Walking Motion Research Articles

Fall-risk assessment of aged workers using wearable inertial measurement units based on machine learning

Falls are the major cause of fatal and nonfatal incidents among aged workers. Estimating individual fall risk is crucial for occupational protection and public health. This study aimed to develop a fall-risk assessment method based on Machine Learning (ML) and Inertial Measurement Units (IMUs). A total of 28 aged workers (60 to 80 years old) participated in this study, recruited from community sanitation workers and janitors. They were categorized into high and low fall-risk groups based on functional gait assessment. Each participant performed 5 sets of motion experiments in the lab, covering 6 daily motions. We gathered their kinematic data with IMUs for training ML-based fall-risk assessment models. Five classic ML classifiers were optimized using grid search, and a Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) hybrid deep neural network was built to recognize walking motion from kinematic data for input into the fall-risk assessment model. The results demonstrated that ML classifiers trained with walking motion data exhibited superior performance. Cross-validation revealed that the optimized Random Forest classifier, with IMU on the right upper leg, reached 91.3 % accuracy. Additionally, the CNN-LSTM models were evaluated using F1-score, which can balance accuracy and coverage of model performance evaluation. The CNN-LSTM achieved a maximum F1-score of 95.18 %, proving their effectiveness in extracting walking motion data. These findings indicate that the developed IMU-based ML method exhibits excellent performance in assessing fall risk, potentially allowing aged workers to assess their fall risk before clinical diagnosis by embedding it in wearable IMUs.

Epidemiological Data of Patients Consulted to Physical Therapy Clinic in the 2023 Kahramanmaraş Earthquake

On February 6, 2023, 7.8-magnitude earthquake occurred in Kahramanmaraş, Türkiye. This earthquake was one of the most devastating disasters to hit Türkiye, resulting in an official death count of over 45,000. In this study, we aimed to determine the injury patterns of the patients who were consulted to the physical therapy and rehabilitation clinic after the Kahramanmaraş earthquake, and to ensure that their physicians were better prepared for possible earthquakes. Our study was completed between February and June 2023. All patients, male and female, who had earthquake-related injuries and were consulted to the physical therapy unit were included. Discharged patients were screened retrospectively. Inpatients were investigated prospectively. A total of 220 patients were included in the study. The patients were examined in terms of age, gender, date of application, pain score, time under the dent, complaint at admission, additional disease, type of injury, and treatment applied. Statistical analyzes were performed using SPSS version 22.0 software. The most frequently affected age group was 15-30 years old. The most common complaints were pain, limitation of movement and difficulty in walking. The most common surgical procedures are fasciotomy, internal fixation, and amputation. The most commonly injured limbs are the lower extremities. The most common level of amputation was transtibial amputation. After the earthquake, patients need physical therapy and rehabilitation. The knowledge and experience of the physicians of the relevant branches about the frequently observed injury patterns should be increased. This study is generally in line with most other studies reporting the epidemiology of injury after earthquakes. However, there is no standardization among the studies. Therefore, standardization in reporting earthquake injuries is necessary for evidence-based response policy planning after natural disasters.

Being an older person: modulation of walking speed with geriatric walking motion avatars

The phenomenon of one’s walking speed being affected by that of other pedestrians on the street is often observed in real-world scenarios. However, the effects of the motion and familiarity of avatars on a user in virtual reality have not been thoroughly investigated. Therefore, this study explored how alterations in human avatars affect the walking speed and sensation of users. Furthermore, walking speed has been shown to be influenced not only by visual perception but also by cognition. However, few studies have investigated the relationships between visual perception, cognition, and behavior. Therefore, we examined the relationships between stereotypical words for older people, a representative example of cognition-induced changes in walking speed, and visual perception stimuli of avatars. The results revealed a significant interaction between the stereotype and avatar walking motion. In particular, in the absence of the stereotype, participants were strongly affected by the older walking motion of the avatar, and their walking speed decreased. We also found that the walking motion of avatars significantly affects participants walking speed and sensation. These findings provide pioneering insights into the psychological factors that regulate human walking speed and propose a new method for manipulating the user’s walking speed and sensation in VR space.

