Younbaek Lee

Background: Two-thirds of people aged 65 years and older may require help with daily activities such as eating, bathing, and getting in and out of bed or a chair. Walking-assist wearable robots have shown significant improvements in physical function in controlled settings for patients. Objective: In this study, we aimed to assess the feasibility and the effect of a gait assistance and gait resistance training program using a walking-assist wearable robot for community-dwelling older adults. Methods: A total of 23 community-dwelling older adults aged 65 years and older (30 participants recruited, 7 dropped out) enrolled in a 12-session, 6-week gait assistance and gait resistance training program using a walking-assist wearable robot. A single-group, pre- and posttest design was employed to evaluate the feasibility based on program adherence and effectiveness. The primary and secondary outcomes for evaluating effectiveness were walking speed and functional performance, respectively. Results: Regarding the feasibility, the average number of sessions attended was 11.7 out of 12, indicating a mean adherence rate of 97.8%. Linear mixed model analysis revealed significant improvements in walking speed and functional performance at the end of the program compared with baseline. Specifically, the walking speed measured using the 10-Meter Walk Test, which includes self-selected velocity and fastest safe velocity, improved by a mean of 0.15 (SD 0.13) m/s (P<.001) and 0.15 (SD 0.17) m/s (P<.001), respectively. Functional performance also improved, with faster performance in Timed Up-and-Go (mean −0.63, SD 0.92 s; P=.003) and Four Square Step Test (mean −1.71, SD 1.64 s; P≤.001). Leg muscle strength increased across all measured domains, including plantarflexion (mean +7.29, SD 4.92; P=.004), hip adduction (mean +3.03, SD 2.73; P≤.001), hip extension (mean +2.63, SD 2.50; P≤.001), knee extension (mean +2.33, SD 3.12; P≤.001), knee flexion (mean +2.19, SD 2.17; P≤.001), dorsiflexion (mean +2.10, SD 3.06; P≤.001), hip abduction (mean +1.59, SD 1.92; P=.002), and hip flexion (mean +0.90, SD 1.56; P≤.001). Conclusions: This study stands out for applying gait assistance and resistance training across various terrains, unlike previous studies that only tested gait assistance in controlled environments. The results demonstrated significant improvements in walking speed and functional performance in older adults, suggesting the effectiveness of preventive health care services using a walking-assist wearable robot as an intervention that can contribute to improving independent functioning and frailty among community-dwelling older adults.

In highly mobile workplaces, wearable walking-assistant devices reduce muscle fatigue in workers’ lower extremities and increase energy efficiency. In our study, we verify this following the development of an ultralight wearable hip exoskeleton for industrial workers. Ten healthy male adults participated in this study, and their muscle activity, muscle fatigue, and energy expenditure were compared with and without a device while walking on a treadmill and going up stairs. While walking on a treadmill with the assistive device, muscle fatigue in the gastrocnemius decreased by 79.5%, and oxygen uptake and energy expenditure per minute decreased by 7.9% and 7.4%, respectively. While climbing stairs with the assistive device, muscle fatigue of the tibialis anterior decreased by 83.5%, average muscle activity of the rectus femoris, semitendinosus, and gastrocnemius muscles decreased significantly, and oxygen uptake and energy expenditure decreased by 14% and 12.9% per minute, respectively. We confirm that an ultralight wearable hip exoskeleton helps the wearer reduce lower-limb muscle fatigue and use metabolic energy more efficiently. The results of this study are intended as basic data to expand the use of ultralight wearable hip exoskeletons at industrial sites and to improve device performance.

In this study, we propose an interaction control framework for gait assistance and resistance using a robotic exoskeleton. We define a smoothed state variable that represents joint angle movements while walking. Furthermore, a self-feedback controller is designed with the delayed output state. By applying an appropriate time-delay and positive or negative feedback gain to the state variable, we can generate assistive or resistive torque stably without any gait phase or environment recognition. The time-delayed selffeedback controller reflects the movement of the wearer's joints at every moment of control, thereby stably coping with sudden task transitions (e.g., walk-stop-walk, forward-backward walking) as well as walking speed or environment changes. Case studies involved gait assistance with a knee exoskeleton and gait assistance and resistance with a hip exoskeleton. We performed various preliminary tests including metabolic energy measurements and a comparison of the positive or negative power of the generated torque profiles. The results show the flexibility and effectiveness of the proposed interaction control method for gait assistive or resistive training.

This paper presents a novel wearable walking assistance device for the elderly, designed to aid them in their physical gait. In compliance with human motion and the human body, the device not only fits tightly to the lower body of a wearer, but also transmits the assisting torque to the hip/knee joint efficiently and comfortably. To overcome the poor wearability and assistive performance of conventional wearable walking assistance devices, three novel mechanisms are proposed: 1) a dual reduction actuator, which makes the mechanism more compact with minimal resistance, 2) compliant joints, which adapt to human motion regardless of the wearing state, wearing position, and three-dimensional human joint motions, 3) a flexible foot/ankle mechanism, which helps in rigidly transmitting the assisting force only to the forefoot. The developed wearable walking assistance device based on these mechanisms was validated through experiments.

This paper presents a novel wearable walking assistance device for the elderly to provide physical gait assistance. The wearable device, to be worn invisibly underneath clothes, not only fits tightly to the wearer's lower body, but also comfortably transmits assistive torque to the wearer's hip/knee joint. To overcome deficiencies in the usability of conventional wearable walking assistance devices, two novel features are proposed: 1) a unique flexible support frame that withstands vertical loads while maintaining the natural curvature of the wearer's lower body; and 2) a kinematically similar anthropomorphic joint that minimizes the unintended resistance force during the wearer's usual motions. The developed wearable walking assistance device based on these features was verified by simulations and experiments whose results are described.

This paper presents a novel self-aligning knee mechanism for walking assistance devices for the elderly to provide physical gait assistance. Self-aligning knee joints can assist in flexion/extension motions of the knee joint and compensate the knee's transitional movements in the sagittal plane. In order to compensate the center of rotation, which moves with the flexion/extension motion of the human knee joint, a self-aligning knee joint is proposed that adds redundant degrees of freedom (i.e., 2-DoF) to the 1-DoF revolute joint. The key idea of the proposed mechanism is to decouple joint rotations and translations for use in lower-extremity wearable devices. This paper describes the mechanical design of this self-aligning knee mechanism and its implementation on a wearable robot and in preliminary experiments. The performance of the proposed mechanism is verified by simulations and experiments.