Gait dynamic stability evaluation in patients undergoing hip joint fractures - tools to measure rehabilitation effectiveness.

A hip joint fracture includes a break in the thigh (femur) or coxa bone near the pelvis. During fracture healing, stability and weight bearing by the affected limb are key indicators to measure patients' improvement. Conventionally, the rehabilitation effectiveness is monitored through clinical examinations, patients' feedback, and few studies also reported instrumented gait evaluations. A gap remains there to numerically quantify the recovery in patients' stability and weight bearing in response to rehabilitation therapies. This study introduces Nyquist and Bode (N&B) methods to analyse the instrumented gait signals further and evaluate gait stability in hip fracture patients during weight loading and unloading transitions. The centre of pressure (CoP) data was recorded using force plates for conditions: coxa hip fracture (HC), femur hip fracture (HF), and normal hip joint (NH). The time rate of CoP signals illustrated two major impulses during the loading and unloading phases which were modelled in time and frequency domains. The frequency models were further analysed by applying N&B methods and stability margins were computed for both impaired and healthy conditions. Results illustrated a significant decrease (Kruskal-Wallis's test, p < 0.001) in the intralimb walking stability of both fracture conditions. Further, Spearman's correlation between CoP velocities of fractured and intact limbs illustrated significant interlimb dependencies to maintain walking stability (p < 0.001) during weight loading and unloading transitions. Overall, the HF impairment illustrated the least intralimb walking stability and relatively greater interlimb dependencies. Clinically, these methods and findings are important to measure the recovery in patients undergoing rehabilitation after a hip joint or other lower limb impairments.

Actuation system modelling and design optimization for an assistive exoskeleton for disabled and elderly with series and parallel elasticity.

BACKGROUND: The aim of a robotic exoskeleton is to match the torque and angular profile of a healthy human subject in performing activities of daily living. Power and mass are the main requirements considered in the robotic exoskeletons that need to be reduced so that portable designs to perform independent activities by the elderly users could be adopted. OBJECTIVE: This paper evaluates a systematic approach for the design optimization strategies of elastic elements and implements an actuator design solution for an ideal combination of components of an elastic actuation system while providing the same level of support to the elderly. METHODS: A multi-factor optimization technique was used to determine the optimum stiffness and engagement angle of the spring within its elastic limits at the hip, knee and ankle joints. An actuator design framework was developed for the elderly users to match the torque-angle characteristics of the healthy human with the best motor and transmission system combined with series or parallel elasticity in an elastic actuator. RESULTS: With the optimized spring stiffness, a parallel elastic element significantly reduced the torque and power requirements up to 90% for some manoeuvres for the users to perform ADL. When compared with the rigid actuation system, the optimized robotic exoskeleton actuation system reduced the power consumption of up to 52% using elastic elements. CONCLUSION: A lightweight, smaller design of an elastic actuation system consuming less power as compared to a rigid system was realized using this approach. This will help to reduce the battery size and hence the portability of the system could be better adopted to support elderly users in performing daily living activities. It was established that parallel elastic actuators (PEA) can reduce the torque and power better than series elastic actuators (SEA) in performing everyday tasks for the elderly.

Evaluation of an ankle-foot orthosis effect on gait transitional stability during ramp ascent/descent.

Wearable ankle-foot orthoses (AFO) are widely prescribed clinically; however, their effect on balance control during ramp ascent/descent walk remains unknown. This study evaluates walking stability on a ramp during weight loading and unloading transitions of the stance phase with the effect of an adjustable AFO. An AFO is tuned firstly by tuning dorsiflexion only and then combining dorsi-plantarflexion adjustments. Gait stability is assessed from neuromotor input (centre-of-mass) and output (centre-of-pressure) responses obtained through motion-capture system and force platform. Stability margins are quantified from Nyquist and Bode methods illustrating the loading phase as stable and the unloading phase as unstable transition in all walking conditions. Further, a significant decrease in stability (p < 0.05) is observed by wearing AFO in its free mode which gets improved (p < 0.05) by tuning AFO. Results from neuromotor outputs also illustrated a strong interlimb correlation (p < 0.001), which implies a compensatory interaction between opposite limbs loading and unloading transitions. Neuromotor inputs illustrated unstable responses both in loading and unloading transitions and were observed to be greater in magnitudes compared with output margins. The overall results support the hypothesis that a wearable AFO affects gait stability during transitional phases, and by applying AFO adjustments, neuromotor balance control achieves stability margins closer to normal range.

