501 research outputs found
Effects of Direction Time Constraints and Walking Speed on Turn Strategies and Gait Adaptations in Healthy Older and Young Adults
Hip fractures can be life-threatening, debilitating, and costly. The odds for hip fracture increases from impact of sideways falls. While turning has been strongly associated with hip fracture & sideways falls, the distinction between the risks for walking-turns as opposed to low-velocity in-place turning is not clear. The present study sought to fill a gap as previous research had not compared walking-turn performance in young & healthy older adults at low-fall risk within the same study and response-conditions of speed interacting with direction-cue time constraints. Spatial-temporal variables representative of AP braking/propulsion (i.e. stride-length & speed) & ML stability (left/right H-H BOS) were collected with the Gaitrite upon approach of a turning zone whose entrance width was just 73 cm; and turn-strategy categorical data for stable wide-BOS step-turns, biomechanically challenging narrow-BOS spin-turns, and combined subtypes of mixed-turns either of the “extra-step” variety representative of an AP stability/braking issue or “small-amplitude” variety representative of a ML stability/balance issue were captured on video. Mixed-ANOVA of gait measures for AP propulsion/braking revealed no age-group differences in speed despite a trend for less of a fast-pace increase in elderly stride-length, yet similar anticipatory slowing and shorter strides approaching turns. Measures of ML stability revealed similar anticipatory widening of right BOS approaching turns, and a three-way interaction showed both had similar anticipatory narrowing of left BOS when approaching turns at fast-pace and similar reactive narrowing of left BOS following an unexpected turn-cue at preferred pace. Loglinear analysis of turn-strategies revealed no age-related associations as both preferred mixed-turns the least. At fast speeds preference for spin-turns decreased, yet when late-cued preference for both step-turns and spin-turns decreased 5.5-fold & 4.0-fold, respectively, indicating other factors besides biomechanical. Furthermore, the standardized residual reached significance for the elderly mixed-turns cell at the most constrained fast-speed*late-cue response-condition, with the “extra-step” sub-type contributing greatest possibly implying an AP rather than ML stability issue. The findings suggest that when approaching turns across an interaction of response-time conditions, healthy older adults show similar anticipatory/reactive gait adaptations and turn-strategy preferences with regards to AP propulsion/deceleration and ML stability/balance. In conclusion, within study limits, fall-prevention gait-training for healthy elderly with low-fall-risk and no age-related speed declines, in addition to addressing important ML stability issues of turn execution, are best served by not losing sight of the fundamental prerequisite to arrest forward momentum upon approach, and being inclusive of spin-turns for their ML space-efficiency
Effects of Direction Time Constraints and Walking Speed on Turn Strategies and Gait Adaptations in Healthy Older and Young Adults
Hip fractures can be life-threatening, debilitating, and costly. The odds for hip fracture increases from impact of sideways falls. While turning has been strongly associated with hip fracture & sideways falls, the distinction between the risks for walking-turns as opposed to low-velocity in-place turning is not clear. The present study sought to fill a gap as previous research had not compared walking-turn performance in young & healthy older adults at low-fall risk within the same study and response-conditions of speed interacting with direction-cue time constraints. Spatial-temporal variables representative of AP braking/propulsion (i.e. stride-length & speed) & ML stability (left/right H-H BOS) were collected with the Gaitrite upon approach of a turning zone whose entrance width was just 73 cm; and turn-strategy categorical data for stable wide-BOS step-turns, biomechanically challenging narrow-BOS spin-turns, and combined subtypes of mixed-turns either of the “extra-step” variety representative of an AP stability/braking issue or “small-amplitude” variety representative of a ML stability/balance issue were captured on video. Mixed-ANOVA of gait measures for AP propulsion/braking revealed no age-group differences in speed despite a trend for less of a fast-pace increase in elderly stride-length, yet similar anticipatory slowing and shorter strides approaching turns. Measures of ML stability revealed similar anticipatory widening of right BOS approaching turns, and