Antie-theft Device Tracking System

This project's goal is to develop an Android application that offers SMS-based location tracking capabilities for Android devices. We can also follow the images of the individual who took our Android phone. This function supports Android OS and sends and receives emails and SMS in response to calls. With simple SMS commands, you can track your Android device. Tracing a location: We can use basic SMS commands to locate the misplaced phone. In a theft gadget, the camera can be remotely manipulated to take pictures. It is said of mobile gadgets that they are portable and that a person can carry them from one place to another. Mobile device theft occurs frequently, and the current system watches users' walking patterns and movements.

Electricity-Driven Strategies for Bioinspired Multifunctional Swimming Marangoni Robots Based on Super-Aligned Carbon Nanotube Composites.

Marangoni actuators that are propelled by surface tension gradients hold significant potential in small-scale swimming robots. Nevertheless, the release of "fuel" for conventional chemical Marangoni actuators is not easily controllable, and the single swimming function also limits application areas. Constructing controllable Marangoni robots with multifunctions is still a huge challenge. Herein, inspired by water striders, electricity-driven strategies are proposed for a multifunctional swimming Marangoni robot (MSMR), which is fabricated by super-aligned carbon nanotube (SACNT) and polyimide (PI) composite. The MSMR consists of a Marangoni actuator and air-ambient actuators. Owing to the temperature gradient generated by the electrical stimulation on the water surface, the Marangoni actuators can swim controllably with linear, turning, and rotary motions, mimicking the walking motion of water striders. In addition, the Marangoni actuators can also be driven by light. Importantly, the air-ambient actuators fabricated by SACNT/PI bilayer structures demonstrate the function of grasping objects on the water surface when electrically Joule-heated, mimicking the predation behavior of water striders. With the synergistic effect of the Marangoni actuator and air-ambient actuators, the MSMR can navigate mazes with tunnels and grasp objects. This research will provide a new inspiration for smart actuators and swimming robots.

Using Computer Vision to Annotate Video-Recoded Direct Observation of Physical Behavior.

Direct observation is a ground-truth measure for physical behavior, but the high cost limits widespread use. The purpose of this study was to develop and test machine learning methods to recognize aspects of physical behavior and location from videos of human movement: Adults (N = 26, aged 18-59 y) were recorded in their natural environment for two, 2- to 3-h sessions. Trained research assistants annotated videos using commercially available software including the following taxonomies: (1) sedentary versus non-sedentary (two classes); (2) activity type (four classes: sedentary, walking, running, and mixed movement); and (3) activity intensity (four classes: sedentary, light, moderate, and vigorous). Four machine learning approaches were trained and evaluated for each taxonomy. Models were trained on 80% of the videos, validated on 10%, and final accuracy is reported on the remaining 10% of the videos not used in training. Overall accuracy was as follows: 87.4% for Taxonomy 1, 63.1% for Taxonomy 2, and 68.6% for Taxonomy 3. This study shows it is possible to use computer vision to annotate aspects of physical behavior, speeding up the time and reducing labor required for direct observation. Future research should test these machine learning models on larger, independent datasets and take advantage of analysis of video fragments, rather than individual still images.

Divergent Component of Motion Planning and Adaptive Repetitive Control for Wearable Walking Exoskeletons.

Wearable walking exoskeletons show great potentials in helping patients with neuro musculoskeletal stroke. Key to the successful applications is the design of effective walking trajectories that enable smooth walking for exoskeletons. This work proposes a walking planning method based on the divergent component of motion to obtain a stable joint angle trajectory. Since periodic and nonperiodic disturbances are ubiquitous in the repeating walking motion of an exoskeleton system, a major challenge in the walking control of wearable exoskeleton is the joint angle drift problem, that is, the joint angle motion trajectories are not necessarily periodic due to the presence of disturbance. To address this challenge, this work develops an adaptive repetitive control strategy to guarantee that the motion trajectories of joint angle are repetitive. In particular, by treating the disturbance as system uncertainties, an adaptive controller is designed to compensate for the uncertainties based on an integral-type Lyapunov function. A fully saturated learning approach is then developed to achieve asymptotic tracking of repetitive walking trajectories. Extensive experiments are carried out to demonstrate the effectiveness of the tracking performance.

