Wearable-based estimation of continuous 3D knee moments during running using a convolutional neural network.

IF 2 3区医学 Q3 ENGINEERING, BIOMEDICAL

Sports Biomechanics Pub Date : 2025-03-24 DOI:10.1080/14763141.2025.2481164

Lucas Höschler, Christina Halmich, Christoph Schranz, Julian Fritz, Saša Čigoja, Martin Ullrich, Anne D Koelewijn, Hermann Schwameder

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引用次数: 0

Abstract

This study aimed to develop and validate a machine learning method to estimate continuous 3D knee moments during running from wearable sensor data. Reference knee moments were calculated from 19 recreational runners during treadmill running at varying slopes (0 ± 5 % incline), speeds (self-selected ± 1 km/h) and in 3 types of footwear. A convolutional neural network was trained on data from 7 inertial measuring units (feet, shanks, thighs, sacrum) and a pair of pressure insoles. We assessed performance over continuous time windows (CONT) and during stance phases (PHSS) by intraclass-correlation (ICC), normalised root mean squared error (nRMSE), and statistical parametric mapping. The agreement levels in the sagittal plane were good to excellent (ICC: 0.84-0.98), with low errors (nRMSE: 0.05-0.11). However, accuracy was lower for non-sagittal estimations (frontal ICC: 0.19-0.90, nRMSE: 0.08-0.23; transverse ICC: 0.72-0.94, nRMSE: 0.07-0.17). Accuracy decreased across all planes during PHSS. The proposed approach yields similar or better accuracy compared to previous work while requiring less preprocessing. It provides a viable method for wearable-based assessment of running kinetics in near real-time. Additional data and methods to address inter-individual variability could improve its precision in assessing frontal plane injury risk factors.

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来源期刊

Sports Biomechanics 医学-工程：生物医学

CiteScore

5.70

自引率

9.10%

发文量

135

审稿时长

>12 weeks

期刊介绍： Sports Biomechanics is the Thomson Reuters listed scientific journal of the International Society of Biomechanics in Sports (ISBS). The journal sets out to generate knowledge to improve human performance and reduce the incidence of injury, and to communicate this knowledge to scientists, coaches, clinicians, teachers, and participants. The target performance realms include not only the conventional areas of sports and exercise, but also fundamental motor skills and other highly specialized human movements such as dance (both sport and artistic). Sports Biomechanics is unique in its emphasis on a broad biomechanical spectrum of human performance including, but not limited to, technique, skill acquisition, training, strength and conditioning, exercise, coaching, teaching, equipment, modeling and simulation, measurement, and injury prevention and rehabilitation. As well as maintaining scientific rigour, there is a strong editorial emphasis on ''reader friendliness''. By emphasising the practical implications and applications of research, the journal seeks to benefit practitioners directly. Sports Biomechanics publishes papers in four sections: Original Research, Reviews, Teaching, and Methods and Theoretical Perspectives.