a three-way interaction showed both had similar anticipatory narrowing of left BOS when approaching turns at fast-pace and similar reactive narrowing of left BOS following an unexpected turn-cue at preferred pace. Loglinear analysis of turn-strategies revealed no age-related associations as both preferred mixed-turns the least. At fast speeds preference for spin-turns decreased, yet when late-cued preference for both step-turns and spin-turns decreased 5.5-fold & 4.0-fold, respectively, indicating other factors besides biomechanical. Furthermore, the standardized residual reached significance for the elderly mixed-turns cell at the most constrained fast-speed*late-cue response-condition, with the “extra-step” sub-type contributing greatest possibly implying an AP rather than ML stability issue. The findings suggest that when approaching turns across an interaction of response-time conditions, healthy older adults show similar anticipatory/reactive gait adaptations and turn-strategy preferences with regards to AP propulsion/deceleration and ML stability/balance. In conclusion, within study limits, fall-prevention gait-training for healthy elderly with low-fall-risk and no age-related speed declines, in addition to addressing important ML stability issues of turn execution, are best served by not losing sight of the fundamental prerequisite to arrest forward momentum upon approach, and being inclusive of spin-turns for their ML space-efficiency
Identifying Gait Deficits in Stroke Patients Using Inertial Sensors
Falls remain a significant problem for stroke patients. Tripping, the main cause of falls, occurs when there is insufficient clearance between the foot and ground. Based on an individual’s gait deficits, different joint angles and coordination patterns are necessary to achieve adequate foot clearance during walking. However, gait deficits are typically only quantified in a research or clinical setting, and it would be helpful to use wearable devices – such as accelerometers – to quantify gait disorders in real-world situations. Therefore, the objective of this project was to understand gait characteristics that influence the risk of tripping, and to detect these characteristics using accelerometers.
Thirty-five participants with a range of walking abilities performed normal walking and attempted to avoid tripping on an unexpected object while gait characteristics were quantified using motion capture techniques and accelerometers. Multiple regression was used to identify the relationship between joint coordination and foot clearance, and multiple analysis of variance was used to determine characteristics of gait that differ between demographic groups, as well as those that enable obstacle avoidance. Machine learning techniques were employed to detect joint angles and the risk of tripping from patterns in accelerometer signals.
Measures of foot clearance that represent toe height throughout swing instead of at a single time point are more sensitive to changes in joint coordination, with hip-knee coordination during midswing having the greatest effect. Participants with a history of falls or stroke perform worse than older non-fallers and young adults on many factors related to falls risk, however, there are no differences in the ability to avoid an unexpected obstacle between these groups. Individuals with an inability to avoid an obstacle have lower scores on functional evaluations, exhibit limited sagittal plane joint range of motion during swing, and adopt a conservative walking strategy.
Machine learning processes can be used to predict knee range of motion and classify individuals at risk for tripping based on an ankle-worn accelerometer. This work is significant because a portable device that detects gait characteristics relevant to the risk of tripping without expensive motion capture technology may reduce the risk of falls for stroke patients
Control Systems Approach to Balance Stabilization during Human Standing and Walking.
Humans rely on cooperation from multiple sensorimotor processes to navigate a complex world. Poor function of one or more components can lead to reduced mobility or increased risk of falls, particularly with age. At present, quantification and characterization of poor postural control typically focus on single sensors rather than the ensemble and lack methods to consider the overall function of sensors, body dynamics, and actuators. To address this gap, I propose a controls framework based on simple mechanistic models to characterize and understand normative postural behavior. The models employ a minimal set of components that typify human behavior and make quantitative predictions to be tested against human data.
