838 research outputs found

    Early diagnosis of frailty: Technological and non-intrusive devices for clinical detection

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    This work analyses different concepts for frailty diagnosis based on affordable standard technology such as smartphones or wearable devices. The goal is to provide ideas that go beyond classical diagnostic tools such as magnetic resonance imaging or tomography, thus changing the paradigm; enabling the detection of frailty without expensive facilities, in an ecological way for both patients and medical staff and even with continuous monitoring. Fried's five-point phenotype model of frailty along with a model based on trials and several classical physical tests were used for device classification. This work provides a starting point for future researchers who will have to try to bridge the gap separating elderly people from technology and medical tests in order to provide feasible, accurate and affordable tools for frailty monitoring for a wide range of users.This work was sponsored by the Spanish Ministry of Science, Innovation and Universities and the European Regional Development Fund (ERDF) across projects RTC-2017-6321-1 AEI/FEDER, UE, TEC2016-76021-C2-2-R AEI/FEDER, UE and PID2019-107270RB-C21/AEI/10.13039/501100011033, UE

    Fifteen years of wireless sensors for balance assessment in neurological disorders

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    Balance impairment is a major mechanism behind falling along with environmental hazards. Under physiological conditions, ageing leads to a progressive decline in balance control per se. Moreover, various neurological disorders further increase the risk of falls by deteriorating specific nervous system functions contributing to balance. Over the last 15 years, significant advancements in technology have provided wearable solutions for balance evaluation and the management of postural instability in patients with neurological disorders. This narrative review aims to address the topic of balance and wireless sensors in several neurological disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, stroke, and other neurodegenerative and acute clinical syndromes. The review discusses the physiological and pathophysiological bases of balance in neurological disorders as well as the traditional and innovative instruments currently available for balance assessment. The technical and clinical perspectives of wearable technologies, as well as current challenges in the field of teleneurology, are also examined

    Wearable sensors system for an improved analysis of freezing of gait in Parkinson's disease using electromyography and inertial signals

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    We propose a wearable sensor system for automatic, continuous and ubiquitous analysis of Freezing of Gait (FOG), in patients affected by Parkinson's disease. FOG is an unpredictable gait disorder with different clinical manifestations, as the trembling and the shuffling-like phenotypes, whose underlying pathophysiology is not fully understood yet. Typical trembling-like subtype features are lack of postural adaptation and abrupt trunk inclination, which in general can increase the fall probability. The targets of this work are detecting the FOG episodes, distinguishing the phenotype and analyzing the muscle activity during and outside FOG, toward a deeper insight in the disorder pathophysiology and the assessment of the fall risk associated to the FOG subtype. To this aim, gyroscopes and surface electromyography integrated in wearable devices sense simultaneously movements and action potentials of antagonist leg muscles. Dedicated algorithms allow the timely detection of the FOG episode and, for the first time, the automatic distinction of the FOG phenotypes, which can enable associating a fall risk to the subtype. Thanks to the possibility of detecting muscles contractions and stretching exactly during FOG, a deeper insight into the pathophysiological underpinnings of the different phenotypes can be achieved, which is an innovative approach with respect to the state of art

    Wearable inertial sensors for human movement analysis

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    Introduction: The present review aims to provide an overview of the most common uses of wearable inertial sensors in the field of clinical human movement analysis.Areas covered: Six main areas of application are analysed: gait analysis, stabilometry, instrumented clinical tests, upper body mobility assessment, daily-life activity monitoring and tremor assessment. Each area is analyzed both from a methodological and applicative point of view. The focus on the methodological approaches is meant to provide an idea of the computational complexity behind a variable/parameter/index of interest so that the reader is aware of the reliability of the approach. The focus on the application is meant to provide a practical guide for advising clinicians on how inertial sensors can help them in their clinical practice.Expert commentary: Less expensive and more easy to use than other systems used in human movement analysis, wearable sensors have evolved to the point that they can be considered ready for being part of routine clinical routine

