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Background:The Clinch Token Transfer Test (C3t) is a bi-manual coin transfer task that incorporates cognitive tasks to add complexity. This study explored the concurrent and convergent validity of the C3t as a simple, objective assessment of impairment that is reflective of disease severity in Huntington's, that is not reliant on clinical expertise for administration. Methods:One-hundred-and-five participants presenting with pre-manifest (n = 16) or manifest (TFC-Stage-1 n = 39; TFC-Stage-2 n = 43; TFC-Stage-3 n = 7) Huntington's disease completed the Unified Huntington's Disease Rating Scale and the C3t at baseline. Of these, thirty-three were followed up after 12 months. Regression was used to estimate baseline individual and composite clinical scores (including cognitive, motor, and functional ability) using baseline C3t scores. Correlations between C3t and clinical scores were assessed using Spearman's R and visually inspected in relation to disease severity using scatterplots. Effect size over 12 months provided an indication of longitudinal behaviour of the C3t in relation to clinical measures. Results: Baseline C3t scores predicted baseline clinical scores to within 9-13% accuracy, being associated with individual and composite clinical scores. Changes in C3t scores over 12 months were small ([Formula: see text] ≤ 0.15) and mirrored the change in clinical scores. Conclusion: The C3t demonstrates promise as a simple, easy to administer, objective outcome measure capable of predicting impairment that is reflective of Huntington's disease severity and offers a viable solution to support remote clinical monitoring. It may also offer utility as a screening tool for recruitment to clinical trials given preliminary indications of association with the prognostic index normed for Huntington's disease.

Objectives Biomechanics is an essential form of measurement in the understanding of the development and progression of osteoarthritis (OA). However, the number of participants in biomechanical studies are often small and there is limited ways to share or combine data from across institutions or studies. This is essential for applying modern machine learning methods, where large, complex datasets can be used to identify patterns in the data. Using these data-driven approaches, it could be possible to better predict the optimal interventions for patients at an early stage, potentially avoiding pain and inappropriate surgery or rehabilitation. In this project we developed a prototype database platform for combining and sharing biomechanics datasets. The database includes methods for importing and standardising data and associated variables, to create a seamless, searchable combined dataset of both healthy and knee OA biomechanics. Methods Data was curated through calls to members of the OATech Network+ (https://www.oatechnetwork.org/). The requirements were 3D motion capture data from previous studies that related to analysing the biomechanics of knee OA, including participants with OA at any stage of progression plus healthy controls. As a minimum we required kinematic data of the lower limbs, plus associated kinetic data (i.e. ground reaction forces). Any additional, complementary data such as EMG could also be provided. Relevant ethical approvals had to be in place that allowed re-use of the data for other research purposes. The datasets were uploaded to a University hosted cloud platform. The database platform was developed using Javascript and hosted on a Windows server, located and managed within the department. Results Three independent datasets were curated following the call to OATech Network+ members. These originated from separate studies collected from biomechanics labs at Cardiff University, Keele University, and Imperial College London. Participants with

Background:The Clinch Token Transfer Test (C3t) is a bi-manual coin transfer task that incorporates cognitive tasks to add complexity. This study explored the concurrent and convergent validity of the C3t as a simple, objective assessment of impairment that is reflective of disease severity in Huntington's, that is not reliant on clinical expertise for administration. Methods:One-hundred-and-five participants presenting with pre-manifest (n = 16) or manifest (TFC-Stage-1 n = 39; TFC-Stage-2 n = 43; TFC-Stage-3 n = 7) Huntington's disease completed the Unified Huntington's Disease Rating Scale and the C3t at baseline. Of these, thirty-three were followed up after 12 months. Regression was used to estimate baseline individual and composite clinical scores (including cognitive, motor, and functional ability) using baseline C3t scores. Correlations between C3t and clinical scores were assessed using Spearman's R and visually inspected in relation to disease severity using scatterplots. Effect size over 12 months provided an indication of longitudinal behaviour of the C3t in relation to clinical measures. Results: Baseline C3t scores predicted baseline clinical scores to within 9-13% accuracy, being associated with individual and composite clinical scores. Changes in C3t scores over 12 months were small ([Formula: see text] ≤ 0.15) and mirrored the change in clinical scores. Conclusion: The C3t demonstrates promise as a simple, easy to administer, objective outcome measure capable of predicting impairment that is reflective of Huntington's disease severity and offers a viable solution to support remote clinical monitoring. It may also offer utility as a screening tool for recruitment to clinical trials given preliminary indications of association with the prognostic index normed for Huntington's disease.

