Gait disturbances as specific predictive markers of the first fall onset in elderly people: a two-year prospective observational study

Falls are common in the elderly, and potentially result in injury and disability. Thus, preventing falls as soon as possible in older adults is a public health priority, yet there is no specific marker that is predictive of the first fall onset. We hypothesized that gait features should be the most relevant variables for predicting the first fall. Clinical baseline characteristics (e.g., gender, cognitive function) were assessed in 259 home-dwelling people aged 66 to 75 that had never fallen. Likewise, global kinetic behavior of gait was recorded from 22 variables in 1036 walking tests with an accelerometric gait analysis system. Afterward, monthly telephone monitoring reported the date of the first fall over 24 months. A principal components analysis was used to assess the relationship between gait variables and fall status in four groups: non-fallers, fallers from 0 to 6 months, fallers from 6 to 12 months and fallers from 12 to 24 months. The association of significant principal components (PC) with an increased risk of first fall was then evaluated using the area under the Receiver Operator Characteristic Curve (ROC). No effect of clinical confounding variables was shown as a function of groups. An eigenvalue decomposition of the correlation matrix identified a large statistical PC1 (termed "Global kinetics of gait pattern"), which accounted for 36.7% of total variance. Principal component loadings also revealed a PC2 (12.6% of total variance), related to the "Global gait regularity." Subsequent ANOVAs showed that only PC1 discriminated the fall status during the first 6 months, while PC2 discriminated the first fall onset between 6 and 12 months. After one year, any PC was associated with falls. These results were bolstered by the ROC analyses, showing good predictive models of the first fall during the first six months or from 6 to 12 months. Overall, these findings suggest that the performance of a standardized walking test at least once a year is essential for fall prevention

Objective assessment of movement disabilities using wearable sensors

The research presents a series of comprehensive analyses based on inertial measurements obtained from wearable sensors to quantitatively describe and assess human kinematic performance in certain tasks that are most related to daily life activities. This is not only a direct application of human movement analysis but also very pivotal in assessing the progression of patients undergoing rehabilitation services. Moreover, the detailed analysis will provide clinicians with greater insights to capture movement disorders and unique ataxic features regarding axial abnormalities which are not directly observed by the clinicians

Dynamic Simulations and Data Mining of Single-Leg Jump Landing: Implications for Anterior Cruciate Ligament Injury Prevention

It is estimated that 400,000 anterior cruciate ligament (ACL) injuries occur in the United States each year with the cost of ACL reconstruction surgery and rehabilitation exceeding $1 billion annually. The majority of ACL injuries are non-contact injuries occurring during cutting and jump landing movements. Because the majority of the injuries are non-contact injuries there is the potential to develop programs to reduce the risk of injury. Given our understanding of the joint kinematics and kinetics that place an individual at high risk for ACL, researchers have developed neuromuscular training programs that focus on improving muscle function in order to help the muscles support and stabilize the knee during the dynamic movements that increase the strain on the ACL. Yet, despite the implementation of these neuromuscular-based ACL injury training intervention programs ACL rates continue to rise. Thus the objective of this dissertation is to determine the cause and effect relationship between joint biomechanics and muscle function with respect ACL injury. There are four studies in this dissertation. The first two studies rely heavily on the development of subject-specific musculoskeletal models to analyze muscle contribution during single-leg jump landing. These studies will generate forward dynamic simulations to estimate muscle force production and contribution to movement. The results of these studies will aid in the development of muscle-targeted ACL injury training intervention programs. The last two studies will employ data mining techniques; such as, principal component analysis (PCA) and wavelet analysis along with stability methods from control theory, to evaluate an individual’s risk of ACL injury and determine how muscle function differs for individuals at varying levels of injury risk. The goal will be to use this information to develop a more robust ACL injury prescreening tool. The use of both dynamic simulations and data mining techniques provides a unique approach to investigating the relationship between joint biomechanics and muscle function with respect to ACL injury. And this approach has the potential to gain much needed insight about the underlying mechanism of ACL injury and help progress ACL research forward

THE EFFECTS OF AGING ON MULTIPLE POSTURAL MUSCLE CONTROL AND POSTURAL SWAY BEHAVIOR

Episodes of instability and falls in the elderly represent a major public health concern. The lack of scientific information about the effects of age-related changes on neurophysiological mechanisms of postural control has limited the advance in the field of fall prevention and rehabilitation of balance disorders. The overall goal of this dissertation was to investigate the effects of aging on postural control. Considering the progressive non-homogeneous deterioration of aging physiological systems, a series of five experimental studies, with healthy young and healthy nonfaller older adults performing upright stance tasks, explored three main hypotheses: (1) intermuscular coherence analysis is able to detect signs of intermuscular synchronization at lower frequency bands as one of the strategies used by the Central Nervous System to control upright stance; (2) aging is associated with a reorganization of correlated neural inputs controlling postural muscles; and (3) aging is associated with changes in body sway behavior. The first three studies corroborated the use of intermuscular coherence analysis to investigate the formation of correlated neural inputs forming postural muscle synergies during upright stance. The fourth study revealed an age-related reorganization of the distribution and strength of correlated neural inputs to multiple postural muscles. Healthy nonfaller older adults presented stronger levels of synchronization, within 0–10 Hz, for three distinct muscle groups: anterior, posterior, and antagonist muscle groups. The fifth study investigated age-related changes on postural sway using traditional and novel postural indices extracted from the center of pressure coordinates. Although the functional base support is preserved in healthy nonfaller older adults, these seniors revealed a larger, faster, shakier, and more irregular pattern of body sway compared to healthy young adults. In addition, age-related changes on supraspinal mechanisms, spinal reflexes, and intrinsic mechanical properties of muscles and joints involved in postural control were observed by changes in both rambling and trembling components of the postural sway. Findings reported here provide valuable information regarding compensatory mechanisms adopted by healthy nonfaller older adults to control upright stance. Together, these findings suggest an age-related reorganization of correlated neural inputs controlling multiple postural muscles, accompanied by changes in body sway behavior

