Walking In Subjects Research Articles

Analysis of the fall avoidance motion focusing on the angular momentum induced by tripping during gait

Fall is one of the greatest causes of nursing care for the elderly. Thus, the reduction of fall injury of the elderly is required. In some previous researches on trip, angular momentum is used as an evaluation parameter. However, the relation between fall avoidance motion and angular momentum is not focused. Thus, in this research, we focus on angular momentum as an index of fall evaluation. To reveal the influence of angular momentum on fall avoidance motion, angular momentum is increased in different ways. One is attaching weights to subject and another is having subjects walk faster and the other is pulling subject from the front. The result suggested that the trend of reaction motion differed among conditions. However, there are some common feature among the reaction motion of these conditions according to the analysis of correlation coefficients

3-D Gait Abnormality Detection Employing Contactless IR-UWB Sensing Phenomenon

Gait disorder diagnosis and rehabilitation is one area where human perception and observation are highly integrated. Predominantly, gait evaluation comprises technological devices for gait analysis, such as dedicated force sensors, cameras, and wearable sensor-based solutions; however, they are limited by insufficient gait parameter recognition, postprocessing, installation costs, mobility, and skin irritation issues. Thus, the proposed study concentrates on the creation of a widely deployable, noncontact and nonintrusive gait recognition method from impulse radio ultrawideband (IR-UWB) sensing phenomenon, where a standalone IR-UWB system can detect gait problems with less human intervention. A 3-D human motion model for gait identification from IR-UWB has been proposed with embracing spherical trigonometry and vector algebra to determine knee angles. Subsequently, normal and abnormal walking subjects were involved in this study. Abnormal gait subjects belong to the spastic gait category only. The prototype has been tested in both anechoic and multipath environments. The outcomes have been corroborated with a simultaneously deployed Kinect Xbox sensor and supported by a statistical graphical approach Bland and Altman (B&A) analysis.

Generation of a gait pattern for a lower limb rehabilitation exoskeleton

In this article, a simple prototype and control system of a lower limb exoskeleton driven by stepper motors was proposed. To study kinematic parameters of the device, a general, three-dimensional simulation model of the exoskeleton was developed. Moreover, a gait pattern was modeled for hip, knee, and ankle joints. It represents sagittal plane angular positions of joints during normal gait and consists of three piecewise-defined sine-square-based functions. It is based on the experimental gait data recorded with an optoelectronic motion capture system for a healthy subject walking on a treadmill. Although the developed pattern is intended to be implemented in a control system of a lower limb exoskeleton for gait rehabilitation, it can be used to control bipedal robots as well. Last but not least, the control approach was tested with the exoskeleton prototype.

Evaluation of Motor Primitive-Based Adaptive Control for Lower Limb Exoskeletons.

In order to assist after-stroke individuals to rehabilitate their movements, research centers have developed lower limbs exoskeletons and control strategies for them. Robot-assisted therapy can help not only by providing support, accuracy, and precision while performing exercises, but also by being able to adapt to different patient needs, according to their impairments. As a consequence, different control strategies have been employed and evaluated, although with limited effectiveness. This work presents a bio-inspired controller, based on the concept of motor primitives. The proposed approach was evaluated on a lower limbs exoskeleton, in which the knee joint was driven by a series elastic actuator. First, to extract the motor primitives, the user torques were estimated by means of a generalized momentum-based disturbance observer combined with an extended Kalman filter. These data were provided to the control algorithm, which, at every swing phase, assisted the subject to perform the desired movement, based on the analysis of his previous step. Tests are performed in order to evaluate the controller performance for a subject walking actively, passively, and at a combination of these two conditions. Results suggest that the robot assistance is capable of compensating the motor primitive weight deficiency when the subject exerts less torque than expected. Furthermore, though only the knee joint was actuated, the motor primitive weights with respect to the hip joint were influenced by the robot torque applied at the knee. The robot also generated torque to compensate for eventual asynchronous movements of the subject, and adapted to a change in the gait characteristics within three to four steps.

Lagged Relationships Among Chemotherapy-Induced Peripheral Neuropathy, Sleep Quality, and Physical Activity During and After Chemotherapy.