This framework is applied to four topics relevant to daily living: sensory integration for standing balance, limb coordination for one-legged balance, momentum usage in sit-to-stand maneuvers, and the energetic trade-offs of foot-to-ground clearance while walking. First, I demonstrate that integration of information from multiple physiological sensors can be modeled by an optimal state estimator. I show how such a model can predict human responses to conflict between visual, vestibular, and other sensors and use visual perturbation experiments to test this model. Second, I demonstrate that feedback control can model multi-limb coordination strategies during one-legged balance. I empirically identify a control law from human subjects and investigate how reducing stance ankle function necessitates greater gains from other limbs. Third, I show the advantages of momentum usage in sit-to-stand maneuvers. Counter to many human movements, this strategy is not performed with energetic economy, requiring excess mechanical work. However, with optimization models, I demonstrate that momentum serves to balance effort between knee and hip. Fourth, I propose a cost model for preferred ground clearance during swing phase of walking. Walking with greater foot lift is costly, but inadvertent ground contact is also costly. Therefore the tradeoff between these costly measures, modulated by movement variability, can explain expected cost of ground clearance. These controls-based models demonstrate the mechanisms behind normative behavior and enables predictions under novel situations. Thus these models may serve as diagnostic tools to identify poor postural control or aid design of intervention procedures.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116654/1/amyrwu_1.pd
Fall prevention strategy for an active orthotic system
Dissertação de mestrado integrado em Engenharia Biomédica (especialização em Eletrónica Médica)Todos os anos, são reportadas cerca de 684,000 quedas fatais e 37.3 milhões de quedas não
fatais que requerem atenção médica, afetando principalmente a população idosa. Assim, é necessário
identificar eficientemente indivíduos com alto risco de queda, a partir da população alvo idosa, e prepará los para superar perturbações da marcha inesperadas. Uma estratégia de prevenção de queda capaz de
eficientemente e atempadamente detetar e contrariar os eventos de perdas de equilíbrio (PDE) mais
frequentes pode reduzir o risco de queda. Como slips foram identificados como a causa mais prevalente
de quedas, estes eventos devem ser abordados como foco principal da estratégia. No entanto, há falta
de estratégias de prevenção de quedas por slip.
Esta dissertação tem como objetivo o design de uma estratégia de prevenção de quedas de slips
baseada na conceção das etapas de atuação e deteção. A estratégia de atuação foi delineada com base
na resposta biomecânica humana a slips, onde o joelho da perna perturbada (leading) apresenta um
papel proeminente para contrariar LOBs induzidas por slips. Quando uma slip é detetada, a estratégia
destaca uma ortótese de joelho que providencia um torque assisstivo para prevenir a queda. A estratégia
de deteção considerou as propriedades atrativas dos controladores Central Pattern Generator (CPG) para
prever parâmetros da marcha. Algoritmos baseados em threshold monitorizam o erro de previsão do
CPG, que aumenta após uma perturbação inesperada na marcha, para a deteção de slips. O ângulo do
joelho e a velocidade angular da canela foram selecionados como os parâmetros de monitorização da
marcha. Um protocolo experimental concebido para provocar perturbações de slip a sujeitos humanos
permitiu a recolha de dados destas variáveis para posteriormente validar o algoritmo de deteção de
perturbações.
Algoritmos CPG foram capazes de produzir aproximações aceitáveis dos sinais de marcha em
estado estacionário do ângulo do joelho e da velocidade angular da canela com sucesso. Além disso, o
algoritmo de threshold adaptativo detetou LOBs induzidas por slips eficientemente. A melhor performance
global foi obtida usando este algoritmo para monitorizar o ângulo do joelho, que detetou quase 80%
(78.261%) do total de perturbações com um tempo médio de deteção (TMD) de 250 ms. Além disso,
uma média de 0.652 falsas perturbações foram detetadas por cada perturbação corretamente
identificada. Estes resultados sugerem uma performance aceitável de deteção de perturbações do
algoritmo, de acordo com os requisitos especificados para a deteção.Every year, an estimated 684,000 fatal falls and 37.3 million non-fatal falls requiring medical
attention are reported, mostly affecting the older population. Thus, it is necessary to effectively screen
high fall risk individuals from targeted elderly populations and prepare them to successfully overcome
unexpected gait perturbations. A fall prevention strategy capable of effectively and timely detect and
counteract the most frequent loss of balance (LOB) events may reduce the fall risk. Since slips were
identified as the main contributors to falls, these events should be addressed as a main focus of the
strategy. Nonetheless, there is a lack of slip-induced fall prevention strategies.