Comparative foraging behavior of 3 heron species in small standing-water ecosystems in the arid zone of Oman

Abstract The composition of assemblages, diet and behavior of waterbird species with similar ecological features are important aspects in the functioning of aquatic ecosystems. Closely related animal species often share resources such as space and food in ways that reduce competition, but if the diets of different species strongly overlap, interspecific competition may intensify. This analysis examined behavioral data relating to Great Egret, Little Egret, and Squacco Heron to explore their foraging efficiencies in rich aquatic habitats in an arid zone during post-breeding movements. The fieldwork was carried out in small estuaries of a Wadi on the southern coast of Oman. The frequency of interactions was the highest in Squacco Heron and the lowest in Great Egret. However, the differences in the numbers of inter- and intra-specific interactions between the 3 species were significant. Activity indices calculated for a 5-min period, i.e., the number of interactions (interaction index) and times of flying and walking (movement index) differed among the 3 species. The number of successful attacks was the highest in Squacco Heron, while the foraging effectiveness of Great Egret and Little Egret was similar. GLM analysis showed that only the movement index was significant, as it had a positive impact on individual foraging success. Great Egret caught more fish than the other 2 heron species which, in turn, caught a greater number of smaller prey items, mostly invertebrates. This study shows that heron species in the same rich habitat employ different foraging tactics. In comparison to the other two heron species, the foraging tactics of Squacco Heron seem to be the most susceptible to competition. However, its greater mobility and using different foraging tactics, enhance its foraging success.

Evaluation of the accuracy of a UWB tracker for in-home positioning for older adults

The population of older adults is rapidly growing. In-home monitoring systems have been used to support aging-in-place. Ambient sensors or wearable localizers can be used but may be too low resolution, while camera systems are invasive to privacy. Ultra-wideband (UWB) localization offers precise positioning by placing anchors throughout the house and wearing a tag that is tracked by the anchors. In this study, the accuracy of UWB for indoor tracking was evaluated in a motion capture gait lab and in a mock condo in the Glenrose Rehabilitation Hospital. First, the configuration of UWB was tested, changing factors related to sampling time, anchor placement and line-of-sight. Comparing these factors to the configurations recommended by the manufacturer guidelines, accuracies remained within 14 cm. We then performed static and dynamic accuracy tests, with dynamic testing comprised of rolling and walking motions. In the motion capture lab, we found localization accuracies of 7.0 ± 11.1 cm while in the mock condo, we found accuracies of 27.3 ± 12.9 cm. Dynamic testing with rolling motions had an average of 19.1 ± 1.6 cm while walking was 20.5 ± 4.2 cm. The mean accuracy of UWB is within the 30 cm target for indoor localization.

The Systematic Construction of Emergency Medical Security System in Long-Distance Walking Movement on Urban Paved Roads

Objective To explore the scope of building emergency medical security mechanism in urban paved road environment, and to provide reference, sample data and improvement suggestions for building emergency medical security mechanism in such specific environment. Methods The data of rescue personnel deployment, rescue materials allocation, rescue force monitoring, actual rescue situation, emergency plan and relevant regulations setting, training and other aspects of the emergency medical security mechanism in March and April 2023 were collected, and the data were analyzed. Results (1) The hiking distance was 40km and the road conditions were urban paved roads. There were 1150 official trekkers and 65 people were treated medically. (2) The most common symptoms of outdoor hiking included skeletal muscle injury (19.48%), foot skin and soft tissue injury (18.17%), fever (2.61%) and diarrhea (0.61%). (3) In March, 18.36% of the core medical team members and 20.41% of the first aid volunteers who underwent systematic training took up the task of supporting hiking activities. In April, the core medical team personnel who undertook the task of supporting hiking activities accounted for 1.23% of the total number of the security team, and the first aid volunteers who underwent systematic training accounted for 37.04%. (4) According to local conditions, the multi-vehicle rescue and transport mode was adopted, which was combined with the modified commercial rescue vehicle (42.86%) with the on-board emergency medical unit (EMU) and the ordinary ambulance (28.57%). (5) More than 700 pieces of 34 kinds of medical materials and 40 sets of mobile communication equipment, which were put into use after the feasibility study of the expert group and the technical group, guaranteed the competition from the hardware level. Conclusion The construction of emergency medical support mechanism in outdoor walking sports needs to pay attention to environmental characteristics, operation mode of support team, personnel and adaptability training, equipment and deployment of medical support materials, deployment and cooperation of communication and transport capacity, reasonable support plan and other factors. Medical volunteers who have been systematically trained can undertake part of outdoor medical rescue work. Pre-activity training and regular re-training of medical volunteers can ensure the safety of outdoor activities.