Evaluation of an adjustable ankle-foot orthosis impact on walking stability during gait transitional phases.

Walking stability evaluation during gait transitional phases (loading and unloading) has been remained indistinct mainly due to methodological limitations and multiple biomechanical signals being used. This study introduces Nyquist and Bode methods using resultant neuromechanical output/input (O/I) responses to evaluate gait transitional stabilities. The centre of pressure and ground reaction force data are recorded experimentally as output and somatosensory input responses by the neuromotor. Six different walking conditions are simulated by wearing an adjustable orthosis using eleven healthy subjects. The rate of change in O/Is are modelled in time and frequency domains applying linear regression and stability margins are quantified applying N&B methods. Results from outputs showed loading phase as stable and unloading phase as unstable gait phases whereas the margins quantified from inputs showed unstable response during both phases. Stability margins quantified from outputs are decreased (p < 0.05) and instability margins are increased (p < 0.05) on applying ankle-foot restrictions. Overall, the neuromotor output stability margins are greater than the instabilities quantified from inputs. Furthermore, a strong interlimb negative correlation (p < 0.001) was found between loading and unloading phases computed from outputs. This study introduces new stability assessment methods with applications like evaluating lower limb impairments, varying terrains, and stability impacts of wearable devices.

An EMG-Driven Musculoskeletal Model for Estimating Continuous Wrist Motion.

EMG-based continuous wrist joint motion estimation has been identified as a promising technique with huge potential in assistive robots. Conventional data-driven model-free methods tend to establish the relationship between the EMG signal and wrist motion using machine learning or deep learning techniques, but cannot interpret the functional relationship between neuro-commands and relevant joint motion. In this paper, an EMG-driven musculoskeletal model is proposed to estimate continuous wrist joint motion. This model interprets the muscle activation levels from EMG signals. A muscle-tendon model is developed to compute the muscle force during the voluntary flexion/extension movement, and a joint kinematic model is established to estimate the continuous wrist motion. To optimize the subject-specific physiological parameters, a genetic algorithm is designed to minimize the differences of joint motion prediction from the musculoskeletal model and joint motion measurement using motion data during training. Results show that mean root-mean-square-errors are 10.08°, 10.33°, 13.22° and 17.59° for single flexion/extension, continuous cycle and random motion trials, respectively. The mean coefficient of determination is over 0.9 for all the motion trials. The proposed EMG-driven model provides an accurate tracking performance based on user's intention.

A model identification approach to quantify impact of whole-body vertical vibrations on limb compliant dynamics and walking stability.

Extensive research is ongoing in the field of orthoses/exoskeleton design for efficient lower limbs assistance. However, despite wearable devices reported to improve lower limb mobility, their structural impacts on whole-body vertical dynamics have not been investigated. This study introduced a model identification approach and frequency domain analysis to quantify the impacts of orthosis-generated vibrations on limb stability and contractile dynamics. Experiments were recorded in the motion capture lab using 11 unimpaired subjects by wearing an adjustable ankle-foot orthosis (AFO). The lower limb musculoskeletal structure was identified as spring-mass (SM) and spring-mass-damper (SMD) based compliant models using the whole-body centre-of-mass acceleration data. Furthermore, Nyquist and Bode methods were implemented to quantify stabilities resulting from vertical impacts. Our results illustrated a significant decrease (p < 0.05) in lower limb contractile properties by wearing AFO compared with a normal walk. Also, stability margins quantified by wearing AFO illustrated a significant variance in terms of gain-margins (p < 0.05) for both loading and unloading phases whereas phase-margins decreased (p < 0.05) only for the respective unloading phases. The methods introduced here provide evidence that wearable orthoses significantly affect lower limb vertical dynamics and should be considered when evaluating orthosis/prosthesis/exoskeleton effectiveness.

Evaluation of gait transitional phases using neuromechanical outputs and somatosensory inputs in an overground walk.