The influence of musculoskeletal pain disorders on muscle synergies—A systematic review

Background Musculoskeletal (MSK) pain disorders represent a group of highly prevalent and often disabling conditions. Investigating the structure of motor variability in response to pain may reveal novel motor impairment mechanisms that may lead to enhanced management of motor dysfunction associated with MSK pain disorders. This review aims to systematically synthesize the evidence on the influence of MSK pain disorders on muscle synergies. Methods Nine electronic databases were searched using Medical Subject Headings and keywords describing pain, electromyography and synergies. Relevant characteristics of included studies were extracted and assessed for generalizability and risk of bias. Due to the significant heterogeneity, a qualitative synthesis of the results was performed. Results The search resulted in a total of 1312 hits, of which seven articles were deemed eligible. There was unclear consistency that pain reduced the number of muscle synergies. There were low consistencies of evidence that the synergy vector (W weights) and activation coefficient (C weights) differed in painful compared to asymptomatic conditions. There was a high consistency that muscle synergies were dissimilar between painful and asymptomatic conditions. Conclusions MSK pain alters the structure of variability in muscle control, although its specific nature remains unclear. Greater consistency in muscle synergy analysis may be achieved with appropriate selection of muscles assessed and ensuring consistent achievement of motor task outcomes. Synergy analysis is a promising method to reveal novel understandings of altered motor control, which may facilitate the assessment and treatment of MSK pain disorders

A Participative Approach for Objective and Subjective Evaluation of Seat Discomfort and User Interface Usability

The main aim of the work is the objective and subjective evaluation of two aspects of the interaction user-product, the seating discomfort and the user interface usability, relevant to industrial design, by using innovative methodologies for generating interpretative and predictive models that allowed the development of analysis strategies useful to improve the satisfaction of use of the types of industrial products considered. On the first aspect investigated, research in the field of medicine and epidemiology has shown that, over the past decades, the incidence of work-related musculoskeletal disorders (WMSDs) has considerably increased due to sedentary modern lifestyle, closely related to prolonged period of sitting. The importance of good office seating design in improving human wellness, greatly motivates the interest of specialized literature in topics related to the investigation of the biomechanical aspects of sitting and their effect on perceived discomfort. Typically discomfort assessment is realized on the basis of subjective evaluations and/or postural analysis by the interface pressures. In such context, the experimental sessions and the related data analysis were aimed to investigating on three critical aspects of seat discomfort assessment: 1) the relationship between subjective and objective measures of seat discomfort; 2) gender-based differences in seat interface pressure distribution; 3) discriminant effectiveness of indexes based on seat interface pressure. On the second aspect investigated, it's helpful to recognize that, today, design team can speed up the process of managing information related to design process by adopting digital pattern tools. These tools, as Knowledge Based Engineering (KBE) systems, can assist engineers in capture and re-use the multidisciplinary knowledge in an integrated way, in order to reduce time and cost of designing, to automate repetitive tasks and to support activities in conceptual design. The KBE analyzed in this study is a new digital pattern tool that supports the designers of automotive gearboxes. In such context, the research has focused on the evaluation of interface usability that represents a critical point in the development of a KBE system to demonstrate an effective reduction in the time and cost of designing and increased satisfaction in its use. The methods used for the two aspects studied are both theoretical and experimental and can be summarized in four main steps: 1) developmentofparticipativeprotocolsandexecutionofexperimentalsessionswith collecting of objective measures related to the interaction user-product and subjective measures related to user perceptions; 2) organization, classification and synthesis of experimental data collected by using techniques of descriptive statistics; 3) definition of interpretative and predictive models of phenomena investigated including by developing synthetic indexes, by using techniques of multivariate and multicriteria analysis; 4) statisticalvalidationofthesemodelsandindexes. The main results achieved concern the assessment of user-product interaction for different types of industrial products where such evaluation is essential. The outcomes are originals because they allowed to find the factors that had most influence on case studies and to develop synthetic indexes useful for identify some critical issues related use. Statistical data analysis provided new information relating to phenomena examined. Furthermore, the proposed data analysis strategies can be easily adapted to other experimental contexts, involving different target populations, and could have important effects in the industrial field, because they allow the reduction of design time (with obvious consequences on cost) and improvement of products in terms of end-user satisfaction