Publications by authors named "Ayanori Yorozu"

Our research focuses on winter jujube trees and is conducted in a greenhouse environment in a structured orchard to effectively control various growth conditions. The development of a robotic system for winter jujube harvesting is crucial for achieving mechanized harvesting. Harvesting winter jujubes efficiently requires accurate detection and location.

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Background: Footsteps and walking trajectories during the Timed Up and Go test (TUG), and their relationships with spatiotemporal gait parameters during turning in people with Parkinson's disease (PD) and older people have not been clarified.

Research Question: We investigated the footsteps, walking trajectories, and spatiotemporal parameters during the TUG in PD, healthy older (HO), and healthy young (HY) subjects and the associations between the parameters of footsteps or walking trajectories and the spatiotemporal parameters during turning.

Methods: Twenty-six PD, 20 HO, and 20 HY subjects participated.

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Laser range sensor-based timed up and go (laser-TUG) test can evaluate performance in TUG subtasks (sit-to-walk [STW], walking a short distance, and turning). This study aimed to test the hypothesis that weaker hip abductor muscle strength is more significantly associated with slowed turning speed than with the other TUG subtasks (STW and straight walking) after controlling for quadriceps muscle strength in patients with knee osteoarthritis (OA). Community-dwelling participants with knee OA (Kellgren and Lawrence [K&L] grade ≥ 1; mean age, 68.

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For the evaluation of pathological gait, a machine learning-based estimation of the vertical ground reaction force (vGRF) using a low-cost insole is proposed as an alternative to costly force plates. However, learning a model for estimation still relies on the use of force plates, which is not accessible in small clinics and individuals. Therefore, this paper presents a force plate-free learning from a single leg stance (SLS) and natural walking measured only by the insoles.

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Climbing and descending stairs are demanding daily activities, and the monitoring of them may reveal the presence of musculoskeletal diseases at an early stage. A markerless system is needed to monitor such stair walking activity without mentally or physically disturbing the subject. Microsoft Kinect v2 has been used for gait monitoring, as it provides a markerless skeleton tracking function.

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Background: The Timed Up and Go (TUG) test may be a useful tool to detect not only mobility impairment but also possible cognitive impairment. In this cross-sectional study, we used the TUG test to investigate the associations between trajectory-based spatial parameters measured by laser range sensor (LRS) and cognitive impairment in community-dwelling older adults.

Methods: The participants were 63 community-dwelling older adults (mean age, 73.

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Purpose: The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals.

Methods: This study included 99 community-dwelling women aged 72.9 ± 6.

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Falling is a common problem in the growing elderly population, and fall-risk assessment systems are needed for community-based fall prevention programs. In particular, the timed up and go test (TUG) is the clinical test most often used to evaluate elderly individual ambulatory ability in many clinical institutions or local communities. This study presents an improved leg tracking method using a laser range sensor (LRS) for a gait measurement system to evaluate the motor function in walk tests, such as the TUG.

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For the prevention of falling in the elderly, gait training has been proposed using tasks such as the multi-target stepping task (MTST), in which participants step on assigned colored targets. This study presents a gait measurement system using a laser range sensor for the MTST to evaluate the risk of falling. The system tracks both legs and measures general walking parameters such as stride length and walking speed.

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