Background: Muscular strength training interventions have long been a cornerstone in the prevention, non-surgical management and rehabilitation of the entire spectrum of musculoskeletal injuries and diseases. The key goal of strength training, especially during rehabilitation, is to regain healthy musculoskeletal function. Yet, there remains a fundamental lack of understanding with regards to the relationship between subject-specific musculoskeletal biomechanics (i.e. multi-body dynamics function) and different types of strength training interventions because of limitations in assessing these parameters outside the research setting. Thus, clinicians, physiotherapists and coaches continue making training recommendations based on subjective and generalised guidelines, with ineffective or possibly harmful consequences for individual patients and athletes.

Goal: This SNF project aims to advance strength training guidelines and monitoring of training safety and efficiency by means of subject-specific anatomically-based modelling, biomechanical analysis of musculoskeletal function and mobile monitoring of training volume and muscular fatigue in the athletic and recreational setting.Method: We will advance the state-of-the-art in subject-specific biomechanical analysis of strength training intervention by personalising a multi-body dynamics model based on advanced anatomically-based fitting to subject-specific data from 3D body scanning, validated against magnetic resonance imaging as gold standard (Specific Goal SG#1).

In parallel, we will advance numerical algorithms for mobile monitoring of training volume and muscular fatigue by means of Inertial Measurement Units (IMU)s, as embedded in the Apple smartwatch (SG#2). For validation purposes, we will conduct an 8-week intervention study in healthy volunteers with three levels of strength training volume of the key muscle-tendon groups associated with knee joint stability (SG#3) and relate the changes in musculoskeletal and biomechanical parameters (SG#1) to the training-specific parameters and muscular fatigue from mobile monitoring (SG#2) through correlation analysis.

Relevance: In Switzerland, more than 1.3 Mio people are members of a fitness center. Strength training is not only a cornerstone in the maintenance of fitness and rehabilitation from musculoskeletal injuries and diseases as the most frequently reported health issues in the adult population worldwide, but has also been shown to reduce mortality due to cancer by more than 30%. The proposed advancements of computational tools in anatomically-based fitting and personalised analysis of musculoskeletal biomechanics are addressing key limitations that are highly relevant within the global fields of orthopaedics and biomechanics research, and are crucial towards driving future personalised human health models. This project is highly synergistic with the ‘personalised health’ and ‘digitalization’ initiatives of the SBFI, as well as with ‘Healthy Aging’ as core priority both nationally and internationally. Thereby, it is tremendously important to combine state-of-the-art musculoskeletal simulation with science-based data from mobile devices in order to improve strength training monitoring in the athletic and recreational setting, reduce injury risks and help towards developing more effective strength training guidelines for individual athletes and the wider population alike.