The rapid growth of the global aging population has heightened the risk of age-related conditions such as sarcopenia, stroke, Parkinson’s disease, and Alzheimer’s disease. While some of these are primarily neurological, all can lead to significant biomechanical impairments, including muscle weakness, abnormal gait, and balance deficits. Recent advances in materials science, wearable sensors, and AI algorithms now enable continuous, objective measurement of movement patterns, joint function, and muscle activity in both clinical and home settings. These technologies provide detailed biomechanical data, revealing how neurological and musculoskeletal changes translate into functional decline. For example, wearable sensors can detect early gait abnormalities in Parkinson’s disease, while robot-assisted therapy delivers precise, biomechanically-informed rehabilitation after stroke. Despite these advances, traditional approaches remain manual and insufficiently personalized to the biomechanical variability seen in aging individuals. This underscores the urgent need for more precise, individualized biomechanical solutions in age-related healthcare.

This Research Topic aims to address key public health challenges by advancing biomechanical science and technology for older adults, with the ultimate goal of improving functional outcomes and quality of life. The specific objectives are:
• Developing high-fidelity musculoskeletal and neuromechanical models tailored to the aging body, enabling precise simulation and analysis of movement, joint loading, and tissue adaptation in age-related conditions;
• Designing wearable systems that integrate advanced biomechanical sensors, real-time data processing, and ergonomic form factors to continuously monitor gait, posture, and muscle activity, assess fall risk, and deliver personalized, biomechanics-based rehabilitation feedback;
• Applying machine-learning and explainable AI techniques to analyze biomechanical data, enhance the detection of abnormal movement patterns, differentiate between types of motor impairment, and predict rehabilitation outcomes, thereby supporting data-driven biomechanical decision-making in clinical practice;
• Translating these biomechanical innovations into targeted interventions that are accessible and scalable, such as individualized exercise programs, assistive devices, and remote monitoring solutions, all grounded in biomechanical principles and tailored to the needs of aging populations.
By focusing on biomechanical mechanisms and applications, this Research Topic seeks to bridge the gap between technological advances and their practical impact on mobility, independence, and safety in older adults.

We invite submissions focused on the intersection of aging, biomechanics, wearable technology, and AI. Relevant topics include, but are not limited to:
• Novel frameworks and validation studies that elucidate biomechanical mechanisms underlying geriatric conditions and inform the development of diagnostic or therapeutic biomaterials;
• Wearable systems integrating biomechanical sensors and on-device computing for continuous movement monitoring, gait analysis, and fall risk assessment;
• Injury-risk assessment using quantitative biomechanical metrics to evaluate functional status in older adults;
• Digital, biomechanics-based interventions—such as robot-assisted rehabilitation or virtual reality therapies—targeting mobility, balance, and musculoskeletal recovery;
• Explainable AI models for interpreting biomechanical data, predicting injury risk, and providing personalized feedback.

Submissions must emphasize biomechanical mechanisms or applications in geriatric medicine. Only primary research articles and systematic review papers will be considered.

Are you interested in contributing a manuscript to this Research Topic?

Technology-Enabled Healthy Ageing: Biomechanical Modelling, Wearable Devices, and AI in Geriatric Medicine