This dissertation aims the design of a slip-related fall prevention strategy based on the conception
of an actuation and a detection stage. The actuation strategy was delineated based on the human
biomechanical reactions to slips, where the perturbed (leading) leg’s knee joint presents a prominent role
to counteract slip-induced LOBs. Thereby, upon the detection of a slip, this strategy highlighted a knee
orthotic device that provides an assistive torque to prevent the falls. The detection strategy considered
the attractive properties of biological-inspired Central Pattern Generator (CPG) controllers to predict gait
parameters. Threshold-based algorithms monitored the CPG’s prediction error produced, which increases
upon an unexpected gait perturbation, to perform slip detection. The knee angle and shank angular
velocity were selected as the monitoring gait parameters. An experimental protocol designed to provoke
slip perturbations to human subjects allowed to collect data from these variables to further validate the
perturbation detection algorithm.
CPG algorithms were able to successfully produce acceptable estimations of the knee angle and
shank angular velocity signals during steady-state walking. Furthermore, an adaptive threshold algorithm
effectively detected slip-induced LOBs. The best overall performance was obtained using this algorithm
to monitor the knee angle from the perturbed leg, which detected almost 80% (78.261%) of the total
perturbations with a mean detection time (MDT) of 250 ms. In addition, a mean of 0.652 false
perturbations were detected for each correct perturbation identified. These results suggest an acceptable
perturbation detection performance of the algorithm implemented in light of the detection requirements
specified
Complexity and Human Gait
Recently, the complexity of the human gait has become a topic of major interest within the field of human movement sciences. Indeed, while the complex fluctuations of the gait patterns were, for a long time, considered as resulting from random processes, the development of new techniques of analysis, so-called nonlinear techniques, has open new vistas for the understanding of such fluctuations. In particular, by connecting the notion of complexity to the one of chaos, new insights about gait adaptability, unhealthy states in gait and neural control of locomotion were provided. Through methods of evaluation of the complexity, experimental results obtained both with healthy and unhealthy subjects and theoretical models of gait complexity, this review discusses the tremendous progresses made about the understanding of the complexity in the human gait variability.
Recientemente, la complejidad de la marcha humana se está convirtiendo en un tema de gran interés en el campo de la ciencia del movimiento humano. De hecho, mientras las fluctuaciones complejas de los patrones de la marcha fueron, durante mucho tiempo, consideradas como resultado de procesos al azar, el desarrollo de nuevas técnicas de análisis, las llamadas técnicas no lineales, ha abierto nuevas vías para el entendimiento de tales fluctuaciones. En particular, mediante la conexión de la noción de complejidad con la de caos, se están obteniendo nuevos conocimientos sobre la adaptabilidad de la marcha, las condiciones patológicas en la marcha y el control neural de la locomoción. Mediante métodos de evaluación de la complejidad, los resultados experimentales obtenidos tanto con individuos sanos como no sanos y con modelos teóricos de la complejidad de la marcha, esta revisión habla de los enormes progresos efectuados sobre el entendimiento de la complejidad en la variabilidad de la marcha humana
The Biomechanical Mechanisms of Fall Risk on Stairs with Inconsistent Step Dimensions
Stair falls frequently happen, affecting people of all ages and impact on a person’s independence. Not only do high rises and shallow goings increase the fall risk but inconsistent dimensions are commonly reported in stair fall investigations. Literature speculates that, the mechanistic reasoning behind these falls occur because individuals do not detect the inconsistency and therefore do not adjust their stepping behaviour. However, these hypotheses are based on observations and assumptions derived from normal stepping behaviour on consistent stairs and have not yet been experimentally tested. Therefore, the purpose of this thesis is to empirically test the mechanisms by which inconsistencies in rise and going dimensions could cause falls in younger and older adults. Twenty-six younger adults (24±3 y, 1.74±0.09 m, 71.41±11.04 kg) and thirty-two older adults (70±4 y, 1.68±0.08 m, 67.90±14.10 kg) ascended and descended an instrumented staircase in three conditions: 1) consistent dimensions (all steps riser =200 mm and going =250 mm), 2) inconsistent rise (third step was raised 10 mm, causing the fourth step to have 10 mm reduced riser) and 3) inconsistent going (third step was made 10 mm shorter, causing second step to have a 10 mm increased going). Data were collected from 3D motion capture and force plates embedded in the bottom four steps. Data