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As the global population ages, older adults face reduced physical function and increased risks of falls. Virtual reality-based walking-in-place exercise (VR-WIPE) simulates walking movements, making it a safer alternative for older adults, particularly those at risk of falling. This study aims to evaluate the effects of VR-WIPE on step count and balance control ability in older adults. It seeks to determine whether VR-WIPE is more effective than traditional exercise methods in improving these parameters. Twenty older women (aged 65 and over) participated in this study, conducted over four weeks. Participants were randomly assigned to a control group (seated cycling) or an experimental group (VR-WIPE). Pre- and post-intervention assessments were conducted to measure balance control ability and step count, using the short form berg balance scale (SFBBS) and PHYSIO sensing equipment. Post-intervention, the VR-WIPE group showed significant improvements in SFBBS scores, forward–backward walking, and postural sway measures, compared to the control group. Step count during the 2-min walking-in-place task also significantly increased in the VR-WIPE group. The study concludes that VR-WIPE is more effective than traditional seated cycling in improving step count and balance control ability in older adults. The findings suggest that VR-WIPE could be a valuable rehabilitation tool for fall prevention and improving physical function.

Aim: The purpose of this study is to measure the acceleration of upper body (pelvis, shoulder and head) during walking and to investigate whether the acceleration patterns differ among age groups and genders. Methods: Twenty-nine old subjects and thirty young subjects participated in this study. Tri-axial accelerations were measured on the back of upper body (head, shoulder and pelvis). Subjects performed two trials of walking on a treadmill in their own comfortable speeds. Three-way ANOVA (repeated measures) was carried out for the root mean square of each directional acceleration with age, gender and sensor position as independent factors. Results: Age effect was significant on the RMS accelerations of the transverse plane. In the anteroposterior direction, the pelvis acceleration was greater in the younger group, while the head acceleration was greater in the older group ($p<0.05$). In the mediolateral direction, the pelvis acceleration was comparable between age groups but the shoulder and head accelerations were greater in the older group ($p<0.01$). The overall accelerations were greater in men than in women ($p<0.01$). The phase-delay and attenuation of shoulder acceleration relative to the pelvis acceleration was smaller for the elderly in AP and ML directions ($p<0.05$). Normalization of RMS accelerations by height, weight and leg length did not affect the age differences but negated the gender differences. Discussion: Greater head acceleration in older subjects were related to less attenuation of acceleration in the upper body, which may affect the sensory systems in the head and deteriorate balance control during locomotion.

The objective of this research was to evaluate the effects of biofeedback equipment with a tilt sensor and a neck correction exercise program on balance control ability, proprioception, and craniovertebral angle (CVA) in young adults. Ten students (M/F, 7/3) aged 20–30 years attending Sunmoon University in Asan-si, South Korea, participated in this study. All subjects participated in three sessions. These sessions consisted of a biofeedback session with a tilt sensor, followed by an exercise session, and a combined session involving biofeedback equipment with a tilt sensor and exercise. Each session takes 30min. The sessions were conducted with a one-day interval between each one. Before the start of the experiment, physical characteristics were measured, and proprioception, balance control ability, and CVA were evaluated. The exercise program significantly improved the stability index (SI) in the eyes-closed state. The biofeedback program resulted in improvement in left rotation, and the CVA was significantly improved after all exercise sessions. In conclusion, a neck correction exercise program that actively moves muscles may have a potential positive impact on balance control ability. Biofeedback equipment might aid in enhancing proprioception by preventing forward head posture (FHP).

This paper presents a contribution to the study of control law structures and to the selection of relevant sensory information for humanoid robots in situations where dynamic balance is jeopardized. In the example considered, the system first experiences a large disturbance, and then by an appropriate control action resumes a "normal" posture of standing on one leg. In order to examine the control laws used by humans, an experiment was performed in which a human subject was subjected to perturbations and the ensuing reactions were recorded to obtain complete information about the subject's motion and ground reaction force. Then, a humanoid model was advanced with characteristics matching those of the experimental human subject. The whole experiment was simulated so as to achieve a simulated motion that was similar to that of the human test subject. The analysis of the control laws applied, and the behavior of selected ground reference points (ZMP, CMP and CM projection on the ground surface), provided valuable insight into balance strategies that humanoid robots might employ to better mimic the kinetics and kinematics of humans compensating for balance disturbances.

Moving the torso laterally in a walking biped robot can be mechanically more torque-efficient than not moving the torso according to recent research. Motivated by this observation, a torque-efficient torso-moving balance control strategy of a walking biped robot subject to a persistent continuous external force is suggested and verified in this paper. The torso-moving balance control strategy consists of a preliminary step and two additional steps. The preliminary step (disturbance detection) is to perceive the application of an external force by a safety boundary of zero moment point, detected approximately from cheap pressure sensors. Step 1 utilizes center of gravity (COG) Jacobian, centroidal momentum matrix and linear quadratic problem calculation to shift the zero moment point to the center of the support polygon. Step 2 makes use of H_∞ controllers for a more stable state shift from single support phase to double support phase. By comparing the suggested torso moving control strategy to the original control strategy that we suggested previously, a mixed balance control strategy is suggested. The strategy is verified through numerical simulation results.

