In order for gait analysis to be established as part of routine clinical diagnoses, an accurate, flexible and user-friendly motion capture system is required. Commonly used optical, mechanical and acoustic systems offer acceptable accuracy and repeatability, but are often expensive and restricted to laboratory use. Inertial motion capture has seen great innovation in the last few years, but the technology is not yet considered mature enough for clinical gait analysis. In this paper we compare the kinematic reliability of inertial motion capture with optical motion capture during routine gait studies of eight able-bodied subjects. The root mean squared, RMS, and coefficient of correlation, R, was used to compare data sets. Saggital plane joint angles in the knee and hip compared very well. Corresponding transverse and frontal plane values were moderately accurate. The ankle joint angles calculated from the two systems were less accurate. This was believed to be due to the use of different rotation axis orientations used for calculation of angular rotations.

BackgroundPre-eclampsia is one of the leading causes of maternal death and morbidity in low-resource countries due to delays in case identification and a shortage of health workers trained to manage the disorder. Pre-eclampsia Integrated Estimate of RiSk (PIERS) on the Move (PotM) is a low cost, easy-to-use, mobile health (mHealth) platform that has been created to aid health workers in making decisions around the management of hypertensive pregnant women. PotM combines two previously successful innovations into a mHealth app: the miniPIERS risk assessment model and the Phone Oximeter.ObjectiveThe aim of this study was to assess the usability of PotM (with mid-level health workers) for iteratively refining the system.MethodsDevelopment of the PotM user interface involved usability testing with target end-users in South Africa. Users were asked to complete clinical scenario tasks, speaking aloud to give feedback on the interface and then complete a questionnaire. The tool was then evaluated in a pilot clinical evaluation in Tygerberg Hospital, Cape Town.ResultsAfter ethical approval and informed consent, 37 nurses and midwives evaluated the tool. During Study 1, major issues in the functionality of the touch-screen keyboard and date scroll wheels were identified (total errors n=212); during Study 2 major improvements in navigation of the app were suggested (total errors n=144). Overall, users felt the app was usable using the Computer Systems Usability Questionnaire; median (range) values for Study 1 = 2 (1-6) and Study 2 = 1 (1-7). To demonstrate feasibility, PotM was used by one research nurse for the pilot clinical study. In total, more than 500 evaluations were performed on more than 200 patients. The median (interquartile range) time to complete an evaluation was 4 min 55 sec (3 min 25 sec to 6 min 56 sec).ConclusionsBy including target end-users in the design and evaluation of PotM, we have developed an app that can be easily integrated into health care settings in low- and middle-income countries. Usability problems were often related to mobile phone features (eg, scroll wheels, touch screen use). Larger scale evaluation of the clinical impact of this tool is underway.

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BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder with a worldwide prevalence of 1–2%. In low-resource environments, in particular, early identification and diagnosis is a significant challenge. Therefore, there is a great demand for ‘language-free, culturally fair’ low-cost screening tools for ASD that do not require highly trained professionals. Electroencephalography (EEG) has seen growing interest as an investigational tool for biomarker development in ASD and neurodevelopmental disorders. One of the key challenges is the identification of appropriate multivariate, next-generation analytical methodologies that can characterise the complex, nonlinear dynamics of neural networks in the brain, mindful of technical and demographic confounders that may influence biomarker findings. The aim of this study was to evaluate the robustness of recurrence quantification analysis (RQA) as a potential biomarker for ASD using a systematic methodological exploration of a range of potential technical and demographic confounders.MethodsRQA feature extraction was performed on continuous 5-second segments of resting state EEG (rsEEG) data and linear and nonlinear classifiers were tested. Data analysis progressed from a full sample of 16 ASD and 46 typically developing (TD) individuals (age 0–18 years, 4802 EEG segments), to a subsample of 16 ASD and 19 TD children (age 0–6 years, 1874 segments), to an age-matched sample of 7 ASD and 7 TD children (age 2–6 years, 666 segments) to prevent sample bias and to avoid misinterpretation of the classification results attributable to technical and demographic confounders. A clinical scenario of diagnosing an unseen subject was simulated using a leave-one-subject-out classification approach.ResultsIn the age-matched sample, leave-one-subject-out classification with a nonlinear support vector machine classifier showed 92.9% accuracy, 100% sensitivity and 85.7% specificity in differentiating ASD from TD. Age, sex, intellectual ability and the number of training and test segments per group were identified as possible demographic and technical confounders. Consistent repeatability, i.e. the correct identification of all segments per subject, was found to be a challenge.ConclusionsRQA of rsEEG was an accurate classifier of ASD in an age-matched sample, suggesting the potential of this approach for global screening in ASD. However, this study also showed experimentally how a range of technical challenges and demographic confounders can skew results, and highlights the importance of probing for these in future studies. We recommend validation of this methodology in a large and well-matched sample of infants and children, preferably in a low- and middle-income setting.

SUMMARYOrthopaedic shoeing applied for disorders such as navicular disease is mostly evaluated on hard track surfaces, but very often horses are ridden only on soft tracks. To compare the effects of normal shoes, eggbar shoes, and shoes with heel wedges (5 degrees) on the kinematics of the distal forelimb on hard and soft track surfaces, eleven sound Dutch Warmblood horses were led across three different tracks (an asphalt, a fibre/sand mix (= Agterberg®), and a pure sand track) with three different shoe types (a normal shoe, an eggbar shoe, and a shoe with heel wedges). The hoof rotation and the maximal extension of the fetlock joint at midstance period were recorded by an infrared-light based gait analysis system (ProReflexe) at walk and at trot. Statistical analysis revealed significant effects of track and shoe type, and a shoe-track interaction (p<0.05). On soft track surfaces, the equilibrium of the distal forelimb dictated a 1.5-4 degrees forward rotation of the normal or eggbar shod foot, the most on a sand track. The wedge effect on hoof rotation, however, was always significantly greater, but similar to that on the hard track surface (5 degrees forward rotation). The maximal fetlock extension was less on a soft surface, in particular on the sand track (p<0.05). This decrease was most pronounced when the horses were shod with heel wedges and was least pronounced with normal shoes. In conclusion, in particular the sand track allows a forward rotation of the hoof and thus relief of pressure in the navicular area, and a decrease in maximal fetlock extension and thus unloading of the fetlock joint. The extra forward rotation of the hoof induced by heel wedges on hard tracks was almost the same on soft track surfaces. Eggbars and fibre/sand mix tracks have intermediate effects on unloading of the distal forelimb.