Craig Childs

Accurate measurement of muscle belly length in the motion analysis laboratory: potential for the assessment of contracture

Two-dimensional ultrasound imaging was combined with motion analysis technology to measure distances between remote anatomical landmarks. The length of the belly of the medial gastrocnemius muscle in five normal adults (nine limbs) was estimated using this technique. Our results in vivo were similar to the reported data for the lengths of muscles in cadavers, and were consistent with the expected relationship between muscle belly length and ankle joint angle. Experiments in vitro demonstrated that the accuracy of the device was better than 2 mm over 20 cm. Measurements on the same subject on different occasions showed that the results were repeatable in vivo. Rendering of the reconstructed volume of a foam phantom gave results comparable to photographic images. This validated technique could be used to measure muscle lengths in children with spastic cerebral palsy and indicate which muscles had fixed shortening, and to what extent.

Barefoot and shod walking in virtual reality environment with Oxford foot model

Introduction and Objectives: The Oxford Foot Model (OFM) [1] was developed to get accurate measurement of foot movement during gait as the bone pin method [2] is not practical for most clinical situations. It has been validated in adults [3] and children [4]. However, since barefoot walking on a treadmill is not recommended there is a question over whether the OFM can be usefully applied in facilities such as the Motek CAREN (Computer Assisted Rehabilitation Environment - motekmedical.com). Consequently, there is an interest to see if applying OFM markers to shoes can give useful results when measuring human walking on treadmills. This study looks at the differences in measurements using the OFM between walking over-ground (barefoot and with shoes) and on a treadmill (with shoes). Methods: Nine boys (mean age 13.5±0.5yrs, height 1.59±0.09m, mass 47.8±8.3kg) were recruited. Retro-reflective markers were attached bilaterally following the Plug-in-Gait lower limb and OFM models. The over-ground (barefoot and with shoes) trials were recorded in a standard gait laboratory (12 camera Vicon T-Series). Barefoot trials were performed first to minimise the need to reattach markers. The treadmill walking trials were recorded in the CAREN immediately after the over-ground trials (12 camera Vicon Bonita10). The treadmill speed was set to match the speed of over-ground walking in the gait laboratory. Gait events were determined from force plate contacts. All the boys wore light indoor training shoes. Data was captured using Vicon Nexus 1.8.5 and processed using Plug in Gait and OFM models in Nexus 2.1. Results: There was no difference in ankle kinematics between over-ground (barefoot and with shoes) and on a treadmill (with shoes). Although Forefoot-Hindfoot angles were comparable to the literature in the barefoot condition, this was not the case with shoes (Table 1). Barefoot, there was a steady dorsiflexing motion throughout stance until push off which was signified by a rapid plantar-flexing motion. With shoes on, the same model segments show rapid dorsiflexion, then plantar flexion during early stance followed by neutral position held until push-off. Conclusion: Reinschmidt and colleagues [2] reported that the shape of the calcaneal motion curves was similar for shoe mounted markers and bone markers, but that the shoe-mounted markers overestimated joint angles. In this study, the shape of the curves was quite different.Stoichiometric indirect calorimetry is the most commonly used method for assessing the oxidation of fatty acids (FAO) and carbohydrates (CHO). It relies on gaseous exchange measurements of oxygen uptake (VO2), carbon dioxide production (VCO2), and respiratory exchange ratio (RER) for accurate estimations of FAO and CHO. During exercise protein utilization contributes minimally compared with FAO and CHO contribution. Hence, common mathematical estimations are based on FAO and CHO relative contribution at various exercise intensity domains. The utilization of FAO predominates at low exercise intensities, and its relative contribution gradually decreases as exercise intensity increase in favour of CHO contribution. Higher exercise intensities beyond RER ≥1 reflect an excess non-oxidative CO2 from bicarbonate buffering, which further elevates VCO2 and caused an overestimated CHO and underestimated FAO. Therefore, detecting meaningful effects on FAO is often measured below the severe exercise intensity domain and corresponds to exercise intensities below approximately 85% of maximal VO2 (VO2 max). The most common diagnostic indices derived from FAO, CHO and corresponding power output include: 1) maximal fat oxidation (MFO), thought to correspond to approximately 30-75% of VO2 max, and is defined as the power output or exercise intensity at which FAO becomes maximal. 2) the cross-over point (COP), defined as the power output at which energy expenditure at which energy derived from CHO predominates over that from FAO. Prolonged single intensity, testing protocols have long been shown to provide a valid estimate of FAO and CHO because they allow a steady state attainment for the gaseous exchange attainment. However, they require several laboratory visits, and so they can be less practical compared with the incremental exercise protocols commonly being used. However, it is important that incremental protocols consider the selection of an appropriate initial workload, stage increment, and stage duration. The reliability of metabolic exercise testing may also be affected by exercise testing modality (e.g. cycling vs. running or walking protocols), or cadence (e.g. cycling at fast vs. low cadence), primarily due to the effects on muscle recruitment patterns. Selecting an appropriate respiratory sampling and averaging method is equally important to prevent overor under-estimation of FAO and CHO and related estimations. Valid and reliable exercise testing protocols are devised individually because of the numerous factors that affect human substrate metabolism, including muscle glycogen content and activity, preceding diet, and muscle fibre composition, daily physical activity levels, aerobic capacity, gender and exercise intensity and duration. To conclude, Short Communication