Chemotherapy-induced peripheral neuropathy (CIPN) is well-documented and can become chronic for up to a third of patients. CIPN management is hampered by limited pharmacological options. Thus, identifying modifiable behaviors that influence CIPN may help inform future interventions. The purpose of the current study was to examine bidirectional relationships between sleep quality, physical activity, and CIPN during and after chemotherapy. Participants were 138 women with gynecologic cancer (M age = 61, 94% white, 96% non-Hispanic), collected as part of an ongoing study. Assessments occurred at postcycle 1, postcycle 6, and 6- and 12-month postchemotherapy. CIPN (EORTC-CIPN20), sleep quality (PSQI), and physical activity (IPAQ) were assessed via self-report. Objective physical activity was assessed via wrist actigraphy. Latent change score models were used to examine lagged relationships between CIPN, sleep quality, and physical activity pairs. Over the study period, sleep quality was found to contribute to CIPN (p = .001), but not the reverse (p > .05). Bidirectional relationships were observed between CIPN and both objective and subjective walking (ps ≤ .001). Illustrations of these relationships showed that patients with less CIPN early in treatment demonstrate more substantial increases in walking over time, while those with higher CIPN demonstrate more consistent levels of walking during and after treatment. These findings suggest that worse sleep quality and lower walking levels may contribute to the course and maintenance of CIPN. Future investigation should evaluate the impact of early interventions aimed at improving sleep quality and encouraging physical activity in patients treated with chemotherapy.

Comparative analysis of neural network for human gait classification

The paper reviews different neural network architecture for human gait recognition as a part of the control loop of soft exoskeleton. 6-axis inertial measurement unit (IMU) used for experimental data collection and gait phase prediction. IMU sensors are attached to the hip, ankle and foot of each leg. Three different architecture were chosen for comparison: feed-forward neural network, cascade neural network and recurrent neural network. All neural networks trained on the group of dataset that consist of 100 steps and compared by precision. Dataset was collected during subject walking on a treadmill with a different speed. The experiments show that recurrent neural network more efficient than other one.

Walking for subjects with type 2 diabetes: a systematic review and joint AMD/SID/SISMES evidence-based practical guideline

AimsRegular exercise is considered a cornerstone in the management of type 2 diabetes mellitus (T2DM). It improves glucose control and cardiovascular risk factors, contributes to weight loss, and also improves general well-being, likely playing a role in the prevention of chronic complications of diabetes. However, compliance to exercise recommendations is generally inadequate in subjects with T2DM. Walking is the most ancestral form of physical activity in humans, easily applicable in daily life. It may represent, in many patients, a first simple step towards lifestyle changes. Nevertheless, while most diabetic patients do not engage in any weekly walking, exercise guidelines do not generally detail how to improve its use. The aims of this document are to conduct a systematic review of available literature on walking as a therapeutic tool for people with T2DM, and to provide practical, evidence-based clinical recommendations regarding its utilization in these subjects.Data synthesisAnalysis of available RCTs proved that regular walking training, especially when supervised, improves glucose control in subjects with T2DM, with favorable effects also on cardiorespiratory fitness, body weight, and blood pressure. Moreover, some recent studies have shown that even short bouts of walking, used for breaking prolonged sitting, can ameliorate glucose profiles in diabetic patients with sedentary behavior.ConclusionsThere is sufficient evidence to recognize that walking is a useful therapeutic tool for people with T2DM. This document discusses theoretical and practical issues for improving its use.

Walking for subjects with type 2 diabetes: A systematic review and joint AMD/SID/SISMES evidence-based practical guideline

AimsRegular exercise is considered a cornerstone in the management of type 2 diabetes mellitus (T2DM). It improves glucose control and cardiovascular risk factors, contributes to weight loss, and also improves general well-being, likely playing a role in the prevention of chronic complications of diabetes. However, compliance to exercise recommendations is generally inadequate in subjects with T2DM. Walking is the most ancestral form of physical activity in humans, easily applicable in daily life. It may represent, in many patients, a first simple step towards lifestyle changes. Nevertheless, while most diabetic patients do not engage in any weekly walking, exercise guidelines do not generally detail how to improve its use. The aims of this document are to conduct a systematic review of available literature on walking as a therapeutic tool for people with T2DM, and to provide practical, evidence-based clinical recommendations regarding its utilization in these subjects. Data synthesisAnalysis of available RCTs proved that regular walking training, especially when supervised, improves glucose control in subjects with T2DM, with favorable effects also on cardiorespiratory fitness, body weight and blood pressure. Moreover, some recent studies have shown that even short bouts of walking, used for breaking prolonged sitting, can ameliorate glucose profiles in diabetic patients with sedentary behavior. ConclusionsThere is sufficient evidence to recognize that walking is a useful therapeutic tool for people with T2DM. This document discusses theoretical and practical issues for improving its use.This article is co-published in the journals Sport Sciences for Health and Nutrition, Metabolism and Cardiovascular Diseases.