In this paper, we propose a force-resisting balance control strategy for a walking biped robot subject to an unknown continuous external force. We assume that the biped robot has 12 degrees of freedom (DOFs) with position-controlled joint motors, and that the unknown continuous external force is applied to the pelvis of the biped robot in the single support phase (SSP) walking gait. The suggested balance control strategy has three phases. Phase 1 is to recognize the application of an unknown external force using only zero moment point (ZMP) sensors. Phase 2 is to control the joint motors according to a method that uses a genetic algorithm and the linear interpolation technique. Against an external continuous force, the robot retrieves the pre-calculated solutions and executes the desired torques with interpolation performed in real time. Phase 3 is to make the biped robot move from the SSP to the double support phase (DSP), rejecting external disturbances using the sliding mode controller. The strategy is verified by numerical simulations and experiments.

The study of individual mobile devices has been widely conducted. In this paper, we propose the design of some fuzzy logic control systems for the control of the Segway-type mobile robot, which is a kind of inverted pendulum system. We first design two conventional fuzzy logic control systems for position and balance control of the Segway-type mobile robot. And then, we design another two fuzzy logic control systems with a single input variable for position and its balance control. We also propose a new defuzzification method called vectored sum scheme. Finally, in order to check the feasibility of the proposed systems we present some simulation examples.

In this paper, we propose standing and stepping control with switching rules based on angular momentum around the ankle for planar bipedal robots. A theoretical analysis under some approximation and mass distribution conditions shows that the proposed standing control maximizes stable regions. We can then classify the state of robots into the following three categories: (1) stabilizable via ankle torque; (2) unstabilizable only via ankle torque and stabilizable via ankle torque and trunk posture control; and (3) unstabilizable via ankle torque and trunk posture control. This criterion enables switching rules to appropriately switch robot control to balance control via ankle torque, balance control via ankle torque and trunk posture control, or stepping control. The proposed method is applicable to robots without feet. Simulation results demonstrate that the proposed method appropriately switches control according to the amplitudes of disturbances and maintains the balance of robots with and without feet.

We developed a bipedal robot equipped with brake and clutch mechanisms to change the number of active and passive joints, thereby enabling various types of movements including normal active walking using 12-dof joints, under-actuated walking using brake, and passive-based walking using clutch and passive joints. In this paper, we describe three technologies to achieve the proposed system and show experimental results on active and semi-passive walking. The first technology comprises a small and high-strength clutch mechanism to sustain the massive weight of life-sized robots using actuators for joint and dog clutch control. The second technology comprises a walking controller using a simulation-based optimization technique to consider passive joint dynamics instead of depending on the inverse kinematics problem, thereby enabling the control of the under-actuated leg. The last technology is model parameter identification to achieve unstable passive-based walking in real-world considering the body as well as environmental parameters such as ground slope. To the best of our knowledge, the proposed robot is the first to achieve both active and passive-based walking using a bipedal body. This enables the implementation of the passive-walking technology to active-joint robots and expands the application possibility of passive joint for bipedal robots.

This narrative review examines the use of inertial measurement units (IMUs) for assessing gait balance control. Impaired gait balance control is associated with an increased risk of falls and reduced mobility, particularly in older adults. Traditional methods of assessing gait balance control, such as clinical balance assessments and camera-based motion analysis, have limitations in terms of reliability, cost, and practicality. Wearable sensor technology, including IMUs, offers a more accessible and cost-effective alternative for assessing gait and balance performance in real-world settings. IMUs, equipped with tri-axial accelerometers, gyroscopes, and magnetometers, can directly measure body movement and provide quantifiable data. This review explores the advantages and limitations of using IMUs for assessing gait balance control, including the measurement of anticipatory postural adjustments (APAs) for gait initiation, spatiotemporal gait parameters, center of mass (COM) motion during walking, and data-driven machine learning models. IMUs have shown promise in quantifying APAs, estimating gait spatiotemporal parameters, assessing COM motion, and using machine learning algorithms to classify and predict balance-related outcomes. However, further research is needed to establish standardized protocols, validate IMU-based measurements, and determine the specific IMU parameters that correlate with balance control ability. Overall, IMUs have the potential to be a valuable tool for assessing gait balance control, monitoring changes over time, and tracking interventions to improve balance control in both clinical and research settings.

Children with cerebral palsy (CP) have been reported to have various levels of deficits in balance control, which can be described using the relationship between the body's centre of mass (COM) and the centre of pressure (COP). This study aimed to investigate the balance control of children with spastic diplegic CP during level walking. The COM-COP inclination angles and angular velocities, as well as temporal-spatial variables from 12 children with spastic diplegic CP (seven girls and five boys, aged 12.4 ± 4.4 years) and 12 normal controls (eight girls and four boys, aged 11.2 ± 4.4 years) were obtained using a motion analysis system and two forceplates. With compromised balance control as a result of neuromusculoskeletal pathologies, the CP group walked with reduced walking speed and stride length (p < 0.05), but increased stride time and step width (p < 0.05), indicating reduced gait efficiency. They also showed significantly reduced anterioposterior COM-COP inclination angles and angular velocities (p < 0.05), but increased mediolateral COM-COP inclination angles and angular velocities (p < 0.05) when compared to the normal controls. The latter phenomenon may be related to an increased risk of falling in these patients. Therefore, it appears that programs and/or devices for preventing falls are needed for children with spastic diplegic CP.

