Motion analysis (MA) hardware has recently become more accessible; however, protocols have not developed in conjunction. Routine clinical assessment mostly relies on unreliable observational methods. This study aimed to develop an MA protocol for routine clinical use and compare kinematics and reliability to the gold-standard. Ten participants completed 10 over ground walks with a comprehensive marker set (bespoke and gold-standard). Inter/intra-assessor reliability was also compared. Results demonstrated comparable kinematics. Reliability of the bespoke model was lower than the gold standard but higher than observational methods. The bespoke model can be recommended for routine clinical use to assess patient progress and function.

Recently, systems have been developed to improve alignment of unicompartmental knee arthroplasty (UKA) implants, although improvement in function has been difficult to document. The MAKO RIO robotic surgery system has previously shown improvements in in knee flexion during weight acceptance (WA) in comparison to conventional methods at a one year follow up. This study aimed to determine if these improvements remained at five years follow up. Twenty five MAKO and 21 conventional knees were tested using three dimensional gait analysis to measure knee kinematics. Results demonstrated that the MAKO group achieved significantly greater knee flexion in WA than the conventional group which was consistent with results are one year. This could be due to the improved accuracy of prosthesis implantation offered by the MAKO system.

Background: Stroke rehabilitation often uses the motor relearning concept that require patients to perform active practice of skill-specific training and to receive feedback. Treadmill training augmented with real-time visualisation feedback and functional electrical stimulation may have a beneficial synergistic effect on motor recovery. This study aims to determine the feasibility of this kind of enhanced treadmill training for gait rehabilitation among patients after stroke. A system for dynamic visualisation of lower-limb movement based on 3-dimentional motion capture and a computer timed functional electrical stimulation system was developed. Participants received up to 20-min enhanced treadmill training instead of their over-ground gait training once or twice a week for 6 weeks at Coathill hospital, Lanarkshire, United Kingdom. Number of training sessions attended, and training duration were used to assess feasibility. Ankle kinematics in the sagittal plane of walking with and without functional electrical stimulation support of the pre-tibial muscles were also compared and used to confirm the functional electrical stimulation was triggered at the targeted time. Results: Six patients after stroke participated in the study. The majority of participants were male (5/6) with a age range from 30 to 84 years and 4/6 had left hemiplegia. All participants suffered from brain infarction and were at least 3 months after stroke. Number of training sessions attended ranged from 5 to 12. The duration of training sessions ranged from 11 to 20 min. No serious adverse events were reported. The computerised functional electrical stimulation to the pre-tibial muscles was able to reduce plantarflexion angle during the swing phase with statistical significance (p = 0.015 at 80%; p = 0.008 at 90 and 100% of the gait cycle). Conclusions: It is safe and feasible to use treadmill gait training augmented with real-time visual feedback and computer-controlled functional electrical stimulation with patients after stroke in routine clinical practice. Trial registration: NCT03348215. Registered

IntroductionRecent evidence suggests an underlying movement disruption may be a core component of autism spectrum disorder (ASD) and a new, accessible early biomarker. Mobile smart technologies such as iPads contain inertial movement and touch screen sensors capable of recording subsecond movement patterns during gameplay. A previous pilot study employed machine learning analysis of motor patterns recorded from children 3–5 years old. It identified those with ASD from age-matched and gender-matched controls with 93% accuracy, presenting an attractive assessment method suitable for use in the home, clinic or classroom.Methods and analysisThis is a phase III prospective, diagnostic classification study designed according to the Standards for Reporting Diagnostic Accuracy Studies guidelines. Three cohorts are investigated: children typically developing (TD); children with a clinical diagnosis of ASD and children with a diagnosis of another neurodevelopmental disorder (OND) that is not ASD. The study will be completed in Glasgow, UK and Gothenburg, Sweden. The recruitment target is 760 children (280 TD, 280 ASD and 200 OND). Children play two games on the iPad then a third party data acquisition and analysis algorithm (Play.Care, Harimata) will classify the data as positively or negatively associated with ASD. The results are blind until data collection is complete, when the algorithm’s classification will be compared against medical diagnosis. Furthermore, parents of participants in the ASD and OND groups will complete three questionnaires: Strengths and Difficulties Questionnaire; Early Symptomatic Syndromes Eliciting Neurodevelopmental Clinical Examinations Questionnaire and the Adaptive Behavioural Assessment System-3 or Vineland Adaptive Behavior Scales-II. The primary outcome measure is sensitivity and specificity of Play.Care to differentiate ASD children from TD children. Secondary outcomes measures include the accuracy of Play.Care to differentiate ASD children from OND children.Ethics and disseminationThis study was approved by the West of Scotland Research Ethics Service Committee 3 and the University of Strathclyde Ethics Committee. Results will be disseminated in peer-reviewed publications and at international scientific conferences.Trial registration numberNCT03438994

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