Assessing the performance of pedestrian stoop evacuation under height constraints with different motivations

In some specific pedestrian evacuation circumstances such as where the presence of fire smoke, pedestrians are forced to take abnormal walking postures like stooping or crawling to avoid exposure to harmful smoke. Many previous studies have focused on the characteristics of pedestrians' upright walking or crawling. However, the performance of pedestrians’ stoop evacuation has not been comprehensively studied. In the present paper, a series of experiments were carried out to understand the performance of pedestrian stoop movement by considering three height constraints (H = 1.0, 1.5, and 2.0 m) and two motivation levels (normal walking and running movement). To quantificationally analyze the speed features, the trajectories of pedestrians were first extracted from video recordings. With these data, the distribution of pedestrian walking speed and the speed reduction characteristics during long-distance stoop motions were discussed. In addition, physiological indicators like blood pressure and heart rate (HR) were compared before and after the experiment. Finally, according to the collected HR data and questionnaire data, HR-based evaluation and self-reported evaluation of stoop movement intensity were discussed. The findings in this paper provide fundamental data for pedestrian stoop movement with height constraints which could be beneficial to the evacuation models and the building safety design.

A study on contaminant leakage from Airborne Infection Isolation room during medical staff entry; Implementation of walking motion on hypothetical human model in CFD simulation

The recent outbreak of respiratory infectious diseases such as Middle East Respiratory Syndrome (MERS) and Coronavirus Disease-19 (COVID-19) highlights the critical role of Air Infection Isolation (AII) rooms in preventing the spread of disease. However, the risk of contaminant leakage from the AII room during medical staff interactions remains a significant challenge. This study advances our understanding by employing Computational Fluid Dynamics (CFD) simulations with a novel approach. While CFD simulations mitigate some limitations of field experiments, such as measurement resolution and variable changes, their accuracy is often limited by the oversimplification of models, particularly in representing human models and movement. Unlike prior studies, we incorporate minimal simplification, featuring a human model with Personal Protective Equipment (PPE) and realistic walking motions. This study explores four distinct scenarios with varied human movements, offering a comprehensive analysis of airflow and contaminant dispersion in AII rooms. The results indicated significant differences in airflow patterns and contaminant distribution when realistic walking motion was implemented in the human model, as opposed to simplified movement models. The contaminant leakage from the AII room ranged from 20.6 % to 28.6 %, suggesting that prior studies may underestimate infection risks due to oversimplified human models and motions. These findings underscore the importance of implementing realistic human models and motions in CFD simulations for accurate infection risk assessment in AII rooms. Additionally, our study opens pathways for future research to explore more complex human interactions in clinical settings, enhancing infection control strategies.

The effect of intense and distributed exercise in teaching the disease and controlling the compatibility of some body movements in sports walking among young women in Basmaya Sports Academy