    Wearables for Movement Analysis in Healthcare

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    Quantitative movement analysis is widely used in clinical practice and research to investigate movement disorders objectively and in a complete way. Conventionally, body segment kinematic and kinetic parameters are measured in gait laboratories using marker-based optoelectronic systems, force plates, and electromyographic systems. Although movement analyses are considered accurate, the availability of specific laboratories, high costs, and dependency on trained users sometimes limit its use in clinical practice. A variety of compact wearable sensors are available today and have allowed researchers and clinicians to pursue applications in which individuals are monitored in their homes and in community settings within different fields of study, such movement analysis. Wearable sensors may thus contribute to the implementation of quantitative movement analyses even during out-patient use to reduce evaluation times and to provide objective, quantifiable data on the patients’ capabilities, unobtrusively and continuously, for clinical purposes

    Recommendations for determining the validity of consumer wearable and smartphone step count: expert statement and checklist of the INTERLIVE network

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    PBJ is supported by the Portuguese Foundation for Science and Technology (SFRH/BPD/115977/2016). WJ is partly funded by Science Foundation Ireland (12/RC/2289_P2). PMG and FBO are supported by grants from the MINECO/FEDER (DEP2016-79512-R) and from the University of Granada, Plan Propio de Investigacion 2016, Excellence actions: Units of Excellence; Scientific Excellence Unit on Exercise and Health (UCEES); Junta de Andalucia, Consejeria de Conocimiento, Investigacion y Universidades and European Regional Development Funds (ref. SOMM17/6107/UGR). JMM is partly funded by Private Stiftung Ewald Marquardt fur Wissenschaft und Technik, Kunst und Kultur. UE and JS are partly funded by the Research Council of Norway (249932/F20). AG is supported a European Research Council Grant (grant number 716657). ELS is supported by TrygFonden (grant number 310081). This research was partly funded by Huawei Technologies, Finland.Consumer wearable and smartphone devices provide an accessible means to objectively measure physical activity (PA) through step counts. With the increasing proliferation of this technology, consumers, practitioners and researchers are interested in leveraging these devices as a means to track and facilitate PA behavioural change. However, while the acceptance of these devices is increasing, the validity of many consumer devices have not been rigorously and transparently evaluated. The Towards Intelligent Health and Well-Being Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives to develop best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice consumer wearable and smartphone step counter validation protocol. A two-step process was used to aggregate data and form a scientific foundation for the development of an optimal and feasible validation protocol: (1) a systematic literature review and (2) additional searches of the wider literature pertaining to factors that may introduce bias during the validation of these devices. The systematic literature review process identified 2897 potential articles, with 85 articles deemed eligible for the final dataset. From the synthesised data, we identified a set of six key domains to be considered during design and reporting of validation studies: target population, criterion measure, index measure, validation conditions, data processing and statistical analysis. Based on these six domains, a set of key variables of interest were identified and a 'basic' and 'advanced' multistage protocol for the validation of consumer wearable and smartphone step counters was developed. The INTERLIVE consortium recommends that the proposed protocol is used when considering the validation of any consumer wearable or smartphone step counter. Checklists have been provided to guide validation protocol development and reporting. The network also provide guidance for future research activities, highlighting the imminent need for the development of feasible alternative 'gold-standard' criterion measures for free-living validation. Adherence to these validation and reporting standards will help ensure methodological and reporting consistency, facilitating comparison between consumer devices. Ultimately, this will ensure that as these devices are integrated into standard medical care, consumers, practitioners, industry and researchers can use this technology safely and to its full potential.Portuguese Foundation for Science and Technology SFRH/BPD/115977/2016Science Foundation IrelandEuropean Commission 12/RC/2289_P2MINECO/FEDER DEP2016-79512-RUniversity of Granada, Plan Propio de Investigacion 2016, Excellence actions: Units of ExcellenceScientific Excellence Unit on Exercise and Health (UCEES)European Commission SOMM17/6107/UGRPrivate Stiftung Ewald Marquardt fur Wissenschaft und Technik, Kunst und KulturResearch Council of Norway 249932/F20European Research Council (ERC) European Commission 716657TrygFonden 310081Huawei TechnologiesJunta de Andaluci

    Inertial Measurement Unit-Based Gait Event Detection in Healthy and Neurological Cohorts: A Walk in the Dark

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    A deep learning (DL)-based network is developed to determine gait events from IMU data from a shank- or foot-worn device. The DL network takes as input the raw IMU data and predicts for each time step the probability that it corresponds to an initial or final contact. The algorithm is validated for walking at different self-selected speeds across multiple neurological diseases and both in clinical research settings and the habitual environment. The algorithms shows a high detection rate for initial and final contacts, and a small time error when compared to reference events obtained with an optical motion capture system or pressure insoles. Based on the excellent performance, it is concluded that the DL algorithm is well suited for continuous long-term monitoring of gait in the habitual environment