Tai-Chi Chuan (TCC) is thought to be a low-impact and effective exercise to improve balance capability in the elderly. However, the effects of TCC exercise on balance improvement remain controversial. The purpose of the current study was to investigate the effects of long-term Yang-Style TCC training on balance variables such as stable standing time and center of pressure (COP) movement patterns. Fifteen long-term Yang-Style TCC practitioners and fifteen age-matched adults performed different static balance tests each for 30 seconds. For each test, the time-varying COP positions were measured by two forceplates. The sway area of the COP was described by an equivalent ellipse, the two principal axes of which were obtained by using principal component analysis. The results showed that elderly subjects with long-term Yang-Style TCC training were able to maintain stable standing longer than those without TCC training, with reduced COP sway area during challenging tasks such as single-leg stance and tandem stance. It is suggested that long-term TCC exercise is a good choice in a training program aimed at reducing the risk of falling in the elderly.

Powered prosthetic feet (PPF) are designed to provide transtibial amputees (TTA) with active propulsion and range of motion similar to that of the biological limb. Previous studies have demonstrated the PPF’s ability to increase TTA walking speeds while reducing the energetic costs, however, little is known about its effects on dynamic balance control. The purpose of this pilot study was to assess dynamic balance control in TTA subjects during level ground walking and obstacle-crossing tasks. Control subjects ($n=6$) and TTA subjects ($n=4$) were instructed to complete a series of functional walking tasks. The TTA subjects completed the walking protocol twice, first in their passive energy-storing prosthetic foot (ESPF) and again in the prescribed PPF after two weeks of acclimation. Motion data were collected via a 10-camera system with a 53-marker and 15-segment body model. Whole body medial-lateral center of mass motion (displacement and peak velocity) was analyzed and used as a functional indicator of dynamic balance control. Findings indicate no difference in the dynamic balance control of TTA wearing the PPF compared to the ESPF. However, there was an observed trend of walking speed and obstacle height affecting balance control within the groups.

Falls are a multi-factor problem that poses a serious risk to the elderly. Approximately, 60% of falls are caused by a number of known factors, including the environment, which accounts for approximately 25–45% of falling risk. Most of the remainder results from a lack of personal balance control. Falling can cause long-term disabilities in the elderly, sometimes resulting in lower quality of life, and is also associated with increased medical expenses and personal care costs. In this study, we developed a falling assessment system to evaluate and classify individuals into four graded falling risk groups. During the test, all subjects were required to wear a self-developed dynamic measurement system and to perform two balance tests: a “Timed Up and Go Test” and a “30-Second Chair Stand Test.” We obtained 29 characteristic parameters from the data recorded during these tests. Next, we performed group classification. Eigenvalues were normalized, and a principal component analysis (PCA) was performed. After identifying informative characteristic parameters, support vector machine (SVM) was used to classify individuals as members of one of the four falling risk groups. These included low-, moderate-, high-, and extreme-risk groups. Using unreduced data of the 29 characteristic parameters extracted from the two balance tests, the accuracy of the SVM classification in allocating individuals to the correct group was 97.5%. After PCA, the 29 characteristic parameters were reduced to eight principal components, and the SVM classification method using these eight principal components was 93.25%.

The paper presents a new motion planning method for a biped robot. The method uses elevation map of the environment to plan the path of the feet and robot's body on rough terrain. We show how to incorporate modules which determine footholds, posture of the robot and check if the planned path is secure into a single general framework based on the Rapidly-exploring Random Trees. We describe the controller which stabilizes the robot during execution of the planned path. In the paper the implementation of the method for the Atlas robot in Gazebo environment is presented.

Legged locomotion of autonomous humanoid robots is advantageous but also challenging since it inherently suffers from high posture instability. External disturbances such as collisions with other objects or robots in the environment can cause a robot to fall. Many of the existing approaches for instability detection and falling prevention include a large number of sensors resulting in complex multi-sensor data fusion and are not decoupled from the walking motion planning. Such methods can not simply be integrated into an existing low-level controller for real-time motion generation and stabilization of a humanoid robot. A procedure that is both easily implementable using a minimal number of affordable sensors and capable of reliable detection of posture instabilities is missing to date. We propose a simple, yet reliable balance control technique consisting of a filtering module for the used data from two-axes-gyroscopes and -accelerometers located at the trunk, an instability classification algorithm, and a lunge step module. The modules are implemented on our humanoid robots which participate at the yearly RoboCup competitions in the humanoid kid-size league of soccer playing robots. Experimental results show that the approach is suited for real-time operation during walking.