This research dealt with the effect of intensive and distributed exercise on teaching to perform and control the compatibility of movements of body parts in athletic walking at the Basmaya Sports Academy for young women. The objective of the research focus on preparing special exercises with both intensive and distributed styles and identifying their effects in teaching , performing and control the compatibility of movements of body parts in athletic walking at the Basmaya Sports Academy For Young Women..The hypotheses included that there were statistically significant differences between the results of the pre and posttests of the two experimental research groups in teaching performance and controlling the motor compatibility of body parts in athletic walking. The research community was determined by the budding of the Basmaya Academy for the academic year 2019-2020, as the sample included (12) players ( female ) who were intentionally chosen from the beginners in teaching performance , controlling and matching the movements of body parts ..After the researcher made sure of the homogeneity of the sample, they were randomly distributed in two equal groups and performed parity in testing and evaluating the performance and kinetic compatibility of body parts in athletic walking. One of the groups represented the experimental group which is its teaching was according to intensive method ,while the other group used distributed method in teaching sport walking movements .The implementation of the main experiment took 5 weeks, with three teaching units per week. After the specified period, the tests and evaluations of the motions under study were re-examined. Statistical treatments were performed using the (spss) program by adopting the two tests (T) for the independent and interrelated samples. Conclusions showed excellence of 2nd group ( with distributed exercise ) and preference over first experimental group ( with intensive exercise ) in terms of teaching and controlling the kinematic compatibility of the movements of the parts of the body walking, and accordingly the recommendations came in the necessities of adopting exercises for the distributed method in teaching young beginners to the movements of athletic walking and controlling their compatibility

Research on force/position switching control of servo actuator for hydraulically driven joint robot

According to the robot’s walking motion characteristics, the position/force switching control is studied to realize the segmental control of the robot stroke. This stroke is controlled by position when the foot end of the robot descends from the suspension to the ground. To avoid excessive contact force when the robot touches the ground, force control is carried out when the foot touches the ground. Due to the force and position control methods and control parameters of the hydraulic quadruped robots are different, the precise mathematical model for the joint position control and joint force control of the leg joints of the hydraulic quadruped robot is established using the system identification method. A fuzzy multi-model switching algorithm is proposed to solve the problem of jumping and jitter of system parameters in the process of force/position switching. Through simulation and prototype experiments, fuzzy multi-model switching is compared with direct switching and multi-model switching, and the switching effect of the algorithm is verified.

Magnetically driven formation of 3D freestanding soft bioscaffolds.

3D soft bioscaffolds have great promise in tissue engineering, biohybrid robotics, and organ-on-a-chip engineering applications. Though emerging three-dimensional (3D) printing techniques offer versatility for assembling soft biomaterials, challenges persist in overcoming the deformation or collapse of delicate 3D structures during fabrication, especially for overhanging or thin features. This study introduces a magnet-assisted fabrication strategy that uses a magnetic field to trigger shape morphing and provide remote temporary support, enabling the straightforward creation of soft bioscaffolds with overhangs and thin-walled structures in 3D. We demonstrate the versatility and effectiveness of our strategy through the fabrication of bioscaffolds that replicate the complex 3D topology of branching vascular systems. Furthermore, we engineered hydrogel-based bioscaffolds to support biohybrid soft actuators capable of walking motion triggered by cardiomyocytes. This approach opens new possibilities for shaping hydrogel materials into complex 3D morphologies, which will further empower a broad range of biomedical applications.

Automatic Detection of Faults in Simulated Race Walking from a Fixed Smartphone Camera

Abstract Automatic fault detection is a major challenge in many sports. In race walking, judges visually detect faults according to the rules. Hence, automatic fault detection systems will help a training of race walking without experts’ visual judgement. Some studies have attempted to use sensors and machine learning to automatically detect faults. However, there are problems associated with sensor attachments and equipment such as a high-speed camera, which conflict with the visual judgement of judges, and the interpretability of the fault detection models. In this study, we proposed an automatic fault detection system for non-contact measurement. We used pose estimation and machine learning models trained based on the judgements of multiple qualified judges to realize fair fault judgement. We verified them using smartphone videos of normal race walking and walking with intentional faults in several athletes including the medalist of the Tokyo Olympics. The results show that the proposed system detected faults with an average accuracy of over 90%. We also revealed that the machine learning model detects faults according to the rules. In addition, the intentional faulty walking movement of the medalist was different from that of other walkers. This finding informs realization of a more general fault detection model.