    Functional mobility in Parkinson’s disease

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    Introduction: Parkinson’s disease (PD) is the second most common neurodegenerative disease, affecting 1% of the world population over the age of 60. The presence of a large and heterogeneous spectrum of motor and non-motor symptoms, some resistant to levodopa therapy, is usually a major source of disability that affects patients’ daily activities and social participation. Functional mobility (FM) is an outcome that merges the concepts of function with mobility, autonomy, and the accomplishment of daily tasks in different environments. Its use in PD studies is common. However, several aspects associated with its application in PD remain to be defined, hampering a wider use of the concept in clinical practice and the comparison of clinical study results. Aim: This thesis aimed to provide evidence on the appropriateness of the concept of FM in the PD field. A two-fold approach was used to this end: 1) To investigate the clinical and research applicability of the concept of FM in PD; 2) To identify the most suitable clinical and technological outcome measures for evaluating the response of PD patients’ FM to a therapeutic intervention. Methods: A narrative review using the framework of the International Classification of Functioning, Disability, and Health (ICF) was performed to explore the concept of FM when applied to PD. This first study aimed to provide a better understanding of the interaction between PD symptoms, FM, and patients’ daily activities and social participation. To identify and recommend the most suitable outcome measures to assess FM in PD, a systematic review was conducted using the CENTRAL, MEDLINE, Embase, and PEDro databases, from their inception to January 2019. During this review, we also explored the different definitions of FM present in the literature, proposing the one we believed should be established as the definition of FM in the PD field. We then conducted a focus group to explore PD patients' and health professionals’ perspectives on the proposed definition. Part of the scope of the focus group was also to investigate the impact of FM problems on patients’ daily living and the strategies used to deal with this. The study included four focus groups, two with patients (early and advanced disease stages), and two with health professionals (neurologists and physiotherapists). A second systematic review using the CENTRAL, MEDLINE, Embase, and PEDro databases, from their inception to September 2019, was performed to summarize and critically appraise the published evidence on PD spatiotemporal gait parameters. Finally, a pragmatic clinical study was conducted to identify the clinical and technological outcome measures that better predict changes in FM, when patients are submitted to a specialized multidisciplinary program for PD. Results: All the definitions found in an open search of the literature on the FM concept included three key aspects: gait, balance, and transfers. All participants in the focus group study were able to present a spontaneous definition of FM that matched the one used by the authors. All also agreed that FM reflects the difficulties of PD patients in daily life activities. Early-stage PD patients mentioned needing more time to complete their usual tasks, while advanced-stage PD patients considered FM limitations as the main limiting factor of daily activities, especially in medication “OFF” periods. Physiotherapists maintained that the management of PD FM limitations should be a joint work of the multidisciplinary team. For neurologists, FM may better express patients’ perception of their overall health status and may help to adopt a more patient-centered approach. Of the 95 studies included in the systematic review aiming to appraise the outcome measures that have been used to assess FM in PD patients, only one defined the concept of FM. The most frequent terms used as synonyms of FM were mobility, mobility in association with functional activities/performance, motor function, gait-related activity, or balance. In the literature, the Timed Up and Go (TUG) test was the most frequently reported tool used as a single instrument to assess FM in PD. The changes from baseline in the TUG Cognitive test, step length, and free-living step time asymmetry were identified as the best predictors of TUG changes. Conclusion: The information generated by the different studies included in this thesis revealed FM as a useful concept to be adopted in the PD field. FM was shown to be a meaningful outcome (for patients and health professionals), easy to measure, and able to provide more global and ecological information on patients’ daily living performances. Our results support the use of FM for PD assessment and free-living monitoring, as a way to better understand and address patients’ needs. The changes in the TUG Cognitive test, the supervised step length, and the free-living step time asymmetry seem the most suitable outcomes to measure an effect in FM. Future research should focus on determining the severity cut-off for FM changes, the minimal clinical important difference (MCID) for each of these outcome measures and resolve the current obstacles to the widespread use of technological assessments in PD clinical practice and research
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