18 research outputs found
Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.
Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems
慣性センサを用いた変形性膝関節症患者の歩行遊脚期の下肢運動学
広島大学(Hiroshima University)博士(保健学)Doctor of Philosophy in Health Sciencedoctora
Characterizing the Variability of Kinematic Outcome Measures and Compensatory Movements using Inertial Measurement Units
Cost-effective wearable sensors to measure movement have gained traction as research and clinical tools. The potential to quantify movement with a portable and inexpensive way could provide benefits to patient populations (e.g. amputees) to supplement or replace current clinical evaluations. For example, characterization of frontal plane kinematic outcome measures is a relevant movement pattern to a complex amputee population. The ability to capture such movements could have important therapeutic opportunities. The current research worked towards characterizing frontal plane compensatory movement patterns with kinematic outcome measures described by inertial measurement units (IMU) data in healthy adults. This was an initial step towards developing a future toolkit that could characterize normal and aberrant movement patterns in clinical populations.
The thesis is comprised of two related studies. The first study set out to evaluate the numerical accuracy of IMU estimated spatial measures when compared to a gold standard system. Six subjects completed six different movement tasks while instrumented with optical motion capture and IMUs. Each movement task probed the accuracy of specific deviations (e.g. vertical deviation). The hypothesis was that outcome measures would be strongly associated (r>0.8) and mean error would not be significantly different from zero and the coefficient of repeatability would be within priori set limits of agreement (±18 mm). Kinematic outcome measures had small mean error bias compared to gold standard measures and range of subject specific mean errors showed minimal differences. Task specific differences were evident when movement patterns exhibit large transverse rotations. These results showed the devices have a level of accuracy that may be suitable to characterize changes in movement patterns clinically.
The second study aimed to utilize the same techniques from study 1 to describe compensatory kinematic outcome measures during a clinical obstacle avoidance task to differentiate between compensatory and normal movement patterns. Twelve subjects wore IMUs bilaterally on the ankles and on the belt above the right hip. An off the shelf orthotic knee brace was used to restrict lower limb knee joint kinematics (reduce range of motion). Participants completed 15 walking trials for three different brace conditions (No Brace, Unlocked Brace, Locked Brace) and two obstacle task conditions (Level Ground Walking and Obstacle Avoidance) to elicit a comparison of normal and compensatory movements. During the walking task, IMUs were able to characterize compensatory movements typical of the amputee population. Lateral deviation of the swinging foot was significantly larger during obstacle crossing with a locked brace compared to no brace. Maximum elevation of the limb was significantly larger while crossing obstacles compared to level ground walking and was precise enough to discern elevation differences of No Brace elevation from both Unlocked and Locked Brace conditions. Hip hiking was also significantly larger in the locked brace obstacle crossing from no brace obstacle crossing. Swing time was longer when the limb was braced and during obstacle crossing when compared to level ground walking. Healthy subjects had no significant changes to double support time compared those exhibited by amputees during walking.
Overall, differences between IMU and gold standard measures are present. Mean error differences are present for certain tasks and criteria for agreeability between devices is not satisfied. Descriptive analysis of low subject mean error ranges across the majority of tasks indicate a potential utility in these measures to distinguish between movement patterns. During the clinical task, when knee mobility was manipulated compensatory movements were significantly different across conditions. This study provides evidence for the utility of IMU devices to support clinical gait analysis with quantifiable measures
Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders
The aging population and the increased prevalence of neurological diseases have raised the issue of gait and balance disorders as a major public concern worldwide. Indeed, gait and balance disorders are responsible for a high healthcare and economic burden on society, thus, requiring new solutions to prevent harmful consequences. Recently, wearable sensors have provided new challenges and opportunities to address this issue through innovative diagnostic and therapeutic strategies. Accordingly, the book “Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders” collects the most up-to-date information about the objective evaluation of gait and balance disorders, by means of wearable biosensors, in patients with various types of neurological diseases, including Parkinson’s disease, multiple sclerosis, stroke, traumatic brain injury, and cerebellar ataxia. By adopting wearable technologies, the sixteen original research articles and reviews included in this book offer an updated overview of the most recent approaches for the objective evaluation of gait and balance disorders
Optimising Assessment and Rehabilitation in People Hospitalised with an Acute Exacerbation of Chronic Obstructive Pulmonary Disease
This research; (i) evaluated the measurement properties of the two-minute walk test (2MWT), including the effect of test repetition, coefficient of repeatability and validity, and compared the cardiorespiratory responses and symptoms reported during the 2MWT and the six-minute walk test, (ii) developed regression equations to estimate the two-minute walk distance and (iii) evaluated the effectiveness of an exercise program in people hospitalised with an AECOPD on exercise capacity, muscle force, functional performance and physical activity
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Technology-assisted healthcare: exploring the use of mobile 3D visualisation technology to augment home-based fall prevention assessments
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonFalls often cause devastating injuries which precipitate hospital and long-term care admission and result in an increased burden on health care services. Fall prevention interventions are used to overcome fall risk factors in an ageing population. There is an increasing need for technology-assisted interventions to reduce health care costs, whilst also lessening the burden that an ageing population increasingly has on health care services. Research efforts have been spent on reducing intrinsic fall risk factors (i.e. functional ability deficits and balance impairments) in the older adult population through the use of technology-assisted interventions, but relatively little effort has been expended on extrinsic risk factors (i.e. unsuitable environmental conditions and lack of assistive equipment use), considering the drive for healthcare outside of the clinical setting into the patients’ home. In the field of occupational therapy, the extrinsic fall-risk assessment process (EFAP) is a prominent preventive intervention used to promote independent living and alleviate fall risk factors via the provision of assistive equipment prescribed for use by patients in their home environment. Currently, paper-based forms with measurement guidance presented in the form of 2D diagrams are used in the EFAP. These indicate the precise points and dimensions on a furniture item that must be measured as part of an assessment for equipment. However, this process involves challenges, such as inappropriate equipment prescribed due to inaccurate measurements being taken and recorded from the misinterpretation of the measurement guidance. This is largely due to the poor visual representation of guidance that is provided by existing paper-based forms, resulting in high levels of equipment abandonment by patients. Consequently, there is a need to overcome the challenges mentioned above by augmenting the limitations of the paper-based approach to visualise measurement guidance for equipment. To this end, this thesis proposes the use of 3D visualisation technology in the form of a novel mobile 3D application (Guidetomeasure) to visualise guidance in a well-perceived manner and support stakeholders with equipment prescriptions. To ensure that the artefact is a viable improvement over its 2D predecessor, it was designed, developed and empirically evaluated with patients and clinicians alike through conducting five user-centred design and experimental studies. A mixed-method analysis was undertaken to establish the design, effectiveness, efficiency and usability of the proposed artefact, compared with conventional approaches used for data collection and equipment prescription. The research findings show that both patients and clinicians suggest that 3D visualisation is a promising development of an alternative tool that contains functionality to overcome existing issues faced in the EFAP. Overall, this research makes a conceptual contribution (secondary) to the research domain and a software artefact (primary) that significantly improves practice, resulting in implications and recommendations for the wider healthcare provision (primary).The Engineering and Physical Sciences Research Council (EPSRC)