Falls are common among older people. Age-related changes in toe strength and force steadiness may increase fall risk. This study aimed to evaluate the performance of a fall risk prediction model using toe strength and force steadiness data as input variables. Participants were four healthy adults (25.5±1.7 yrs). To indirectly reproduce physical conditions of older adults, an experiment was conducted by adding conditions for weight and fatigue increase. The maximal strength (MVIC) was measured for 5 s using a custom toe dynamometer. For force steadiness, toe flexion was measured for 10 s according to the target line, which was 40% of the MVIC. A one-leg-standing test was performed for 10 s with eyes-opened using a force plate. Deep learning experiments were performed with seven conditions using long short-term memory (LSTM) algorithms. Results of the deep learning model were randomly mixed and expressed through a confusion matrix. Results showed potential of the model"s fall risk prediction with force steadiness data as input variables. However, experiments were conducted on young adults. Additional experiments should be conducted on older adults to evaluate the predictive model.
The purpose of the study was to evaluate the lumbar mobility and flexibility by the vertical vibration stimulation. The subjects were 21 young adults were divided into vibration group (n = 7) that applied 30 Hz vibration stimulation to the lumbar, foam roller group (n = 7) that relaxes the lumbar muscles with a foam roller, and good morning exercise group (n = 7) that stimulates the lumbar spine with the good morning exercise. The muscle strength, EMG and the sit & reach test were measured, to evaluate the lumbar mobility and flexibility before and after exercise intervention in each group. Results showed increasing in the vibrating group in muscle strength and EMG, and the good morning group and the vibrating group in the Sit & Reach test. This can be developed as a new alternative to exercise therapy for spine rehabilitation.
Many of the workers are exposed to work that burdens the musculoskeletal system, and musculoskeletal diseases, such as low back pain, are increasing every year. Various muscle support systems, such as wearable robots, have been developed to prevent musculoskeletal diseases at industrial sites, but the system is bulky. Therefore, the total weight is high, it is inconvenient to wear, and the wearer cannot freely perform the activities when power is not supplied. In this paper, in order to compensate for the shortcomings of the hard-type wearable robot system, a soft-type wearable suit using an elastic band was manufactured so that it is light and portable, as it does not require an actuator. The experiment was conducted to verify the effect of muscle strength assistance through an experiment (Measurement of Maximum Waist Torque and Measurement of the Approximate Dose) on the effect of the soft wearable suit. In addition, by making two different types of elastic bands in the wearable suit, it was possible to classify the more effective types for the waist and lower extremities according to the elasticity by comparing the muscle strength assisting effect according to the elastic band.
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EMG and Usability Assessment of Adjustable Stiffness Passive Waist-Assist Exoskeletons for Construction Workers Jung Sun Kang, Bo Ra Jeong, Eung-Pyo Hong, Bok Man Lim, Byung June Choi, Youn Baek Lee, Yun Hee Chang International Journal of Precision Engineering and Manufacturing.2025; 26(1): 227. CrossRef
Development of lifting-assistive passive functional pants for construction works Jin Zhi Chen, Jeong Eun Yoon, Zi Ying Liu, Sung Kyu Lee, Sumin Helen Koo Textile Research Journal.2025;[Epub] CrossRef
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Design development and evaluation of arm movement-assistive suits for lifting and movement for industrial workers considering wearability Jiwon Chung, Jung Eun Yoon, Soah Park, Hyunbin Won, Suhyun Ha, Sumin Helen Koo International Journal of Industrial Ergonomics.2024; 103: 103616. CrossRef
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Farming is a typical task that includes repetitive tasks, incomplete working positions, and weight work, along with exposure to a number of musculoskeletal diseases and harmful factors. Therefore, in this study, work clothes were developed for older agricultural workers exposed to musculoskeletal diseases and alienated from the medical system. Work clothes can help in repetitive cropping and support the load on the work, preventing and mitigating farmers" diseases. To verify the effectiveness of the developed clothing, six men in their 20s were evaluated for muscle usage before and after wearing the clothing in two ways: stoop lifting and squat lifting. The results of this study showed that the mass of most muscles, except the gastrocnemius muscle, was reduced during lifting operations by stoop lifting after wearing work clothes. The reason why the gastrocnemius was more activated was that the ankle joint was greatly activated by dorsal flexion. For squatting and lifting, most of the muscle usage was reduced. In future research, we want to analyze the muscle characteristics of actual agricultural workers on wearing work clothes.
This paper describes the development of a power assistive device controller with user intention detection for fire fighters. In order to detect the intention of users, an F/T sensor frame was designed for the power assistive device controller. Using the numerical approach, each directional strain value of the F/T sensor frame was evaluated singly to determine the optimum point to mount the strain gauge under varying load conditions. The numerical analysis was conducted using the commercial program Ansys v11.0. The finite element model for the F/T sensor frame consisted of 37,547 elements and 157,154 nodes. A sensor bonding device and calibration jig were designed for the F/T sensor frame. In an effort to obtain the decoupling matrix for the F/T sensor frame of the proposed power assist device, calibration tests were conducted in the x-direction, y-direction, z-direction, My-direction and Mz-direction. In addition, the operating system was tested using the power assistive device controller that comprised of the F/T sensor frame.
In this paper, we examine the exoskeleton robot which can support the muscular strength of the soldiers handling the front load and its applicability in the military field. In fact, in the questionnaire survey on the military applicability of exoskeleton robots, many soldiers reported that they felt immensely fatigued due to the heavy load on their back during the operation. Most of the exoskeleton robots in the military have been developed to reduce fatigue during the mobility and movement of soldiers. Research on the exoskeleton robots to support the waist has been carried out with emphasis on its role in assisting performance of repetitive work in the industrial field or the medical field. To examine the studies on conventional back support exoskeleton robots and to find out the functions required to apply a back-support exoskeleton robot to soldiers, we have classified the existing back support exoskeleton robots into power type, supported body, waterproof grades, and others based on weight, purpose, working time, etc. Apparently, the shape of the exoskeleton robot suitable for application in the military field and the required performance is presented in the present work.
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The purpose of this study was to develop and verify the smart insole based FSR sensor for measurement and improvement of the muscle strength imbalance. We recruited 15 subjects with muscle strength difference over 20% and 15 subjects with muscle strength balance below 10%. We developed the human body load insole and integrated modules using FSR sensor. Subjects walked for 5 minutes at a slope of 0% and a speed of 3 km / h on a treadmill with a smart insole. We measured the real-time muscle activity and foot pressure according to the muscle strength imbalance during gait. FSR data of the developed smart insole showed that the insole had similar accuracy and efficacy as muscle activity and foot pressure. This is the interval in which the muscle imbalance shifts from the stance phase to the load reaction, and the weight support is the largest, and the center of gravity of the human body passes over the whole foot, which is considered to cause the greatest imbalance. This suggests that there is a direct or indirect correlation between muscle strength imbalance of the lower limb and the imbalance of the body weight distribution during gait.
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Design and manufacturing of a smart insole Seung Joo Lee, Chae Young Park, In Hwan Lee Sensors and Actuators A: Physical.2026; 397: 117225. CrossRef
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