In a bipedal walk, the human body experiences continuous changes in stability especially during weight loading and unloading transitions which are reported crucial to avoid fall. Prior stability assessment methods are unclear to quantify stabilities during these gait transitions due to methodological and/or measurement limitations. This study introduces Nyquist and Bode methods to quantify stability gait transitional stabilities using the neuromechanical output (CoP) and somatosensory input (GRF) responses. These methods are implemented for five different walking conditions grouped into walking speed and imitated rotational impairments. The trials were recorded with eleven healthy subjects using motion cameras and force platforms. The time rate of change in O/Is illustrated impulsive responses and modelled in the frequency domain. Nyquist and Bode stability methods are applied to quantify stability margins. Stability margins from outputs illustrated loading phases as stable and unloading phases as unstable in all walking conditions. There was a strong intralimb compensatory interaction (p < .001, Spearman correlation) found between opposite limbs. Overall, both walking groups illustrated a decrease (p < .05, Wilcoxon signed-rank test) in stability margins compared with normal/preferred speed walk. Further, stabilities quantified from outputs were found greater in magnitudes than the instability quantified from inputs illustrating the neuromotor balance control ability. These stability outcomes were also compared by applying extrapolated-CoM method. These methods of investigating gait dynamic stability are considered as having important implications for the assessment of ankle-foot impairments, rehabilitation effectiveness, and wearable orthoses.

A review of gait disorders in the elderly and neurological patients for robot-assisted training.

Purpose: Ambulation is an important objective for people with pathological gaits. Exoskeleton robots can assist these people to complete their activities of daily living. There are exoskeletons that have been presented in literature to assist the elderly and other pathological gait users. This article presents a review of the degree of support required in the elderly and neurological gait disorders found in the human population. This will help to advance the design of robot-assisted devices based on the needs of the end users.Methods: The articles included in this review are collected from different databases including Science Direct, Springer Link, Web of Science, Medline and PubMed and with the purpose to investigate the gait parameters of elderly and neurological patients. Studies were included after considering the full texts and only those which focus on spatiotemporal, kinematic and kinetic gait parameters were selected as they are most relevant to the scope of this review. A systematic review and meta-analysis were conducted.Results: The meta-analysis report on the spatiotemporal, kinematic and kinetic gait parameters of elderly and neurological patients revealed a significant difference based on the type and level of impairment. Healthy elderly population showed deviations in the gait parameters due to age, however, significant difference is observed in the gait parameters of the neurological patients.Conclusion: A level of agreement was observed in most of the studies however the review also noticed some controversies among different studies in the same group. The review on the spatiotemporal, kinematics and kinetic gait parameters will provide a summary of the fundamental needs of the users for the future design and development of robotic assistive devices.Implications for rehabilitationThe support requirements provide the foundation for designing assistive devices.The findings will be crucial in defining the design criteria for robot assistive devices.

Foot trajectories and loading rates in a transfemoral amputee for six different commercial prosthetic knees: An indication of adaptability.

BACKGROUND: The relationship between the functional loading rate and heel velocities was assessed in an active unilateral transfemoral amputee (UTFA) for adaptation to six different commercial prosthetic knees. OBJECTIVE: To Investigate the short-term process of adaptability for UTFA for two types of prosthetic knees were evaluated, based on the correlation between heel vertical velocity and transient loading rate. METHODS: The loading rate was calculated from the slope of ground reaction forces (GRF) and the corresponding time. The heel velocities and GRF were obtained by a motion analysis system. RESULTS: Biomechanical adaptation was evident following a short period of prosthetic knee use based upon the mean transient impact (loading rate) and the heel vertical velocity in slow, normal and fast walking. Trend lines of transient impact versus vertical heel velocity for a set of actively controlled variable damping (microprocessor) and mechanically passive prosthetic knees were all negatively correlated, except for an amputated leg during normal pace and healthy leg during fast pace. For an amputee to adapt well to a prescribed prosthesis excellent coordination between the intact and amputated limbs is required to control placement of the amputated leg to achieve a gait comparable to healthy subjects. CONCLUSION: There are many factors such as the hip, knee flexion/extension and the ankle plantarflexion/dorsiflexion contributing to the control of the transient impact of an amputee during walking. Therefore, for enhanced control of a prosthetic knee, a multifaceted approach is required. This study showed that UTFA adaption to different prosthetic knees in the short term with slower than self-selected speed is completely achievable based on the negative correlation of ground reaction forces versus linear velocity. Reduced speed may provide the prosthetists with the vision of the amputees' progression of adaptation with a newly prescribed prosthetic knee.

