Pre-impact fall detection: optimal sensor positioning based on a machine learning paradigm

The aim of this study was to identify the best subset of body segments that provides for a rapid and reliable detection of the transition from steady walking to a slipping event. Fifteen healthy young subjects managed unexpected perturbations during walking. Whole-body 3D kinematics was recorded and a machine learning algorithm was developed to detect perturbation events. In particular, the linear acceleration of all the body segments was parsed by Independent Component Analysis and a Neural Network was used to classify walking from unexpected perturbations. The Mean Detection Time (MDT) was 3516123 ms with an Accuracy of 95.4%. The procedure was repeated with data related to different subsets of all body segments whose variability appeared strongly influenced by the perturbation-induced dynamic modifications. Accordingly, feet and hands accounted for most data information and the performance of the algorithm were slightly reduced using their combination. Results support the hypothesis that, in the framework of the proposed approach, the information conveyed by all the body segments is redundant to achieve effective fall detection, and suitable performance can be obtained by simply observing the kinematics of upper and lower distal extremities. Future studies are required to assess the extent to which such results can be reproduced in older adults and in different experimental conditions

Changes in human walking dynamics induced by uneven terrain are reduced with ongoing exposure, but a higher variability persists

During walking, uneven terrain alters the action of the ground reaction force from stride to stride. The extent to which such environmental inconsistencies are withstood may be revealed by the regulation of whole-body angular momentum (L) during walking. L quantifies the balance of momenta of the body segments (thigh, trunk, etc.) about their combined center of mass, and remains close to zero during level walking. A failure to constrain L has been linked to falls. The aim of this study was to explore the ability of young adults to orchestrate their movement on uneven terrain, illustrated by the range of L (LR) and its variability (vLR). In eleven male adults, we observed significant increases in sagittal plane LR, and vLR in all three planes of motion during walking on an uneven in comparison to a flat surface. No reductions in these measures were observed within a 12-minute familiarisation period, suggesting that unimpaired adults either are unable to, or do not need to eliminate the effects of uneven terrain. Transverse plane LR, in contrast, was lower on immediate exposure, and then increased, pointing to the development of a less restrictive movement pattern, and would support the latter hypothesis

Estimation of sagittal-plane whole-body angular momentum during perturbed and unperturbed gait using simplified body models

Human whole-body angular momentum (WBAM) during walking typically follows a consistent pattern, making it a valuable indicator of the state of balance. However, calculating WBAM is labor-intensive, where the kinematic data for all body segments is needed, that is, based on a full-body model. In this study, we focused on selecting appropriate segments for estimating sagittal-plane WBAM during both unperturbed and perturbed gaits, which were segments with significant angular momentum contributions. Those major segments were constructed as a simplified model, and the sagittal-plane WBAM based on a simplified model was calculated by combining the angular momenta of the selected segments. We found that the WBAM estimated by seven-segment models, incorporating the head & torso (HT) and all lower limb segments, provided an average correlation coefficient of 0.99 and relative angular momentum percentage of 96.8% and exhibited the most similar sensitivity to external perturbations compared to the full-body model-based WBAM. Additionally, our findings revealed that the rotational angular momenta (RAM) of lower limb segments were much smaller than their translational angular momenta (TAM). The pair-wise comparisons between simplified models with and without RAMs of lower body segments were observed with no significant difference, indicating that RAMs of lower body segments are neglectable. This may further simplify the WBAM estimation based on the seven-segment model, eliminating the need to estimate the angular velocities of lower limb segments. These findings have practical implications for future studies of using inertial measurement units (IMUs) for estimating WBAM, as our results can help reduce the number of required sensors and simplify kinematics measurement

Angular Momentum During Unexpected Multidirectional Perturbations Delivered While Walking

This study investigated the hypothesis that the coupled contribution of all body segments to the whole-body response during both walking and managing unexpected perturbations is characterized by similar features which do not depend on the laterality (i.e., right versus left sides), but can be influenced by the direction (e. g., north, east, south, etc.) of the perturbation. The whole-body angular momentum was estimated as summation of segmental angular momenta, while 15 young adults managed ten unexpected unilateral perturbations during walking. Then, the Principal component analysis was used to extract primitive features describing intersegment coordination. Results showed that intersegment coupling was similar even though the reactive response to the perturbations elicited more consistent motor schemes across body segments than during walking, especially in the frontal plane. The direction of the perturbation significantly (p < 0.05) affected angular momentum regulation documenting the attitude of the central nervous system to interpret multiple sensory inputs in order to produce context-dependent reactive responses. With respect to the side, results highlighted anisotropic features of the elicited motor schemes that seemed to depend on subjects' dominance. Finally, results confirm that the coordination of upper and lower body segments is synergistically achieved strengthening the hypothesis that it may result from common neural pathways

Angular momentum during unexpected multidirectional perturbations delivered while walking.

This study investigated the hypothesis that the coupled contribution of all body segments to the whole-body response during both walking and managing unexpected perturbations is characterized by similar features which do not depend on the laterality (i.e., right versus left sides), but can be influenced by the direction (e. g., north, east, south, etc.) of the perturbation. The whole-body angular momentum was estimated as summation of segmental angular momenta, while 15 young adults managed ten unexpected unilateral perturbations during walking. Then, the Principal component analysis was used to extract primitive features describing intersegment coordination. Results showed that intersegment coupling was similar even though the reactive response to the perturbations elicited more consistent motor schemes across body segments than during walking, especially in the frontal plane. The direction of the perturbation significantly (p < 0.05) affected angular momentum regulation documenting the attitude of the central nervous system to interpret multiple sensory inputs in order to produce context-dependent reactive responses. With respect to the side, results highlighted anisotropic features of the elicited motor schemes that seemed to depend on subjects' dominance. Finally, results confirm that the coordination of upper and lower body segments is synergistically achieved strengthening the hypothesis that it may result from common neural pathways

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

IEEE Transactions On Biomedical Engineering : Vol. 60, No. 7, July 2013

1. Closed-Loop Control of Renal Perfusion Pressure in Physiological Experiments 2. Angular Momentum During Unexpected Multidirectional Perturbations Delivered While Walking 3. Influence of Running Stride Frequency in Heart Rate Variability Analysis During treadmill Exercise testing 4. Magnetic Fluid Hyperthermia Modeling Based on Phantom Measurements and Realistic Breast Model 5. Coefficient-Free Blood Pressure Estimation Based on Pulse Transit Time-Cuff Pressure Depedence Etc