Now showing 1 - 10 of 139
  • Publication
    The use of SHIMMER to detect stride time in running gait
    Wireless sensing solutions that provide for accurate long term monitoring of walking and running stride characteristics in a real world environment would be an excellent tool for biomechanics researchers. SHIMMER™ is a small, wireless, low-power inertial sensor with a large storage capacity that facilitates wearable wireless sensing in both connected and disconnected modes. It is a very flexible, multi-sensing device, consisting of a tri-axial accelerometer, with options of add-on daughter boards such as tri-axial gyropscopes, or ECG/EMG sensors. The purpose of this study was to compare the performance of the SHIMMER wireless sensor platform for the determination of heel-strike and stride times, across a range of speeds, to a marker-based motion capture system (CODA, Charnwood Dynamics, UK). Previous studies have shown that the SHIMMER sensor and associated algorithms can successfully calculate these parameters in slow to fast walking speeds, but it has not yet been applied to running.
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  • Publication
    Acute ankle sprain injury alters kinematic and centre of pressure measures of postural control during single limb stance
    Background: Upright single-limb stance (SLS) is maintained via integration of visual, vestibular and somatosensory afferents. The presence of redundancies between these afferents allows the sensorimotor system to simplify a specific task within a number of strategies. Musculoskeletal injury challenges the somatosensory system to reweight distorted sensory afferents. No current investigation has supplemented kinetic analysis of eyes-open and eyes-closed SLS tasks with a kinematic profile of lower limb postural orientation in an acute lateral ankle sprain (LAS) group to assess the adaptive capacity of the sensorimotor system to injury. Objective: To compare centre of pressure (COP) and lower limb postural orientation characteristics of participants with acute LAS to non-injured participants during a SLS task. Design Cross-sectional: Setting University biomechanics laboratory. Participants: 66 participants with acute LAS completed a task of eyes-open SLS on their injured and non-injured limbs (task 1). 23 of these participants successfully completed the SLS task with their eyes closed (task 2). A non-injured control group of nineteen participants completed task 1, with 16 completing task 2. Main outcome measures: 3D kinematics of the hip, knee and ankle joints as well as associated fractal dimension (FD) of the COP path. Results: Between trial analyses of groups revealed significant differences in lower limb kinematics and FD of the COP path for task 2. Post-hoc testing revealed that non-injured control group bilaterally assumed a position of greater hip flexion compared to LAS participants (injured limb=7.41±6.1◦ vs 1.44±4.8◦; non-injured limb=9.59±8.5◦ vs 2.16±5.6◦), with a corollary of greater FD of the COP path (injured limb=1.39±0.16 vs 1.25±0.14; non-injured limb=1.37±0.21 vs 1.23±0.14). Conclusion: Acute LAS causes bilateral impairment in postural control strategies.
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  • Publication
    Acute physiological responses to electrical muscle stimulation in a spinal cord injured man – a case study
    Cardiovascular (CV) disease is a leading cause of death in populations with Spinal Cord Injury (SCI) and is contributed to by a lack of opportunities to engage in physical activity as well as limited motor function [1]. Functional Electrical Stimulation (FES) has been suggested as a novel CV training tool to alleviate this problem associated with SCI by increasing peak oxygen consumption (VO2) and heart rate (HR) [2]. However the use of FES is limited by its effect on muscle fatigue as well as the need for specialist equipment and training. Our research group have devised an electrical muscle stimulation (EMS) training device which has improved CV health in obese and chronic heart failure populations [3], whose symptoms are akin to those of SCI patients with CV symptoms. These results warrant further investigation into this system`s effects on the CV health of people with SCI.