Bulanık Mantık Kontrolü kullanarak hedeflere atış yapan dört bacaklı bir robotun dinamik simülasyonu

This study aims to track and shoot targets with a gun mounted on a quadruped robot in rough terrain and different environmental conditions for increase deterrence in defense. The dynamic movements of the system were modelled as planarly and it was used in walking movement. PID control was used for control the robot leg joints while walking. Because of the walking motion, the success of the target tracking and shooting simulations was examined under the disruptive effects. In order to track the targets whose coordinates were randomly determined and the elevation angle was calculated. It was observed that the robot tracked the targets at 3°, 6° and 9° with a maximum error of 0.6°. In addition, shootings were made to fixed targets located at 10 different coordinates. It was seen that the maximum shooting error value was 16 cm. So, this study will make important contributions to the defense industry.

Human micro-doppler detection and classification studies at Mersin University using real outdoor experiments via C-band FMCW radar

In this work, a unique radar hardware is introduced for human-gait micro-Doppler studies. The developed radar sensor operates in C-band microwave frequencies. We share several outdoor experiments at Mersin University facilities to detect and characterize human walking and running movements. In these experiments, various walking and running movements were performed with different people. To examine the Doppler properties of human motion, raw data gathered is transformed onto 2D joint-time-frequency plane. The generation of micro-Doppler signatures in the transformed data is the first step in the extraction of features of the walking/running human motion. It is shown that the directions, durations, range distances as well as torso and limb velocities of walking and running human movements in each experiment are successfully obtained from these micro-Doppler signatures.

Analysis of muscle synergy and gait kinematics during regain of gait function through rehabilitation in a monoplegic patient.

We conducted muscle synergy and gait analyses in a monoplegic patient whose gait function improved through training, to explore the possibility of using these parameters as indicators of training. A 49-year-old male had monoplegia of the right lower limb caused by infarction of the left paracentral lobule. After 2 months of training, he was able to walk and returned to work. Consecutive analyses were done after admission. Muscle synergy analysis: during walking, surface electromyograms of gluteus maximus, quadriceps femoris, adductor femoris, hamstrings, tibialis anterior, medial/lateral gastrocnemius, and soleus on both sides were recorded and processed for non-negative matrix factorization (NNMF) analysis. Gait analysis: markers were placed at foot, and walking movements were video recorded as changes in position of the markers. Compared with three muscle synergies detected on the non-paretic side, two muscle synergies were extracted on the paretic side at admission, and the number increased to three and then four with progress in rehabilitation training. Changes in weighting and activity of the muscle synergies were greater on the non-paretic side than on the paretic side. With training, the knee joint flexor and the ankle dorsiflexor activities on the paretic side and the gluteus maximus activity on the non-paretic side increased during swing phase as shown by weight changes of muscle synergies, and gait analysis showed increased knee joint flexion and ankle joint dorsiflexion during swing phase in the paretic limb. On the non-paretic side, however, variability of muscle activity was observed, and three or four muscle synergies were extracted depending on the number of strides analyzed. The number of muscle synergies is considered to contribute to motor control. Rehabilitation training improves gait by increasing the number of muscle synergies on the paretic side and changing the weights of the muscles constituting the muscle synergies. From the changes on the non-paretic side, we propose the existence of compensatory mechanisms also on the non-paretic side. In muscle synergy analysis, in addition to the filters, the number of strides used in each analysis set has to be examined. This report highlights the issues of NNMF as analytical methods in gait training for stroke patients.

Design, modeling, and control of a novel soft-rigid knee joint robot for assisting motion

AbstractThis paper presents the design, modeling, and control of a novel soft-rigid knee joint robot (SR-KR) for assisting motion. SR-KR is proposed to assist patients with knee joint injuries conducting gait training and completing walking movements. SR-KR consists of a novel soft-rigid bidirectional curl actuator, a thigh clamping structure, and a crus clamping structure. The actuating part of SR-KR is composed of soft materials, which ensures the wearing comfort and safety, while the wearing parts contain rigid structure, which ensures the efficient transmission of torque. The bending deformation model of SR-KR is established, which reveal the relationship among SR-KR’s bending curvature, working pressure, and output torque. Experiments show that SR-KR can provide more than 26.3 Nm torque for knee joint motion in human gait range. A double closed loop servo control system including attitude servo and pressure servo is built to better apply SR-KR. Mechanical property test, trajectory-driven test, and lower limb wearing test have been conducted, which show that SR-KR has ability to assist in lower limb motion and has potential in the fields of rehabilitation and human enhancement.