Background: Current tools to measure pain are broadly subjective impressions of the impact of the nociceptive impulse felt by the patient. A direct measure of nociception may offer a more objective indicator. Specifically, movement-induced physiological responses to nociception may offer a useful way to monitor knee OA. In this proof-of-concept study, we evaluated whether integrated biomechanical and physiological sensor datasets could display linked and quantifiable information to a nociceptive stimulus. Method: Following ethical approval, we applied a quantified thermal pain stimulus to a volunteer during stationary standing in a gait lab setting. An inertial measurement unit (IMU) and an electromyography (EMG) lower body marker set were tested and integrated with ground reaction force (GRF) data collection. Galvanic skin response electrodes and skin thermal sensors were manually timestamp linked to the integrated system. Results: The integrated EMG, GRF and IMU data show fluctuations within 0.5 seconds of each other when a thermal pain trigger is applied at several time points during a stationary standing test. Manually timestamped physiology measures displayed increased values during testing for skin conductivity (up to 5 µSiemens, 37% compared to baseline) and skin temperature (up to 0.3˚C, 1% compared to baseline). Discussion: This proof-of-concept study suggests that physiological data mimics biomechanical data in response to a known pain stimuli. While this protocol requires further evaluation as to the measurement parameters, the association of the physiological output to the known pain stimulus suggests the potential development of wearable nociceptive sensors that can measure disease progression and treatment effectiveness.

Background: Current tools to measure pain are broadly subjective impressions of the impact of the nociceptive impulse felt by the patient. A direct measure of nociception may offer a more objective indicator. Specifically, movement-induced physiological responses to nociception may offer a useful way to monitor knee OA. In this proof-of-concept study, we evaluated whether integrated biomechanical and physiological sensor datasets could display linked and quantifiable information to a nociceptive stimulus. Method: Following ethical approval, we applied a quantified thermal pain stimulus to a volunteer during stationary standing in a gait lab setting. An inertial measurement unit (IMU) and an electromyography (EMG) lower body marker set were tested and integrated with ground reaction force (GRF) data collection. Galvanic skin response electrodes and skin thermal sensors were manually timestamp linked to the integrated system. Results: The integrated EMG, GRF and IMU data show fluctuations within 0.5 seconds of each other when a thermal pain trigger is applied at several time points during a stationary standing test. Manually timestamped physiology measures displayed increased values during testing for skin conductivity (up to 5 µSiemens, 37% compared to baseline) and skin temperature (up to 0.3˚C, 1% compared to baseline). Discussion: This proof-of-concept study suggests that physiological data mimics biomechanical data in response to a known pain stimuli. While this protocol requires further evaluation as to the measurement parameters, the association of the physiological output to the known pain stimulus suggests the potential development of wearable nociceptive sensors that can measure disease progression and treatment effectiveness.

This paper details the use of an on body Accelerometer COTS RFID system for use in determining specific therapeutic movements, and the performance of said movements. Conventional methodologies rely on power intensive Bluetooth or Wi-Fi technologies for live communications, but this paper outlines the use of ultra-low power battery assistive passive modes on UHF RFID chips to harness sub-2mW continuous streaming of Accelerometer data.

About 10% of the global population, i.e. about 650 million people, have disabilities [1]. Studies indicate that, of these, some 10% require a wheelchair. Manual wheelchair propulsion is an important form of mobility for those people to become productive members of their communities. The shoulder is a complex mechanism that plays an important role in manual wheelchair propulsion. Better knowledge of upper limb biomechanics during manual wheelchair propulsion can improve understanding of the resulted injuries and lead to improvements in propulsion efficiency. The primary purpose of this study is to investigate the simultaneous shoulder complex kinematics during functional manual wheelchair mobility. A protocol for three-dimensional kinematic measurements of the shoulder complex is presented using six degrees of freedom analysis. Each upper limb is treated as a four segments linked system that consists of trunk, upper arm, forearm and hand. Each segment is considered as a single rigid body. Selected temporal and kinematic parameters over the wheelchair stroke cycle are characterised in all three planes of motion.