were used to quantify and compare stepping mechanics and centre of mass control in the consistent condition to that in the inconsistent rise and inconsistent going conditions. In the inconsistent rise condition (Chapter 3), during ascent clearances of both groups were reduced (≈9 mm, F=48.4, p=.001) over the higher step-edge, increasing trip risk. During descent, percentage foot contact lengths decreased (≈2%, F=9.1, p=.004) on the inconsistently higher step for both groups, possibly increasing the risk of a slip. Foot centre of mass (CoM) trajectories during swing prior to contact, revealed that there were no alterations to stepping behaviour prior to contact with the inconsistently higher rise step, causing a magnitude of change that was comparable to the 10 mm manipulation. In the inconsistent going condition (Chapter 4), during descent percentage foot contact lengths of both groups were not significantly different to the consistent condition (≈1%, F=2.5, p=.121). Foot CoM trajectories during swing confirmed that, individuals changed their stepping behaviour in late swing prior to contact with the shorter step, contradicting previous assumptions. Additionally, younger adults then had reduced clearances over the inconsistently longer step, which could increase their trip risk. During ascent, there were interaction effects detected between stair configurations and age groups. On the shorter step, foot contact lengths were increased for younger adults (≈+2.2%) and decreased for older adults (≈-2.8%) (interaction: F = 8.8, p=.004), this could increase the chances of a miss-step for the older adults. These differences seemed to stem from positioning on the walkway before transition. Younger adults were 8 mm closer to the stairs in their level-ground step, whereas older adults were 14 mm further away in the inconsistent going condition (interaction effect, p=.048). Descending balance parameters were affected by the presence of the inconsistent dimensions (Chapter 5). There were interactions between the CoM accelerations at 23.6%-31.9% and 73.4%-77.0% of stance on Step4 (p=.008 and p=.035, respectively) prior to contact with the inconsistent shorter going step, balance parameters after contact were minimally affected. Whereas for the inconsistent rise condition, balance was altered at contact with the higher step due to more posteriorly directed forces between 16.5%-22.2% of stance on Step3 (p=.020) and higher peak coefficients of friction (p=.003), this could increase the risk of slipping during loading. Despite increased loading rates (p<.001) and larger vertical CoM accelerations (p=.016) at initial contact onto Step2 (longer step down), there were compensations between 13.7%-19.5% of stance on Step2, whereby upward vertical CoM acceleration were increased to regain control before the subsequent step. Stepping behaviours observed on the inconsistent rise stairs indicate that younger and older adults did not detect the 10 mm difference in step rise, which put them at a higher risk of tripping in ascent and slipping in descent, and further required good reactive balance control to maintain CoM control after contact. The proactive changes to stepping behaviour and CoM control observed during descent of the inconsistent going stairs, seems to improve stepping mechanics so that minimal adjustments to CoM control are needed after contact. The proactive change is likely dependent on visual detection of the inconsistency. Frailer or distracted individuals may not be able to respond to the inconsistencies in the same way and therefore may have more frequent falls on inconsistent steps
Balance Recovery Response in Community-Dwelling Adults with Unilateral Transtibial Amputation and the Potential Benefits of a Weight-Shifting Balance Training Intervention
Previous studies have shown that individuals with various physical, sensory and neuromuscular impairments are at higher risks of falls. Individuals with unilateral transtibial amputation (UTTA) suffered from all these impairments, and tripping not surprisingly caused a considerable number of falls in this population. To study falls, researchers have to put participants in a well-protected environment and reproduce tripping fall scenarios. Furthermore, the perturbation delivery needs to be precise in terms of temporo-spatial timing. These features would ensure the quality of responses elicited and reproducibility of the results. Thus, in Chapter 2, we developed a treadmill-based perturbation delivery protocol and confirmed that by referencing ground reaction force, the system was able to consistently and precisely deliver perturbations in early stance phase to elicit tripping falls.Because tripping usually arrests only one side of the limb, individuals with UTTA may respond differently when encountering trips with their prosthetic versus non- prosthetic limb. Understanding the biomechanical differences in fall recovery response between these two tripping conditions will facilitate ideas for patient-specific intervention targeting tripping fall prevention. Therefore, in Chapter 3, we utilized the protocol developed