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The purpose of this paper is to present gait analysis for five different terrains: level ground, ramp ascent, ramp descent, stair ascent and stair descent.

Gait analysis has been carried out using a combination of the following sensors: force-sensitive resistor (FSR) sensors fabricated in foot insole to sense foot pressure, a gyroscopic sensor to detect the angular velocity of the shank and MyoWare electromyographic muscle sensors to detect muscle’s activities. All these sensors were integrated around the Arduino nano controller board for signal acquisition and conditioning purposes. In the present scheme, the muscle activities were obtained from the tibialis anterior and medial gastrocnemius muscles using electromyography (EMG) electrodes, and the acquired EMG signals were correlated with the simultaneously attained signals from the FSR and gyroscope sensors. The nRF24L01+ transceivers were used to transfer the acquired data wirelessly to the computer for further analysis. For the acquisition of sensor data, a Python-based graphical user interface has been designed to analyze and display the processed data. In the present paper, the authors got motivated to design and develop a reliable real-time gait phase detection technique that can be used later in designing a control scheme for the powered ankle-foot prosthesis.

The effectiveness of the gait phase detection was obtained in an open environment. Both off-line and real-time gait events and gait phase detections were accomplished for the FSR and gyroscopic sensors. Both sensors showed their usefulness for detecting the gait events in real-time, i.e. within 10 ms. The heuristic rules and a zero-crossing based-algorithm for the shank angular rate correctly identified all the gait events for the locomotion in all five terrains.

This study leads to an understanding of human gait analysis for different types of terrains. A real-time standalone system has been designed and realized, which may find application in the design and development of ankle-foot prosthesis having real-time control feature for the above five terrains.

The noise-free data from three sensors were collected in the same time frame from both legs using a wireless sensor network between two transmitters and a single receiver. Unlike the data collection using a treadmill in a laboratory environment, this setup is useful for gait analysis in an open environment for different terrains.

Recognising people by their gait is a biometric of increasing interest. Recently, analysis has progressed from evaluation by few techniques on small databases with encouraging results to large databases and still with encouraging results. The potential of gait as a biometric was encouraged by the considerable amount of evidence available, especially in biomechanics and literature. This potential motivated the development of new databases, new technique and more rigorous evaluation procedures. We adumbrate some of the new techniques we have developed and their evaluation to gain insight into the potential for gait as a biometric. In particular, we consider implications for the future. Our work, as with others, continues to provide encouraging results for gait as a biometric, let alone as a human identifier, with a special regard for recognition at a distance.

Human gait analysis is based on a significant part of the musculoskeletal, nervous and respiratory systems. Gait analysis is widely adopted to help patients increase community involvement and independent living.

This paper presents a system for the classification of abnormal human gaits using a Markerless 3D Motion Capture device. This study aims at examining and estimating the spatiotemporal and kinematic parameters obtained by 3D gait analysis in diverse groups of gait-impaired subjects and compares the parameters with that of healthy participants to interpret the gait patterns.

The classification is based on mathematical models that distinguish between normal and abnormal gait patterns depending on the deviations in the gait parameters. The difference between the gait measures of the control and each disease group was examined using 95% limits of agreement by the Bland and Altman method. The scatter plots demonstrated gait variability in Parkinsonian and ataxia gait and knee joint angle variation in hemiplegic gait when compared with those of healthy controls. To prove the validity of the Kinect camera, significant correlations were detected between Kinect- and inertial-based gait tests.

The various techniques used for gait assessments are often high in price and have existing limitations like the hindrance of components. The results suggest that the Kinect-based gait assessment techniques can be used as a low-cost, less-intrusive alternative to expensive infrastructure gait lab tests in the clinical environment.

Construction workers are frequently exposed to safety hazards on sites. Wearable sensing systems (e.g. wearable inertial measurement units (WIMUs), wearable insole pressure system (WIPS)) have been used to collect workers' gait patterns for distinguishing safety hazards. However, the performance of measuring WIPS-based gait parameters for identifying safety hazards as compared to a reference system (i.e. WIMUs) has not been studied. Therefore, this study examined the validity and reliability of measuring WIPS-based gait parameters as compared to WIMU-based gait parameters for distinguishing safety hazards in construction.

Five fall-risk events were conducted in a laboratory setting, and the performance of the proposed approach was assessed by calculating the mean difference (MD), mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE) and intraclass correlation coefficient (ICC) of five gait parameters.

Comparable results of MD, MAE, MAPE and RMSE were found between WIPS-based gait parameters and the reference system. Furthermore, all measured gait parameters had validity (ICC = 0.751) and test-retest reliability (ICC = 0.910) closer to 1, indicating a good performance of measuring WIPS-based gait parameters for distinguishing safety hazards.

Overall, this study supports the relevance of developing a WIPS as a noninvasive wearable sensing system for identifying safety hazards on construction sites, thus highlighting the usefulness of its applications for construction safety research.

This is the first study to examine the performance of a wearable insole pressure system for identifying safety hazards in construction.

The purpose of this study is to test a chassis robot on rugged road cargo handling.

Attitude solution of D-H series robot gyroscope speed and acceleration sensor.

In identical experimental environments, hexapodal robots experience smaller deviations when using a four-footed propulsive gait from a typical three-footed gait for forward motion; for the same distance but at different speeds, the deviation basically keeps itself within the same range when the robot advances forward with four-foot propulsive gait; because the foot slide in the three-footed gait sometimes experiences frictions, the robot exhibits a large gap in directional deviations in different courses during motion; for motion using a four-footed propulsive gait, there are minor directional deviations of hexapodal robots resulting from experimental errors, which can be reduced through optimizing mechanical structures.

