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The finite element method has been used with considerable success to simulate the behaviour of various joints such as the hip, knee and shoulder. It has had less impact on more complicated joints such as the wrist and the ankle. Previously published finite element studies on these multi-bone joints have needed to introduce un-physiological boundary conditions in order to establish numerical convergence of the model simulation. That is necessary since the stabilizing soft tissue mechanism of these joints is usually too elaborate in order to be fully included both anatomically and with regard to material properties. This paper looks at the methodology of creating a finite element model of such a joint focussing on the wrist and the effects additional constraining has on the solution of the model. The study shows that by investigating the effects each of the constraints, a better understanding on the nature of the stabilizing mechanisms of these joints can be achieved.

Characterisation of free-living physical activity requires the use of validated and reliable monitors. This study reports an evaluation of the validity and reliability of the activPAL3 monitor for the detection of posture and stepping in both adults and young people. Twenty adults (median 27.6y; IQR22.6y) and 8 young people (12.0y; IQR4.1y) performed standardised activities and activities of daily living (ADL) incorporating sedentary, upright and stepping activity. Agreement, specificity and positive predictive value were calculated between activPAL3 outcomes and the gold-standard of video observation. Inter-device reliability was calculated between 4 monitors. Sedentary and upright times for standardised activities were within ±5% of video observation as was step count (excluding jogging) for both adults and young people. Jogging step detection accuracy reduced with increasing cadence >150stepsmin(-1). For ADLs, sensitivity to stepping was very low for adults (40.4%) but higher for young people (76.1%). Inter-device reliability was either good (ICC(1,1)>0.75) or excellent (ICC(1,1)>0.90) for all outcomes. An excellent level of detection of standardised postures was demonstrated by the activPAL3. Postures such as seat-perching, kneeling and crouching were misclassified when compared to video observation. The activPAL3 appeared to accurately detect 'purposeful' stepping during ADL, but detection of smaller stepping movements was poor. Small variations in outcomes between monitors indicated that differences in monitor placement or hardware may affect outcomes. In general, the detection of posture and purposeful stepping with the activPAL3 was excellent indicating that it is a suitable monitor for characterising free-living posture and purposeful stepping activity in healthy adults and young people.

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