in Chapter 2 to deliver destabilizing perturbations to the participants in order to examine the limb-to-limb differences during fall recovery. We found that while the gross fall recovery strategies (i.e. the stepping response) were similar, there existed key biomechanical differences. Perturbation during a static standing condition was typically arrested with the perturbed limb making the recovery step. Dynamic perturbation condition was recovered with the contralateral (non-perturbed) limb making the first recovery step followed by the ipsilateral limb making the reciprocal second recovery step. We observed that certain defined response times were longer when the recover step was executed by the prosthetic limb in both static and dynamic perturbation conditions, suggesting the impaired sensory detection or motor execution of the prosthetic limb. Currently, clinical practitioners are encouraged to include balance training in post amputation rehabilitation. A balance training that focuses on weight-shifting may prepare individuals with lower limb loss the essential ability to make successful recovery step when encountering destabilizing scenarios. However, it is currently unknown if a training program focusing solely on balance control can improve fall recovery response. Hence, in Chapter 4, we examined the effects of a 2-day weight-shifting balance training using protocols developed in Chapters 2 and 3. We found that certain biomechanical variables relevant to weight-shifting and weight-bearing during fall recovery were altered by the training. For instance, the duration for unloading the prosthetic limb before taking the recovery step during static perturbation condition were improved after training. Another example was that when the prosthetic limb was perturbed, the duration of the first recovery step increased; meanwhile, when the non-prosthetic limb was perturbed, the duration of the second recovery step increased. These two durations were the non- prosthetic limb executing the recovery step in which the prosthetic limb providing the stance support, and the stance time increased. Overall, our findings suggest that sensorimotor deficits related to UTTA may lead to longer duration of step time when the prosthetic limb executed the recovery step. This is a promising direction to intervene in the future. Our balance training protocol appears to improve components that were related to participants’ weight-shifting ability. Whilst for altering the global fall recovery responses, we concluded that a more perturbation-based approach may be required and should be investigated in the future
Fast biped walking with a neuronal controller and physical computation
Biped walking remains a difficult problem and robot models can
greatly {facilitate} our understanding of the underlying
biomechanical principles as well as their neuronal control. The
goal of this study is to specifically demonstrate that stable
biped walking can be achieved by combining the physical properties
of the walking robot with a small, reflex-based neuronal network,
which is governed mainly by local sensor signals. This study shows
that human-like gaits emerge without {specific} position or
trajectory control and that the walker is able to compensate small
disturbances through its own dynamical properties. The reflexive
controller used here has the following characteristics, which are
different from earlier approaches: (1) Control is mainly local.
Hence, it uses only two signals (AEA=Anterior Extreme Angle and
GC=Ground Contact) which operate at the inter-joint level. All
other signals operate only at single joints. (2) Neither position
control nor trajectory tracking control is used. Instead, the
approximate nature of the local reflexes on each joint allows the
robot mechanics itself (e.g., its passive dynamics) to contribute
substantially to the overall gait trajectory computation. (3) The
motor control scheme used in the local reflexes of our robot is
more straightforward and has more biological plausibility than
that of other robots, because the outputs of the motorneurons in
our reflexive controller are directly driving the motors of the
joints, rather than working as references for position or velocity
control. As a consequence, the neural controller and the robot
mechanics are closely coupled as a neuro-mechanical system and
this study emphasises that dynamically stable biped walking gaits
emerge from the coupling between neural computation and physical
computation. This is demonstrated by different walking
experiments using two real robot as well as by a Poincar\'{e} map
analysis applied on a model of the robot in order to assess its
stability. In addition, this neuronal control structure allows the
use of a policy gradient reinforcement learning algorithm to tune
the parameters of the neurons in real-time, during walking. This
way the robot can reach a record-breaking walking speed of 3.5
leg-lengths per second after only a few minutes of online
learning, which is even comparable to the fastest relative speed
of human walking
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