Simultaneous identification of human body model parameters and gait trajectory from 3D motion capture data

The analysis of human movements rests on a realistic human body model. Deducing model parameters from anthropomorphic data is challenging since these are inherently imprecise. An approach to improve model accuracy is the parameter adaptation based on motion data. 3D motion capture data are already being used for generating the trajectories of a human body model, so combining motion tracking and parameter identification seems most natural. This paper introduces a holistic approach to simultaneously identify the geometric parameters of a kinematic human lower limb model and the parameters defining a (cyclic) gait trajectory, based on 3D marker positions. The result is a time-continuous description of a physiologically compatible lower extremity movement along with optimal model parameters so to best reproduce the captured motion. The method takes into account restrictions such as the range of motion of human body joints and is robust against missing data due to marker occlusions or failures of the measurement system. Considering multiple gait cycles of a movement trial, we derive the characteristic motion pattern (CMP) of a specific subject walking at a specific speed. Our method further allows for motion analysis and assessment, but also for motion synthesis with arbitrary time span and time resolution and can thus be used for simulations and trajectory planning of rehabilitation and movement assistance systems, such as exoskeletons.

Hierarchical goal effects on center of mass velocity and eye fixations during gait.

The purpose of this study was to determine the effect of hierarchical goal structure of a yet-to-be performed task on gait and eye fixation behavior while walking to the location of where the task was to be performed. Subjects performed different goal-directed tasks representing three hierarchical levels of planning. The first level of planning consisted of having the subject walk to a bookcase on which an object (a cup) was located in the middle of a shelf. The second level of planning consisted of walking to the bookcase and picking up the cup which was in the middle, on the right side, or on the left side of the bookcase shelf. The third level of planning consisted of walking to the bookcase, picking up the cup which was located in the middle of the bookcase shelf, and moving it to a higher shelf. Findings showed that hierarchal goals do affect center of mass velocity and eye fixation behavior. Center of mass velocity to the bookcase increased with an increase in the number of goals. Subjects decreased gait velocity as they approached the bookcase and adjusted their last steps to accommodate picking up the cup. The findings also demonstrated the important role of vision in controlling gait velocity in goal-directed tasks. Eye fixation duration was more important than the number of eye fixations in controlling gait velocity. Thus, the amount of information gained through object fixation duration is of greater importance than the number of fixations on the object for effective goal achievement.

Structured Laser Light Improves Tripping Hazard Recognition for People with Visual Impairments.

PurposeUsing a geometrically derived model and a virtual curb simulator, we quantify the degree to which a wearable device that projects a laser line onto tripping hazards in a pedestrian's path improves visual recognition for people with visual impairments (VI). We confirm this with subjects' performance on computer simulations of low contrast curbs.MethodsWe derive geometric expressions quantifying the visual cue users perceive when a single laser line is projected from their hip onto a curb. We show how the efficacy of this cue changes with the angle of the laser line relative to the subject's walking trajectory. We confirm this result with data from three subjects with VI in a simulated curb recognition task in which subjects classified computer images as an “Ascending,” “Flat,” or “Descending” curb.ResultsThe derived model predicts that human recognition performance depends strongly on the laser line angle and the subject data confirms this (r2 = 0.86, P < 0.001). The laser line cue improved subject accuracy from a chance level of 33% to 95% for a simulated, one-inch, low-contrast curb at a distance of five feet.ConclusionsRecognition of curbs in low light can be improved by augmenting the scene with a single laser line projected from a user's hip, if the angle of laser line is appropriately selected.Translational RelevanceA majority of people with VI rely on their impaired residual vision for mobility, rather than a mobility aid, resulting in increased injury for this population. Enhancing residual vision could promote safety, increase independence, and reduce medical costs.

Comparison of different optimal control formulations for generating dynamically consistent crutch walking simulations using a torque-driven model

Walking impairment due to spinal cord injury can be improved using active orthoses, together with some type of external support such as crutches for balance. This study explores how optimal control problem formulation affects the ability to generate dynamically consistent crutch walking simulations with active orthosis assistance that closely reproduce experimental data. The investigation compares eight optimal tracking problem formulations using a torque-driven full-body skeletal model of a healthy subject walking with active knee-ankle-foot orthoses and forearm crutches. We have found that small adjustments to ground reactions are required to achieve convergence, tracking of joint instead of marker coordinates significantly improves convergence, and minimising joint jerks instead of joint accelerations has only a minor effect on the problem convergence. These results provide guidance for future work that seeks to develop predictive optimal control simulations that can identify orthosis control parameters that maximise improvement in walking function on an individual patient basis.