Planning different gaits can solve problems existing in some typical gaits. This article has put forward a gait planning method for hexapodal robots moving forward with diverse gaits as a redundant multifreedom structure. Subsequent research can combine a multiparallel-legged structure to analyze kinematics, optimize the robot’s mechanical structure and carry out in-depth research of hexapod robot gaits.

Current healthcare applications produce a complex and inaccessible set of data that often needs to be investigated simultaneously. As such the conflicting software applications and mental effort being demanded from the user result in time‐consuming analysis and diagnosis. The purpose of this paper is to provide a prototype, interactive system for management of multiple data sets, currently used for gait analysis capturing, reconstruction and diagnosis. In summary, this work is concerned with the development of interactive information‐visualisation software that assists medical practitioners in simplifying and enhancing the retrieval, visualisation and analysis of medical data with the intention of improving the overall system leading to an improved service for the user and patient experience.

The design of the proposed system aims to combine all the related existing software currently used for gait analysis and diagnosis under one, user‐friendly package. The latter will have the capacity to offer also real‐time, three dimensional (3D) representations of all the derived data (CT, MRI, motion capture) in an interactive virtual reality (VR) environment.

It is intended that the proposed prototype solutions will enhance interactive systems for management of multiple data sets, currently used for gait analysis capturing, reconstruction and diagnosis. The derived data encapsulate a plethora of multimedia information aiming to enhance medical visualisation.

The proposed system offers simulation capacity and a VR visualisation experience, which enhances the gait analysis diagnostic process. The 3D data can be manipulated in real‐time through a novel human‐computer interface which uses multimodal interaction through the use of graphical user interfaces and gesture recognition. The system aims towards a cost‐effective, clearly presented and timely accessible system that follows a threefold approach; It entails managing the extensive amount of the daily produced medical data, combining the scattered information related to one patient in one interface with a filtering criteria to the required information, and visualising in 3D the data from different sources, in order to improve 3D mental mapping, increase productivity and consequently ameliorate quality of service and management.

The recent advancement in gait analysis combines internet of things that provides better observations of person living behavior. The biomechanical model used for elderly and physically challenged persons is related to gait-related parameters, and the accuracy of the existing systems significantly varies according to different person abilities and their challenges. The paper aims to discuss these issues.

Deployment of wearable sensors in gait analysis provides a better solution while tracking the changes of the personal style, and this proposed model uses an electronics system using force sensing resistor and body sensors.

Experimental results provide an average gait recognition of 95 percent compared to the existing neural network-based gait analysis model based on the walking speeds and threshold values.

The sensors are used to monitor and update the predicted values of a person for analysis. Using IoT a communication process is performed in the research work by identifying a physically challenged person even in crowded areas.

Most current lower extremity exoskeletons emphasize assistance for walking rather than stability. The purpose of this paper is to propose a rehabilitation gait based on the transfer of gravity center to improve the balance of exoskeleton rehabilitation training of the hemiplegic patients in the frontal plane, reducing the dependence on crutches/walking frames.

The real-time and predictable instability factors of human and exoskeleton system (HES) are analyzed. Inspired by the walking balance strategy of the blind, a rehabilitation gait based on the transfer of gravity center is proposed and studied by modeling and experimental test and is finally applied to the prototype – Zhejiang University lower extremity exoskeleton (ZJULEEX) – to verify its feasibility.

At least three real-time and predictable factors cause the instability of HES, and the factor of lateral tilt caused by gravity should be focused in the balance control of frontal plane. With the proposed gait, the hip height of stepping leg of HES does not reduce obviously even when the crutches do not work, which can improve the balance of HES.

However, the rehabilitation gait control needs to be more complete and intelligent to response to other types of perturbations to further improve the balance of HES. In addition, more clinical trials should be conducted to evaluate the effect of the proposed gait.

May bring happiness to the rehabilitation of patients with hemiplegia.

The rehabilitation gait based on the transfer of gravity center to improve the balance of HES is first proposed and applied to HES.

The aim of this paper is to present and evaluate a methodology for automatically constructing and applying the physiologically‐realistic boundary/loading conditions for use in the structural finite element analysis of the femur during various exertion tasks (e.g. gait/walking).

To obtain physiologically‐realistic boundary/loading conditions needed in the femur structural finite element analysis, a whole‐body musculoskeletal inverse dynamics analysis is carried out and the resulting muscle forces and joint reaction forces/moments extracted.

The finite element results obtained are compared with their counterparts available in literature and it is found that the overall agreement is acceptable while the highly automated procedure for the finite element model generation developed in the present work made the analysis fairly easy and computationally highly efficient. Potential sources of errors in the current procedure have been identified and the measures for their mitigation recommended.

The present approach enables a more accurate determination of the physiological loads experienced by the orthopedic implants which can be of great value to implant designers and orthopedic surgeons.

This study aims to present a type of metamorphic mechanism-based quadruped crawling robot. The trunk design of the robot has a metamorphic mechanism, which endows it with excellent crawling capability and adaptability in challenging environments.

The robot consists of a metamorphic trunk and four series-connected three-joint legs. First, the walking and steering strategy is planned through the stability and mechanics analysis. Then, the walking and steering performance is examined using virtual prototype technology, as well as the efficacy of the walking and turning strategy.

The metamorphic quadruped crawling robot has wider application due to its variable trunk configuration and excellent leg motion space. The robot can move in two modes (constant trunk and trunk configuration transformation, respectively, while walking and rotating), which exhibits outstanding stability and adaptability in the examination and verification of prototypes.

The design can enhance the capacity of the quadruped crawling robot to move across a complex environment. The virtual prototype technology verifies that the proposed walking and steering strategy has good maneuverability and stability, which considerably expands the application opportunity in the fields of complicated scene identification and investigation.