Knee joint forces (KJF) are biomechanical measures used to infer the load on knee joint structures. The purpose of this study is to develop an artificial neural network (ANN) that estimates KJF during sport movements, based on data obtained by wearable sensors. Thirteen participants were equipped with two inertial measurement units (IMUs) located on the right leg. Participants performed a variety of movements, including linear motions, changes of direction, and jumps. Biomechanical modelling was carried out to determine KJF. An ANN was trained to model the association between the IMU signals and the KJF time series. The ANN-predicted KJF yielded correlation coefficients that ranged from 0.60 to 0.94 (vertical KJF), 0.64 to 0.90 (anterior–posterior KJF) and 0.25 to 0.60 (medial–lateral KJF). The vertical KJF for moderate running showed the highest correlation (0.94 ± 0.33). The summed vertical KJF and peak vertical KJF differed between calculated and predicted KJF across all movements by an average of 5.7% ± 5.9% and 17.0% ± 13.6%, respectively. The vertical and anterior–posterior KJF values showed good agreement between ANN-predicted outcomes and reference KJF across most movements. This study supports the use of wearable sensors in combination with ANN for estimating joint reactions in sports applications.

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Human posture is characterised by inherent body sway which forces the sensory and motor systems to counter the destabilising oscillations. Although the potential of biting to increase postural stability has recently been reported, the mechanisms by which the craniomandibular system (CMS) and the motor systems for human postural control are functionally coupled are not yet fully understood. The purpose of our study was, therefore, to investigate the effect of submaximum biting on postural stability and on the kinematics of the trunk and head. Twelve healthy young adults performed force-controlled biting (FB) and non-biting (NB) during bipedal narrow stance and single-leg stance. Postural stability was quantified on the basis of centre of pressure (COP) displacements, detected by use of a force platform. Trunk and head kinematics were investigated by biomechanical motion analysis, and bite forces were measured using a hydrostatic system. The results revealed that FB significantly improved postural control in terms of reduced COP displacements, providing additional evidence for the functional coupling of the CMS and human posture. Our study also showed, for the first time, that reductions in the sway of the COP were accompanied by reduced trunk and head oscillations, which might be attributable to enhanced trunk stiffness during FB. This physiological response to isometric activation of the masticatory muscles raises questions about the potential of oral motor activity as a strategy to reduce the risk of falls among the elderly or among patients with compromised postural control.