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  • Publication
    Mobile App to Streamline the Development of Wearable Sensor-Based Exercise Biofeedback Systems: System Development and Evaluation
    Background: Biofeedback systems that use inertial measurement units (IMUs) have been shown recently to have the ability toobjectively assess exercise technique. However, there are a number of challenges in developing such systems; vast amounts ofIMU exercise datasets must be collected and manually labeled for each exercise variation, and naturally occurring techniquedeviations may not be well detected. One method of combatting these issues is through the development of personalized exercisetechnique classifiers.Objective: We aimed to create a tablet app for physiotherapists and personal trainers that would automate the development ofpersonalized multiple and single IMU-based exercise biofeedback systems for their clients. We also sought to complete apreliminary investigation of the accuracy of such individualized systems in a real-world evaluation.Methods: A tablet app was developed that automates the key steps in exercise technique classifier creation through synchronizingvideo and IMU data collection, automatic signal processing, data segmentation, data labeling of segmented videos by an exerciseprofessional, automatic feature computation, and classifier creation. Using a personalized single IMU-based classification system,15 volunteers (12 males, 3 females, age: 23.8 [standard deviation, SD 1.8] years, height: 1.79 [SD 0.07] m, body mass: 78.4 [SD9.6] kg) then completed 4 lower limb compound exercises. The real-world accuracy of the systems was evaluated.Results: The tablet app successfully automated the process of creating individualized exercise biofeedback systems. Thepersonalized systems achieved 89.50% (1074/1200) accuracy, with 90.00% (540/600) sensitivity and 89.00% (534/600) specificityfor assessing aberrant and acceptable technique with a single IMU positioned on the left thigh.Conclusions: A tablet app was developed that automates the process required to create a personalized exercise techniqueclassification system. This tool can be applied to any cyclical, repetitive exercise. The personalized classification model displayedexcellent system accuracy even when assessing acute deviations in compound exercises with a single IMU.
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  • Publication
    Vectors and drivers of connected health in Europe: a foundation for integrated care
    Coordinated, integrated care requires connected 'inputs, delivery, management and organization of services related to diagnosis, treatment, care, rehabilitation and health promotion' (Grone & Barbero, 2002). Connected health (CH) offers a key building block as a 'paradigm shift, looking after the individual and community health in a process that speaks to the health journey of the person, through the entire lifespan, leveraging a variety of technologies to do so”' (ENJECT, 2016). However, CH is failing to reach its full potential – and therefore failing in its contribution to the realization of integrated care. We conducted a multi-disciplinary literature review across business, technology and healthcare journals, triangulated with a survey of CH experts from academia, industry and clinical settings representing 19 European countries (ENJECT, COST Action TD1405).
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  • Publication
    An investigation into the effects of neuromuscular electrical stimulation exercise in type 2 diabetes : a case study
    Exercise is a vital component in the management and prevention of type 2 diabetes (T2D). Both the American College of Sports Medicine (ACSM) and the American Diabetes Association (ADA) advocate exercise as a treatment method for T2D. However, given the benefits of engaging in physical activity, many T2D patients are often unable to partake in physical activity secondary to complications of their diabetes or other musculoskeletal problems. Neuromuscular electrical stimulation (NMES) exercise is a likely alternative for diabetic individuals who face barriers to physical activity. NMES has received much attention in recent years as a new form of inducing exercise. The ability of NMES to stimulate innervated muscle has resulted in it’s use as a training tool for individuals without neuromuscular pathology. Banerjee and colleagues showed that prolonged NMES exercise in sedentary adults resulted in significant improvements in maximal aerobic capacity, muscle strength and capacity for physical activity. The aim of this case study was to investigate the use of NMES exercise in T2D.