Adaptive Bayesian inference system for recognition of walking activities and prediction of gait events using wearable sensors.

In this paper, a novel approach for recognition of walking activities and gait events with wearable sensors is presented. This approach, called adaptive Bayesian inference system (BasIS), uses a probabilistic formulation with a sequential analysis method, for recognition of walking activities performed by participants. Recognition of gait events, needed to identify the state of the human body during the walking activity, is also provided by the proposed method. In addition, the BasIS system includes an adaptive action-perception method for the prediction of gait events. The adaptive approach uses the knowledge gained from decisions made over time by the inference system. The action-perception method allows the BasIS system to autonomously adapt its performance, based on the evaluation of its own predictions and decisions made over time. The proposed approach is implemented in a layered architecture and validated with the recognition of three walking activities:level-ground, ramp ascent and ramp descent. The validation process employs real data from three inertial measurements units attached to the thigh, shanks and foot of participants while performing walking activities. The experiments show that mean decision times of 240 ms and 40 ms are needed to achieve mean accuracies of 99.87% and 99.82% for recognition of walking activities and gait events, respectively. The validation experiments also show that the performance, in accuracy and speed, is not significantly affected when noise is added to sensor measurements. These results show that the proposed adaptive recognition system is accurate, fast and robust to sensor noise, but also capable to adapt its own performance over time. Overall, the adaptive BasIS system demonstrates to be a robust and suitable computational approach for the intelligent recognition of activities of daily living using wearable sensors.

Prediction of gait events in walking activities with a Bayesian perception system.

In this paper, a robust probabilistic formulation for prediction of gait events from human walking activities using wearable sensors is presented. This approach combines the output from a Bayesian perception system with observations from actions and decisions made over time. The perception system makes decisions about the current gait events, while observations from decisions and actions allow to predict the most probable gait event during walking activities. Furthermore, our proposed method is capable to evaluate the accuracy of its predictions, which permits to obtain a better performance and trade-off between accuracy and speed. In our work, we use data from wearable inertial measurement sensors attached to the thigh, shank and foot of human participants. The proposed perception system is validated with multiple experiments for recognition and prediction of gait events using angular velocity data from three walking activities; level-ground, ramp ascent and ramp descent. The results show that our method is fast, accurate and capable to evaluate and adapt its own performance. Overall, our Bayesian perception system demonstrates to be a suitable high-level method for the development of reliable and intelligent assistive and rehabilitation robots.

Virtual prototyping of a semi-active transfemoral prosthetic leg.

This article presents a virtual prototyping study of a semi-active lower limb prosthesis to improve the functionality of an amputee during prosthesis-environment interaction for level ground walking. Articulated ankle-foot prosthesis and a single-axis semi-active prosthetic knee with active and passive operating modes were considered. Data for level ground walking were collected using a photogrammetric method in order to develop a base-line simulation model and with the hip kinematics input to verify the proposed design. The simulated results show that the semi-active lower limb prosthesis is able to move efficiently in passive mode, and the activation time of the knee actuator can be reduced by approximately 50%. Therefore, this semi-active system has the potential to reduce the energy consumption of the actuators required during level ground walking and requires less compensation from the amputee due to lower deviation of the vertical excursion of body centre of mass.

Effect of bandage thickness on interface pressure applied by compression bandages.

Medical compression bandages are widely used in the treatment of chronic venous disorder. In order to design effective compression bandages, researchers have attempted to describe the interface pressure applied by these bandages using mathematical models. This paper reports on the work carried out to derive the mathematical model used to describe the interface pressure applied by single-layer bandage using two different approaches. The first assumes that the bandage thickness is negligible, whereas the second model includes the bandage thickness. The estimated pressures using the two formulae are then compared, simulated over a 3D representation of a real leg and validated experimentally. Both theoretical and experimental results have shown that taking bandage thickness into consideration while estimating the pressures applied by a medical compression bandage will result in more accurate estimation. However, the additional accuracy is clinically insignificant.