Dispersion of knee helical axes during walking in young and elderly healthy subjects

Knee joint rotation center displacement can be estimated in vivo through the analysis of helical axis (HAs) dispersion. HAs can be analyzed during walking, providing information on joint stability. The study aim was to describe knee HAs dispersion during walking in dominant and non-dominant legs of young and elderly healthy subjects.Twenty young (YG: age 23.3 ± 2.4 years) and twenty elderly (EG: age 69.3 ± 4.6 years) healthy subjects were asked to walk on a treadmill at a self-selected speed with reflective markers placed bilaterally on thighs and shanks to detect HAs dispersion and knee kinematics with an optoelectronic system. HAs dispersion was described during the following four phases of gait cycle: (1) flexion from 95% of the previous gait cycle to 10% of the subsequent gait cycle, (2) extension from 10% to 40%, (3) flexion from 40% to 75% and (4) extension from 75% to 95% of the gait cycle. Mean Distance (MD) and Mean Angle (MA) were used as HAs dispersion indexes during each gait phase.Participants showed greater MD and MA in sagittal and frontal planes during the first and second phases. EG revealed higher MD (p = 0.001) and MA (p < 0.001) during the first phase and higher MA (p = 0.001) during the fourth phase in both dominant and non-dominant legs on the sagittal plane.HAs dispersion could be related to the amount of forces acting on knee (first two phases) and knee degeneration (elderly). These results may be used as reference data in further studies on HAs dispersion in presence of knee pathologies or after knee surgery or rehabilitation.

A wide field-of-view, modular, high-density diffuse optical tomography system for minimally constrained three-dimensional functional neuroimaging.

The ability to produce high-quality images of human brain function in any environment and during unconstrained movement of the subject has long been a goal of neuroimaging research. Diffuse optical tomography, which uses the intensity of back-scattered near-infrared light from multiple source-detector pairs to image changes in haemoglobin concentrations in the brain, is uniquely placed to achieve this goal. Here, we describe a new generation of modular, fibre-less, high-density diffuse optical tomography technology that provides exceptional sensitivity, a large dynamic range, a field-of-view sufficient to cover approximately one-third of the adult scalp, and also incorporates dedicated motion sensing into each module. Using in-vivo measures, we demonstrate a noise-equivalent power of 318 fW, and an effective dynamic range of 142 dB. We describe the application of this system to a novel somatomotor neuroimaging paradigm that involves subjects walking and texting on a smartphone. Our results demonstrate that wearable high-density diffuse optical tomography permits three-dimensional imaging of the human brain function during overt movement of the subject; images of somatomotor cortical activation can be obtained while subjects move in a relatively unconstrained manner, and these images are in good agreement with those obtained while the subjects remain stationary. The scalable nature of the technology we described here paves the way for the routine acquisition of high-quality, three-dimensional, whole-cortex diffuse optical tomography images of cerebral haemodynamics, both inside and outside of the laboratory environment, which has profound implications for neuroscience.

Millimeter wave radar data of people walking.

This dataset contains complex signals coming from a mmWave FMCW radar system. Signals were acquired during a measurement campaign taken indoor and aimed to assess people's different ways of walking. Measurement setup and devices are described.The dataset consists of the acquisitions of six different types of activities, performed by 29 subjects who repeat each activity several times. Therefore, the dataset contains multiple different experiments for each activity, for a total of 231 acquisitions. The subjects walk without any constraint or do not follow any pattern, thus making this dataset useful not only for human gait recognition but also to evaluate the performance of different radar data processing algorithms.

Dual-Motor-Task of Catching and Throwing a Ball During Overground Walking in Virtual Reality.

Virtual Reality is a versatile platform to study human behavior in simulated environments and to develop interventions for functional rehabilitation. In this work, we designed a dual-task paradigm in a virtual environment where both tasks demand motor skills. Twenty-one healthy adults (mean age: 24.1 years) participated in this study. The experiment involved three conditions - normal overground walking, catch and throw a ball while standing, and catch and throw a ball while walking overground -all in the virtual environment. We investigated the dual-task gait characteristics and their correlations with outcomes from cognitive assessments. Results show that subjects walk conservatively with smaller stride lengths, larger stride widths and stride time while catching and throwing. However, they are able to throw the balls more accurately at the target and achieve higher scores. During the dual-task throw, we observed that the participants threw more balls during the stance phase of the gait when the foot was in the terminal stance and pre-swing region. During this region, the body has forward momentum. In addition, the changes in gait characteristics during dual-task throw correlate well with outcome measures in standardized cognitive tests. This study provides a new and engaging paradigm to analyze dual-motor-task cost in a virtual reality environment and it can be used as a basis to compare strategies adopted by different population groups with healthy young adults to execute coordinated motor tasks.