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  • Publication
    Evaluating the use of machine learning in the assessment of joint angle using a single inertial sensor
    Introduction: Joint angle measurement is an important objective marker in rehabilitation. Inertial measurement units may provide an accurate and reliable method of joint angle assessment. The objective of this study was to assess whether a single sensor with the application of machine learning algorithms could accurately measure hip and knee joint angle, and investigate the effect of inertial measurement unit orientation algorithms and person-specific variables on accuracy. Methods: Fourteen healthy participants completed eight rehabilitation exercises with kinematic data captured by a 3D motion capture system, used as the reference standard, and a wearable inertial measurement unit. Joint angle was calculated from the single inertial measurement unit using four machine learning models, and was compared to the reference standard to evaluate accuracy. Results: Average root-mean-squared error for the best performing algorithms across all exercises was 4.81 (SD ¼ 1.89). The use of an inertial measurement unit orientation algorithm as a pre-processing step improved accuracy; however, the addition of person-specific variables increased error with average RMSE 4.99 (SD ¼ 1.83). Conclusions: Hip and knee joint angle can be measured with a good degree of accuracy from a single inertial measurement unit using machine learning. This offers the ability to monitor and record dynamic joint angle with a single sensor outside of the clinic.
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  • Publication
    An interactive exercise biofeedback Android application utilizing a single inertial measurement unit to support joint replacement rehabilitation
    Boomerang Ortho is an Android application developed with the aim to better support patients in their exercise rehabilitation program following total knee replacement. The use of a single inertial measurement unit (IMU) attached to the lower leg allows for classification of exercise technique, real-time biofeedback, and both self and remote monitoring of patient data. The prototype application for demonstration is currently undergoing pilot testing prior to an assessment of impact on clinical outcome.
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  • Publication
    Wearable sensing and mobile devices: the future of post-concussion monitoring?
    In the past decade, concussion has received large amounts of attention in public, medical and research circles. While our understanding of the nature and management of concussion has greatly improved, there are still major limitations which need to be addressed surrounding the identification of the injury, determining when an individual is safe to return to normal activity, and what factors may contribute to the development of post-concussion syndrome (PCS).The current model of concussion management involves a triage evaluation in the acute stage of injury, focusing on the classic signs and symptoms of concussion. Next, the clinician attempts to evaluate key components of cerebral function through clinical symptom evaluation, and traditional assessments of motor and neurocognitive function [1]. The development of the sports concussion assessment tool (SCAT) saw a massive leap forward in the strategies employed in the management of concussion, as it acknowledged the multifactorial nature of concussion, and provided a standardised means for clinicians to assess the many domains of cerebral function [2]. While these methods have demonstrated some promise in the acute stage, they are not designed for serial monitoring (particularly in instances where PCS develops) [3], and provide us with very little clinically relevant information that can assist clinicians in the return to learn/ sport/ performance process.
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  • Publication
    Objective quantification of a clinical dynamic balance assessment
    Objective: To investigate whether addition of inertial sensor data can provide additional insight into the nature of postural stability deficits during a clinical dynamic balance assessment, with a view to enhancing accuracy of post-concussion monitoring protocols. Design: Descriptive laboratory study. Setting: University performance laboratory. Participants: Fifteen physically active adults (age 234 years, height 1758 cm, weight 67.58 kg). Interventions: An inertial measurement unit (IMU) was mounted at the level of the 4th lumbar vertebra. Subjects completed repeated Y-Balance tests (YBT) 10 minutes and immediately prior to a modified 60 second Wingate anaerobic fatiguing test. Post-fatigue YBTs were completed immediately following the test, and at 10 and 20 minutes.Outcome measures: Normalised YBT reach distances, and IMU derived RMS acceleration, velocity and angular velocity. Main results: Prior to the fatiguing intervention, participants demonstrated excellent stability/reliability for all reach directions (Intra-class correlation coefficient 0.872-0.994). Significantly lower reach distances (P<0.05) were observed immediately post-fatigue for the postero-medial and postero-lateral, but not anterior reach direction. Observed deficits returned to pre-fatigue levels by 10 minutes. However, IMU derived measures of postural stability remained significantly reduced (P<0.05) for up to 20 minute post-fatigue. Conclusions: These results demonstrate the ability of both traditional YBT reach distances and inertial sensor data to detect centrally driven postural stability deficits. However, the inertial sensor provided a greater degree of granularity in characterising the nature of these postural stability deficits. This suggests that addition of IMUs to clinical balance measurement tests/protocols may better detect deficits associated with concussion.
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