designs must account for subject-specific uncertainties in musculoskeletal predictions.

Functional resistance training during walking: Mode of application differentially affects gait biomechanics and muscle activation patterns

BACKGROUND

Task-specific loading of the limbs-termed as functional resistance training-is commonly used in gait rehabilitation; however, the biomechanical and neuromuscular effects of various forms of functional resistance training have not been studied systematically. This information is crucial for correctly selecting the appropriate mode of functional resistance training when treating individuals with gait disorders.

RESEARCH QUESTION

To comprehensively evaluate the biomechanical (i.e., joint moment and power) and muscle activation changes with different forms of functional resistance training that are commonly used in clinics and research using biomechanical simulation-based analyses.

METHODS

We developed simulations of functional resistance training during walking using OpenSim (Gait2354, 23 degrees of freedom and 54 muscles) and custom MATLAB scripts. We investigated five modes of functional resistance training that have been commonly used in clinics or in research: (1) a weight attached at the ankle, (2) an elastic band attached at the ankle, (3) a viscous device attached to the hip and knee, (4) a weight attached at the pelvis, and (5) a constant backwards pulling force at the pelvis. Lower-extremity joint moments and powers were computed using inverse dynamics and muscle activations were estimated using computed muscle control while walking with each device under multiple resistance levels: normal walking with no resistance, and walking with 30, 60, and 90 Newtons of resistance.

RESULTS

The results indicate that the way in which resistance is applied during gait training differentially affects the internal joint moments, powers, and muscle activations as well as the joints and phase of the gait cycle where the resistance was experienced.

SIGNIFICANCE

The results highlight the importance of understanding the joints and muscles that are targeted by various modes of functional resistance training and carefully choosing the best mode of training that meets the specific therapeutic needs of the patient.