Prediction of three-dimensional crutch walking patterns using a torque-driven model

Computational prediction of 3D crutch-assisted walking patterns is a challenging problem that could be applied to study different biomechanical aspects of crutch walking in virtual subjects, to assist physiotherapists to choose the optimal crutch walking pattern for a specific subject, and to help in the design and control of exoskeletons, when crutches are needed for balance. The aim of this work is to generate a method to predict three-dimensional crutch-assisted walking motions following different patterns without tracking any experimental data. To reach this goal, we collected gait data from a healthy subject performing a four-point non-alternating crutch walking pattern, and developed a 3D torque-driven full-body model of the subject including the crutches and foot- and crutch-ground contact models. First, we developed a predictive (i.e., no tracking of experimental data) optimal control problem formulation to predict crutch walking cycles following the same pattern as the experimental data collected, using different cost functions. To reduce errors with respect to reference data, a cost function combining minimization terms of angular momentum, mechanical power, joint jerk and torque change was chosen. Then, the problem formulation was adapted to handle different foot- and crutch-ground conditions to make it capable of predicting three new crutch walking patterns, one of them at different speeds. A key aspect of our algorithm is that having ground reactions as additional controls allows one to define phases inside the cycle without the need of formulating a multiple-phase problem, thus facilitating the definition of different crutch walking patterns.

Characterization of human motion by the use of an accelerometer-based detection system

Human motion mode detection is of great value in evaluating motor ability. In this study, a method of human motion mode detection based on an acceleration sensor was characterized. A human motion mode detection system was designed using the standard deviation, peak, valley and peak-valley interval as characteristic values and a particle swarm optimization – support vector machine (PSO-SVM) algorithm as the detection method. The measurements of 10 subjects in static, walking and running stages were collected and evaluated. The experimental results showed that the static, walking and running detection accuracy values were 96%, 90% and 92% respectively, and the overall value was 94%. Using the same number of samples, the detection accuracy of SVM was 82.57%, while that of PSO-SVM was 93.1%, which had the highest reliability. This study demonstrates the validity of the human motion mode detection method based on an acceleration sensor which can accurately detect static state, walking and running, and the method is worth further promotion and application.

Constrained maximum variance stopping for a finite horizon increasing random walk

We derive the optimal solution for the problem of choosing a non-anticipative decision rule to maximize the stopping variance of a finite horizon, increasing random walk subject to a distributional constraint, as well as an explicit upper limit on the variance of the walk’s stopping state. Problems of this caliber arise as subproblems for risk-constrained versions of standard stopping problems in areas including, for instance, market entry decision-making. A numerical example verifies the main result.

Using force data to self-pace an instrumented treadmill and measure self-selected walking speed

BackgroundSelf-selected speed is an important functional index of walking. A self-pacing controller that reliably matches walking speed without additional hardware can be useful for measuring self-selected speed in a treadmill-based laboratory.MethodsWe adapted a previously proposed self-pacing controller for force-instrumented treadmills and validated its use for measuring self-selected speeds. We first evaluated the controller’s estimation of subject speed and position from the force-plates by comparing it to those from motion capture data. We then compared five tests of self-selected speed. Ten healthy adults completed a standard 10-meter walk test, a 150-meter walk test, a commonly used manual treadmill speed selection test, a two-minute self-paced treadmill test, and a 150-meter self-paced treadmill test. In each case, subjects were instructed to walk at or select their comfortable speed. We also assessed the time taken for a trial and a survey on comfort and ease of choosing a speed in all the tests.ResultsThe self-pacing algorithm estimated subject speed and position accurately, with root mean square differences compared to motion capture of 0.023 m s −1 and 0.014 m, respectively. Self-selected speeds from both self-paced treadmill tests correlated well with those from the 10-meter walk test (R>0.93,p<1×10−13). Subjects walked slower on average in the self-paced treadmill tests (1.23±0.27 ms−1) than in the 10-meter walk test (1.32±0.18 ms−1) but the speed differences within subjects were consistent. These correlations and walking speeds are comparable to those from the manual treadmill speed selection test (R=0.89,p=3×10−11;1.18±0.24 ms−1). Comfort and ease of speed selection were similar in the self-paced tests and the manual speed selection test, but the self-paced tests required only about a third of the time to complete. Our results demonstrate that these self-paced treadmill tests can be a strong alternative to the commonly used manual treadmill speed selection test.ConclusionsThe self-paced force-instrumented treadmill well adapts to subject walking speed and reliably measures self-selected walking speeds. We provide the self-pacing software to facilitate use by gait researchers and clinicians.